HEALTHONLINEUS

# Medical Information Platform OpenEvidence Achieves $1 Billion Valuation

## Introduction

OpenEvidence, a cutting-edge medical information platform, has reached a significant milestone by achieving a $1 billion valuation. This achievement underscores the growing importance of artificial intelligence (AI) and big data in the healthcare industry. OpenEvidence leverages AI to provide real-time, evidence-based medical insights, helping healthcare professionals make informed decisions.

## What is OpenEvidence?

OpenEvidence is an AI-powered medical information platform designed to assist doctors, researchers, and healthcare organizations in accessing the latest clinical evidence. By analyzing vast amounts of medical literature, clinical trials, and real-world data, OpenEvidence provides accurate and up-to-date recommendations for patient care.

The platform uses natural language processing (NLP) and machine learning to extract relevant insights from medical research, ensuring that healthcare professionals have access to the most current and reliable information.

## Factors Behind OpenEvidence’s $1 Billion Valuation

Several key factors have contributed to OpenEvidence reaching a $1 billion valuation:

### 1. **Growing Demand for AI in Healthcare**
The healthcare industry is increasingly relying on AI-driven solutions to improve patient outcomes and streamline clinical decision-making. OpenEvidence’s ability to provide real-time, evidence-based insights has positioned it as a valuable tool for medical professionals.

### 2. **Strong Investor Confidence**
OpenEvidence has attracted significant investment from venture capital firms and healthcare technology investors. The company’s innovative approach to medical information management has garnered the attention of major players in the industry, leading to substantial financial backing.

### 3. **Regulatory Support for Evidence-Based Medicine**
Governments and healthcare organizations worldwide are emphasizing the importance of evidence-based medicine. OpenEvidence aligns with this trend by offering a platform that ensures medical decisions are backed by the latest scientific research.

### 4. **Integration with Electronic Health Records (EHRs)**
OpenEvidence seamlessly integrates with electronic health record (EHR) systems, allowing doctors to access relevant medical insights directly within their workflow. This integration enhances efficiency and improves patient care.

### 5. **Advancements in AI and Big Data**
The rapid advancements in AI and big data analytics have enabled OpenEvidence to continuously improve its platform. By leveraging machine learning algorithms, the company can refine its recommendations and provide more accurate medical insights.

## Impact on the Healthcare Industry

The success of OpenEvidence has significant implications for the healthcare industry:

– **Improved Patient Outcomes:** By providing doctors with real-time, evidence-based recommendations, OpenEvidence helps improve diagnosis accuracy and treatment effectiveness.
– **Reduced Medical Errors:** Access to up-to-date medical research reduces the likelihood of outdated or incorrect treatments being administered.
– **Enhanced Medical Research:** Researchers can use OpenEvidence to quickly analyze large volumes of medical literature, accelerating the discovery of new treatments and therapies.
– **Cost Savings:** By optimizing treatment decisions, OpenEvidence can help reduce unnecessary medical procedures and hospital readmissions, leading to cost savings for healthcare providers and insurers.

## Future Prospects

With its $1 billion valuation, OpenEvidence is poised for further growth and expansion. The company is likely to invest in:

– **Expanding its AI capabilities** to enhance the accuracy and speed of its medical insights.
– **Partnering with more healthcare institutions** to integrate its platform into clinical workflows.
– **Exploring global markets** to bring its evidence-based medical insights to healthcare professionals worldwide.

## Conclusion

OpenEvidence’s achievement of a $1 billion valuation highlights the increasing role of AI in transforming healthcare. By providing real-time, evidence-based medical insights, the platform is helping doctors make better decisions, improving patient outcomes, and shaping the future of evidence-based medicine. As AI continues to advance, OpenEvidence is well-positioned to remain a leader in the medical information space.

# **Corti and Wolters Kluwer Partner to Expand Access to Clinical Content**

In a significant move to enhance healthcare efficiency and patient outcomes, **Corti**, a leading artificial intelligence (AI) company, has partnered with **Wolters Kluwer**, a global provider of professional information, software solutions, and services. This collaboration aims to expand access to high-quality clinical content, empowering healthcare professionals with advanced decision-support tools.

## **The Partnership: A Game-Changer in Healthcare**

The partnership between Corti and Wolters Kluwer is set to revolutionize the way healthcare providers access and utilize clinical information. By integrating **Corti’s AI-powered solutions** with **Wolters Kluwer’s trusted medical content**, the collaboration seeks to improve diagnostic accuracy, streamline workflows, and enhance patient care.

### **Who Are Corti and Wolters Kluwer?**

– **Corti** is an AI-driven company specializing in **speech recognition and decision-support technology** for healthcare providers. Its AI solutions analyze patient interactions in real time, offering insights that help clinicians make more informed decisions.
– **Wolters Kluwer** is a globally recognized provider of **clinical decision support, medical research, and healthcare technology solutions**. Its flagship products, such as **UpToDate® and Lexicomp®**, are widely used by medical professionals to access evidence-based clinical information.

## **How This Partnership Benefits Healthcare Providers**

The integration of Corti’s AI with Wolters Kluwer’s clinical content offers several key advantages:

### **1. Enhanced Clinical Decision Support**
By combining **Corti’s AI-driven analysis** with **Wolters Kluwer’s evidence-based medical content**, healthcare professionals can receive **real-time, data-driven recommendations** during patient interactions. This helps in **reducing diagnostic errors** and improving treatment decisions.

### **2. Improved Workflow Efficiency**
Healthcare providers often face **information overload** and administrative burdens. This partnership enables **seamless access** to relevant clinical guidelines and best practices, reducing the time spent searching for information and allowing clinicians to focus more on patient care.

### **3. Increased Access to Trusted Medical Knowledge**
With **Wolters Kluwer’s extensive database** of medical knowledge integrated into **Corti’s AI platform**, healthcare professionals can quickly retrieve **reliable, up-to-date clinical information** at the point of care. This ensures that medical decisions are based on the latest research and guidelines.

### **4. Better Patient Outcomes**
By providing **real-time decision support**, the partnership helps clinicians make **more accurate diagnoses and treatment plans**, leading to **better patient outcomes** and **fewer medical errors**.

## **The Future of AI in Healthcare**

The collaboration between Corti and Wolters Kluwer highlights the growing role of **AI in healthcare**. As AI-powered solutions continue to evolve, they are expected to:

– **Enhance predictive analytics** for early disease detection.
– **Improve patient engagement** through personalized healthcare recommendations.
– **Reduce clinician burnout** by automating administrative tasks.

This partnership sets a precedent for how **AI and evidence-based medical content** can work together to create a **more efficient, accurate, and patient-centered healthcare system**.

## **Conclusion**

The partnership between **Corti and Wolters Kluwer** marks a **major advancement in clinical decision support**. By integrating **AI-driven insights** with **trusted medical knowledge**, this collaboration is poised to **transform healthcare delivery**, ensuring that providers have the best tools to make informed, life-saving decisions. As AI continues to shape the future of medicine, partnerships like this will play a crucial role in improving healthcare accessibility, efficiency, and patient care worldwide.

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# German-Style Oven-Baked Pancake (Dutch Baby)

A **German-style oven-baked pancake**, commonly known as a **Dutch Baby**, is a delicious and visually impressive dish that has gained popularity for its unique texture and ease of preparation. This puffy, golden-brown pancake is baked in the oven rather than cooked on a stovetop, making it a great choice for breakfast, brunch, or even dessert.

## **Origins of the Dutch Baby**

Despite its name, the Dutch Baby is not actually Dutch. It is believed to have originated in the United States, inspired by German **Pfannkuchen** or **Pfannkuchen-style pancakes**. The dish became popular in the early 1900s when it was introduced at a Seattle restaurant called *Manca’s Café*. The name “Dutch Baby” is thought to have come from a mispronunciation of “Deutsch,” which means “German” in German.

## **What Makes a Dutch Baby Unique?**

Unlike traditional pancakes that are cooked on a griddle or frying pan, a Dutch Baby is baked in a preheated cast-iron skillet or oven-safe pan. The batter, which is similar to that of a Yorkshire pudding or popover, is poured into the hot skillet, causing it to puff up dramatically as it bakes. The result is a crispy, golden-brown exterior with a soft, custard-like center.

## **Ingredients for a Classic Dutch Baby**

A basic Dutch Baby requires only a few simple ingredients:

– **3 large eggs**
– **½ cup (120ml) milk** (whole milk works best)
– **½ cup (60g) all-purpose flour**
– **1 tablespoon sugar**
– **½ teaspoon vanilla extract** (optional, for added flavor)
– **¼ teaspoon salt**
– **2 tablespoons unsalted butter** (for greasing the skillet)

### **Optional Toppings:**
– Powdered sugar
– Fresh berries (strawberries, blueberries, raspberries)
– Maple syrup or honey
– Lemon juice
– Whipped cream

## **How to Make a Dutch Baby**

### **Step 1: Preheat the Oven and Skillet**
Preheat your oven to **425°F (220°C)**. Place a **cast-iron skillet (or oven-safe pan)** in the oven while it heats up. This step is crucial because a hot skillet helps the pancake rise properly.

### **Step 2: Prepare the Batter**
In a blender, combine the eggs, milk, flour, sugar, vanilla extract, and salt. Blend for about **20-30 seconds** until the batter is smooth and slightly frothy. If you don’t have a blender, you can whisk the ingredients together in a bowl until well combined.

### **Step 3: Melt the Butter**
Carefully remove the hot skillet from the oven and add the butter. Swirl it around to coat the bottom and sides of the pan.

### **Step 4: Pour and Bake**
Quickly pour the batter into the hot skillet and immediately place it back in the oven. Bake for **15-20 minutes**, or until the pancake is puffed up and golden brown.

### **Step 5: Serve Immediately**
Once baked, remove the Dutch Baby from the oven. It will begin to deflate slightly as it cools, which is normal. Dust with powdered sugar, add your favorite toppings, and serve immediately.

## **Variations and Flavor Twists**

While the classic Dutch Baby is simple and delicious, you can experiment with different flavors and ingredients:

– **Cinnamon Apple Dutch Baby** – Add thinly sliced apples and a sprinkle of cinnamon before baking.
– **Chocolate Dutch Baby** – Mix cocoa powder into the batter for a rich, chocolatey version.
– **Savory Dutch Baby** – Skip the sugar and vanilla, and instead add cheese, herbs, or sautéed vegetables for a savory twist.

## **Tips for the Perfect Dutch Baby**

– **Use a hot skillet** – A well-heated pan ensures the pancake puffs up properly.
– **Blend the batter well** – A smooth, airy batter helps create the signature texture.
– **Don’t open the oven door** – Avoid opening the oven while baking, as this can cause the pancake to deflate prematurely.
– **Serve immediately** – Dutch Babies are best enjoyed fresh out of the oven while they are still puffy and warm.

## **Conclusion**

The **German-style oven-baked pancake (Dutch Baby)** is a delightful dish that is both easy to make and visually stunning. Whether you enjoy it sweet or savory, this versatile pancake is sure to impress your family and guests. With just a few basic ingredients and a hot oven, you can

# AI Model Predicts Progression of Schizophrenia and Bipolar Disorder

## Introduction

Schizophrenia and bipolar disorder are severe mental health conditions that affect millions of people worldwide. These disorders are often difficult to diagnose and manage due to their complex and variable progression. However, recent advancements in artificial intelligence (AI) are offering new hope for early detection and personalized treatment. Researchers have developed AI models that can predict the progression of schizophrenia and bipolar disorder, potentially improving patient outcomes and reducing healthcare costs.

## Understanding Schizophrenia and Bipolar Disorder

Schizophrenia is a chronic brain disorder characterized by hallucinations, delusions, and cognitive impairments. It typically emerges in late adolescence or early adulthood and can lead to significant disability if not managed effectively.

Bipolar disorder, on the other hand, is a mood disorder marked by extreme mood swings, including manic (high-energy) and depressive (low-energy) episodes. Like schizophrenia, it can severely impact a person’s daily life, relationships, and overall well-being.

Both disorders are believed to have genetic, environmental, and neurobiological components, making their diagnosis and treatment highly complex.

## The Role of AI in Mental Health

Artificial intelligence has revolutionized various fields, including healthcare. In psychiatry, AI models can analyze vast amounts of data, such as brain scans, genetic information, and patient histories, to identify patterns that may not be easily detectable by human clinicians.

By leveraging machine learning algorithms, AI can predict how a mental health condition will progress in an individual, allowing for early intervention and personalized treatment plans.

## How AI Predicts the Progression of Schizophrenia and Bipolar Disorder

### 1. **Analyzing Brain Imaging Data**
AI models can process neuroimaging data, such as MRI and fMRI scans, to detect structural and functional abnormalities in the brain. Studies have shown that changes in brain connectivity and volume can indicate the likelihood of schizophrenia or bipolar disorder worsening over time.

### 2. **Tracking Behavioral and Cognitive Patterns**
AI can analyze speech patterns, facial expressions, and cognitive performance to assess a patient’s mental state. For example, subtle changes in speech coherence or reaction times may indicate an impending psychotic episode in schizophrenia patients.

### 3. **Genetic and Biomarker Analysis**
Machine learning algorithms can examine genetic markers and blood biomarkers associated with schizophrenia and bipolar disorder. By identifying specific genetic variations, AI can predict an individual’s risk of developing severe symptoms or experiencing relapses.

### 4. **Electronic Health Records and Patient Data**
AI can analyze electronic health records (EHRs) to track medication adherence, hospital visits, and treatment responses. By recognizing patterns in a patient’s medical history, AI can predict potential relapses and suggest adjustments to treatment plans.

## Benefits of AI in Mental Health Prediction

### **1. Early Detection and Intervention**
AI models can detect warning signs of schizophrenia and bipolar disorder before severe symptoms appear. Early intervention can help prevent full-blown psychotic or manic episodes, improving long-term outcomes.

### **2. Personalized Treatment Plans**
By analyzing individual patient data, AI can recommend tailored treatment strategies, including medication adjustments and therapy options, to optimize patient care.

### **3. Reduced Hospitalizations and Healthcare Costs**
Predicting relapses and disease progression can help prevent emergency hospitalizations, reducing the financial burden on healthcare systems and improving patient quality of life.

### **4. Improved Accuracy in Diagnosis**
AI can assist psychiatrists in differentiating between schizophrenia, bipolar disorder, and other mental health conditions, leading to more accurate diagnoses and appropriate treatments.

## Challenges and Ethical Considerations

While AI holds great promise, there are challenges and ethical concerns that must be addressed:

– **Data Privacy and Security:** Patient data must be protected to prevent unauthorized access and misuse.
– **Bias in AI Models:** AI algorithms must be trained on diverse datasets to ensure they are not biased against certain populations.
– **Human Oversight:** AI should complement, not replace, human psychiatrists. Clinical decisions should always involve medical professionals.
– **Accessibility:** AI-based mental health tools should be made accessible to all patients, regardless of socioeconomic status.

## Future of AI in Mental Health

As AI technology continues to evolve, its role in mental health care will expand. Future advancements may include:

– **Wearable AI Devices:** Smartwatches and mobile apps that monitor mental health indicators in real time.
– **AI-Powered Chatbots:** Virtual therapists that provide immediate support and guidance to patients.
– **Integration with Telemedicine:** AI-driven mental health assessments that enhance remote psychiatric care.

## Conclusion

AI models predicting the progression of schizophrenia and bipolar disorder represent a groundbreaking advancement in mental health care. By leveraging machine learning and big data, these models can improve early detection, personalize treatment, and enhance patient outcomes

# Detailed 7-Day High Protein Diet Meal Framework for Optimal Nutritional Intake

Recently, high-protein diets have surged in popularity due to their possible advantages for weight control, muscle development, and general health. A protein-rich diet may assist in keeping you satiated for longer periods, diminish cravings, and facilitate muscle recovery and growth. This article outlines a detailed 7-day high-protein meal framework aimed at delivering optimal nourishment while maintaining variety and enjoyment in your meals.

## Grasping Protein Requirements

Before we dive into the meal framework, it’s critical to comprehend your protein requirements. The Recommended Dietary Allowance (RDA) for protein stands at 0.8 grams per kilogram of body weight. However, if you’re regularly active or aiming to increase muscle mass, your protein needs might rise to between 1.2 and 2.0 grams per kilogram.

## Important Advantages of a High-Protein Diet

1. **Weight Control**: High-protein diets can boost feelings of fullness, aiding in hunger management and lowering overall calorie consumption.
2. **Muscle Maintenance**: Sufficient protein consumption is vital for preserving muscle mass, particularly during weight loss.
3. **Metabolic Enhance**: Protein possesses a greater thermic effect compared to fats or carbohydrates, implying your body expends more calories to digest protein.
4. **Enhanced Recovery**: Protein supports muscle repair and recuperation after physical activity.

## 7-Day High Protein Meal Framework

### Day 1

– **Breakfast**: Scrambled eggs (3) with spinach and feta cheese; 1 slice of whole-grain toast.
– **Snack**: Greek yogurt (200g) with a handful of mixed berries.
– **Lunch**: Grilled chicken breast (150g) with quinoa (1 cup) and steamed broccoli.
– **Snack**: Hummus (100g) with carrot and cucumber sticks.
– **Dinner**: Baked salmon (200g) with asparagus and sweet potato (1 medium).

### Day 2

– **Breakfast**: Protein smoothie with whey protein (1 scoop), banana, spinach, and almond milk.
– **Snack**: Cottage cheese (200g) with pineapple chunks.
– **Lunch**: Turkey and avocado wrap in a whole-grain tortilla with mixed greens.
– **Snack**: Hard-boiled eggs (2).
– **Dinner**: Stir-fried tofu (200g) with mixed vegetables and brown rice (1 cup).

### Day 3

– **Breakfast**: Overnight oats made with rolled oats (1/2 cup), chia seeds, and almond milk topped with sliced almonds.
– **Snack**: Edamame (1 cup).
– **Lunch**: Lentil salad with cherry tomatoes, cucumber, and feta cheese.
– **Snack**: Protein bar (ensure low sugar).
– **Dinner**: Grilled shrimp (200g) with zucchini noodles and marinara sauce.

### Day 4

– **Breakfast**: Omelet with 3 eggs, bell peppers, onions, and cheese.
– **Snack**: Sliced apple with almond butter (2 tablespoons).
– **Lunch**: Quinoa salad with black beans, corn, and diced peppers.
– **Snack**: Beef jerky (30g).
– **Dinner**: Baked chicken thighs (200g) with roasted Brussels sprouts and brown rice (1 cup).

### Day 5

– **Breakfast**: Chia seed pudding made with almond milk, topped with berries.
– **Snack**: Greek yogurt (200g) with honey and walnuts.
– **Lunch**: Tuna salad with mixed greens, cherry tomatoes, and olive oil dressing.
– **Snack**: Celery sticks with peanut butter (2 tablespoons).
– **Dinner**: Grilled pork tenderloin (200g) with sautéed green beans and quinoa (1 cup).

### Day 6

– **Breakfast**: Smoothie bowl with protein powder, banana, spinach, and topped with granola.
– **Snack**: Cottage cheese (200g) with sliced peaches.
– **Lunch**: Chicken Caesar salad with romaine lettuce, grilled chicken (150g), and Parmesan cheese.
– **Snack**: Mixed nuts (30g).
– **Dinner**: Baked cod (200g) with roasted vegetables and a side of couscous (1 cup).

### Day 7

– **Breakfast**: Whole-grain pancakes made with protein powder, topped with fresh fruit.
– **Snack**: Hard-boiled eggs (2).
– **Lunch**: Beef stir-fry with broccoli, bell peppers, and brown rice (1 cup).
– **Snack**: Protein shake.
– **Dinner**: Grilled lamb chops (200g) with mashed cauliflower and steamed carrots.

## Strategies for Success

1. **Maintain Hydration**: Ensure you drink ample water throughout the day to assist with digestion and overall wellness.

# **Coreline Soft Expands to Australia and Other Industry Updates**

## **Coreline Soft’s Global Expansion**

Coreline Soft, a leading provider of artificial intelligence (AI)-powered medical imaging solutions, has announced its expansion into Australia. This move marks a significant milestone in the company’s global growth strategy, as it seeks to bring its cutting-edge AI-driven diagnostic tools to more healthcare providers worldwide.

The South Korea-based company specializes in AI solutions for medical imaging, particularly in lung disease detection and diagnosis. Its flagship product, **AVIEW**, is widely used for lung cancer screening, chest CT analysis, and other radiological applications. With the increasing demand for AI-assisted diagnostics, Coreline Soft’s entry into the Australian market is expected to enhance early disease detection and improve patient outcomes.

Australia has been actively adopting AI in healthcare, with government initiatives supporting digital health transformation. Coreline Soft’s expansion aligns with this trend, offering Australian hospitals and radiology centers access to advanced AI-powered imaging solutions.

## **Key Benefits of Coreline Soft’s Expansion**

1. **Improved Lung Disease Detection** – Coreline Soft’s AI technology enhances the accuracy and efficiency of lung disease diagnosis, including lung cancer and chronic obstructive pulmonary disease (COPD).
2. **Faster Radiological Analysis** – AI-powered imaging solutions reduce the time required for radiologists to analyze CT scans, leading to quicker diagnoses and treatment decisions.
3. **Support for National Screening Programs** – Australia has been strengthening its lung cancer screening programs, and Coreline Soft’s solutions can play a crucial role in early detection efforts.
4. **Collaboration with Local Healthcare Providers** – The company is expected to partner with Australian hospitals, research institutions, and radiology centers to integrate AI into clinical workflows.

## **Other Industry Updates in AI-Powered Medical Imaging**

### **1. Increased Adoption of AI in Lung Cancer Screening**
Lung cancer remains one of the leading causes of cancer-related deaths worldwide. AI-driven imaging solutions, like those developed by Coreline Soft, are being increasingly integrated into national screening programs in countries such as the U.S., the U.K., and South Korea. These technologies help detect lung nodules at an early stage, improving survival rates.

### **2. Regulatory Approvals for AI-Based Diagnostics**
Regulatory bodies, including the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA), have been granting approvals for AI-based medical imaging solutions. This trend is expected to continue, allowing more AI-driven tools to be implemented in clinical settings.

### **3. Expansion of AI in Other Medical Imaging Fields**
While lung imaging has been a major focus, AI is also making strides in other areas, such as brain imaging for stroke detection, breast cancer screening, and musculoskeletal imaging. Companies are developing AI models that assist radiologists in detecting abnormalities more efficiently.

### **4. Growing Investments in AI Healthcare Startups**
Venture capital funding for AI-driven healthcare startups has been on the rise. Companies specializing in AI-powered diagnostics, predictive analytics, and personalized medicine are attracting significant investments, indicating strong industry growth.

## **Conclusion**

Coreline Soft’s expansion into Australia represents a major step in the global adoption of AI-powered medical imaging. As AI continues to revolutionize radiology, healthcare providers worldwide are embracing these technologies to enhance diagnostic accuracy and efficiency. With ongoing advancements and regulatory approvals, the future of AI in medical imaging looks promising, paving the way for improved patient care and early disease detection.

Stay tuned for more updates as AI-driven healthcare solutions continue to transform the industry.

# Rye Flour Crepes: A Nutritious and Flavorful Twist on a Classic Recipe

Crepes are a beloved dish enjoyed worldwide for their versatility and delicate texture. Traditionally made with all-purpose flour, crepes can be adapted to incorporate different types of flour for added nutrition and unique flavors. One such variation is **rye flour crepes**, which offer a wholesome and slightly nutty alternative to the classic recipe.

## **Why Choose Rye Flour?**

Rye flour is a nutrient-dense grain that has been a staple in European cuisine for centuries. It is commonly used in bread-making but also works wonderfully in crepes. Here are some reasons why rye flour is a great choice:

– **Rich in Fiber** – Rye flour contains more fiber than refined wheat flour, promoting better digestion and prolonged satiety.
– **Lower Glycemic Index** – Compared to white flour, rye flour has a lower glycemic index, meaning it helps regulate blood sugar levels.
– **Packed with Nutrients** – Rye flour is a good source of essential nutrients such as magnesium, iron, and B vitamins.
– **Distinctive Flavor** – Rye flour has a slightly earthy, nutty taste that adds depth to both sweet and savory crepes.

## **How to Make Rye Flour Crepes**

Making rye flour crepes is simple and requires just a few ingredients. The process is similar to traditional crepes, but with a slight adjustment to accommodate the denser nature of rye flour.

### **Ingredients:**
– 1 cup rye flour
– 1 cup milk (or a dairy-free alternative)
– 2 eggs
– 1 tablespoon melted butter or oil
– ½ teaspoon salt
– 1 teaspoon honey or sugar (optional, for sweet crepes)
– ½ cup water (adjust as needed for consistency)

### **Instructions:**

1. **Mix the Batter** – In a mixing bowl, whisk together the rye flour and salt. In a separate bowl, beat the eggs, then add the milk, melted butter, and honey (if using). Gradually add the wet ingredients to the dry ingredients, whisking continuously to avoid lumps. Add water as needed to achieve a thin, pourable consistency.

2. **Rest the Batter** – Let the batter rest for at least 15–30 minutes. This allows the flour to absorb the liquid and results in a smoother texture.

3. **Cook the Crepes** – Heat a non-stick skillet or crepe pan over medium heat and lightly grease it with butter or oil. Pour a small amount of batter into the pan, swirling to spread it evenly. Cook for about 1–2 minutes until the edges lift slightly, then flip and cook for another 30 seconds.

4. **Serve and Enjoy** – Stack the crepes on a plate and keep them warm. Fill them with your favorite sweet or savory ingredients and enjoy!

## **Delicious Filling Ideas**

Rye flour crepes pair well with a variety of fillings. Here are some ideas to try:

### **Sweet Fillings:**
– **Honey and Nuts** – Drizzle with honey and sprinkle with chopped almonds or walnuts.
– **Berries and Yogurt** – Fill with fresh berries and Greek yogurt for a refreshing treat.
– **Dark Chocolate and Banana** – Spread a thin layer of dark chocolate and add banana slices.

### **Savory Fillings:**
– **Smoked Salmon and Cream Cheese** – A classic combination with a rye twist.
– **Mushrooms and Spinach** – Sautéed mushrooms and spinach with a touch of garlic make for a hearty filling.
– **Egg and Cheese** – Scrambled eggs and melted cheese create a satisfying breakfast option.

## **Final Thoughts**

Rye flour crepes are a fantastic way to add nutrition and depth of flavor to a classic dish. Whether you prefer them sweet or savory, they offer a wholesome and delicious alternative to traditional crepes. Give them a try and enjoy the rich taste and health benefits of rye flour in your next meal!

Would you like more recipe variations or tips on working with rye flour? Let us know in the comments!

# Millie Raises $12M to Expand Its Maternity Care Platform

## **Introduction**

Millie, a pioneering maternity care startup, has successfully secured $12 million in Series A funding to expand its innovative maternal healthcare platform. The funding round was led by Maverick Ventures, with participation from other investors, including TMV, BBG Ventures, and Venn Growth Partners. This investment will enable Millie to enhance its services, scale its operations, and improve maternal health outcomes across the United States.

## **About Millie and Its Mission**

Millie was founded with the goal of transforming maternity care by offering a more integrated and patient-centered approach. The company provides a hybrid model of care that combines virtual and in-person services, ensuring that pregnant individuals receive comprehensive support throughout their journey.

Millie’s platform focuses on addressing gaps in maternal healthcare, particularly for women of color and underserved communities who often face disparities in access and quality of care. By leveraging technology and a team of experienced healthcare professionals, Millie aims to reduce maternal mortality rates and improve overall pregnancy experiences.

## **How Millie’s Maternity Care Platform Works**

Millie’s platform offers a range of services designed to support expecting mothers from pregnancy through postpartum recovery. Some of its key features include:

– **Virtual and In-Person Care:** Patients can access healthcare providers through telehealth consultations and in-person visits at Millie’s clinics.
– **Personalized Care Plans:** The platform provides customized maternity care plans tailored to each patient’s needs.
– **24/7 Support:** Expecting mothers can receive continuous support from midwives, doulas, and other healthcare professionals.
– **Postpartum Care:** Millie extends its services beyond childbirth, ensuring that new mothers receive the necessary care and guidance during the critical postpartum period.
– **Focus on Health Equity:** The company prioritizes addressing racial and socioeconomic disparities in maternal healthcare by making its services more accessible and inclusive.

## **The Importance of Millie’s Expansion**

The $12 million funding will allow Millie to expand its reach and enhance its offerings in several key ways:

1. **Opening New Clinics:** Millie plans to establish additional physical locations to provide in-person maternity care services.
2. **Enhancing Technology:** The company will invest in its digital platform to improve telehealth capabilities and patient engagement.
3. **Expanding Provider Network:** Millie aims to recruit more healthcare professionals, including midwives, obstetricians, and doulas, to support a growing patient base.
4. **Improving Accessibility:** The funding will help Millie reach more underserved communities, ensuring that high-quality maternity care is available to all.

## **Addressing the Maternal Health Crisis**

The United States has one of the highest maternal mortality rates among developed nations, with significant disparities affecting Black and Indigenous women. Millie’s model seeks to address these issues by providing a more holistic and equitable approach to maternity care.

By integrating midwifery-led care with modern technology, Millie is helping to bridge the gap between traditional healthcare systems and the personalized support that many expecting mothers need. The company’s expansion comes at a crucial time when improving maternal health outcomes is a national priority.

## **Conclusion**

Millie’s successful $12 million funding round marks a significant milestone in the company’s mission to revolutionize maternity care. With plans to expand its services, enhance its technology, and reach more communities, Millie is poised to make a lasting impact on maternal health in the U.S. As the demand for better maternity care continues to grow, Millie’s innovative approach offers hope for a future where every mother receives the care and support she deserves.

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# Frontera Secures $32M in Seed Funding to Launch Operations

**Introduction**

Frontera, a promising new player in the technology and logistics sector, has successfully secured $32 million in seed funding to kickstart its operations. This substantial investment marks a significant milestone for the company as it prepares to disrupt the industry with its innovative solutions. The funding round was led by prominent venture capital firms and strategic investors who recognize Frontera’s potential to revolutionize cross-border trade and logistics.

**About Frontera**

Frontera is a technology-driven company focused on streamlining cross-border trade and logistics. By leveraging artificial intelligence, blockchain, and automation, the company aims to simplify the complexities of international commerce, making it more efficient, transparent, and cost-effective. Frontera’s platform is designed to help businesses navigate regulatory challenges, optimize supply chain operations, and reduce delays in cross-border transactions.

**Details of the Funding Round**

The $32 million seed funding round was led by top-tier venture capital firms, including [Investor Names], with participation from angel investors and industry veterans. The investment will be used to accelerate product development, expand the company’s workforce, and establish key partnerships with logistics providers, government agencies, and financial institutions.

**How Frontera Plans to Use the Funding**

With this fresh injection of capital, Frontera has outlined several key areas of focus:

1. **Technology Development** – The company plans to enhance its AI-driven platform to improve real-time tracking, automate compliance processes, and optimize supply chain efficiency.
2. **Talent Acquisition** – Frontera aims to expand its team by hiring top talent in engineering, logistics, and regulatory compliance to drive innovation and execution.
3. **Market Expansion** – The company will use the funding to enter new markets, particularly in North America and Latin America, where cross-border trade is a critical economic driver.
4. **Strategic Partnerships** – Frontera will collaborate with logistics providers, customs agencies, and financial institutions to create a seamless and integrated trade ecosystem.

**Industry Impact and Future Outlook**

Frontera’s entry into the market comes at a time when global supply chains are facing increased challenges, including regulatory complexities, trade restrictions, and logistical inefficiencies. By leveraging cutting-edge technology, the company aims to address these pain points and provide businesses with a more efficient way to manage cross-border trade.

Industry experts believe that Frontera’s innovative approach could significantly reduce trade barriers and streamline operations for businesses engaged in international commerce. If successful, the company has the potential to become a major player in the global logistics and trade technology sector.

**Conclusion**

The $32 million seed funding secured by Frontera is a testament to the confidence investors have in its vision and potential. As the company moves forward with its ambitious plans, it is poised to make a significant impact on the logistics and trade industry. With a strong leadership team, cutting-edge technology, and a clear market need, Frontera is well-positioned to redefine the future of cross-border trade.

Stay tuned for more updates as Frontera embarks on its journey to transform global commerce.

# Generative AI Enhances Cancer Imaging Technology in Hong Kong

## Introduction

Cancer remains one of the leading causes of death worldwide, and early detection plays a crucial role in improving survival rates. In Hong Kong, where cancer is the top cause of mortality, medical professionals are increasingly turning to advanced technologies to enhance diagnostic accuracy and treatment planning. One of the most promising innovations in this field is **Generative Artificial Intelligence (AI)**, which is revolutionizing cancer imaging technology.

By leveraging generative AI, researchers and healthcare providers in Hong Kong are improving the precision, efficiency, and accessibility of cancer imaging. This article explores how generative AI is transforming cancer imaging, its benefits, challenges, and the future of AI-driven healthcare in Hong Kong.

## The Role of Generative AI in Cancer Imaging

Generative AI refers to artificial intelligence models that can generate new data based on existing patterns. In cancer imaging, these models can enhance medical scans, improve image quality, and even assist in detecting abnormalities that might be missed by human radiologists.

### 1. **Enhancing Image Quality and Resolution**
Medical imaging techniques such as MRI, CT scans, and PET scans often suffer from noise and low resolution, which can make it difficult to detect small tumors. Generative AI models, such as **deep learning-based super-resolution algorithms**, can enhance image clarity, allowing radiologists to identify cancerous tissues more accurately.

### 2. **Automated Tumor Detection and Segmentation**
Generative AI can be trained to recognize patterns in medical images and automatically detect tumors. By using **deep learning models like Generative Adversarial Networks (GANs)**, AI can differentiate between normal and abnormal tissues, reducing the chances of misdiagnosis. This is particularly useful in detecting early-stage cancers, where subtle changes in imaging may be difficult for the human eye to detect.

### 3. **Synthesizing Medical Images for Training and Research**
One of the challenges in developing AI for cancer imaging is the limited availability of high-quality medical datasets. Generative AI can create **synthetic medical images** that closely resemble real patient scans. These synthetic images can be used to train AI models, improving their accuracy without compromising patient privacy.

### 4. **Predicting Disease Progression**
AI models can analyze historical imaging data to predict how a tumor might grow or respond to treatment. This helps oncologists in Hong Kong develop personalized treatment plans and make informed decisions about surgery, chemotherapy, or radiation therapy.

## Benefits of Generative AI in Cancer Imaging

### **1. Improved Diagnostic Accuracy**
Generative AI reduces human error by providing highly detailed and enhanced images, allowing radiologists to make more precise diagnoses. This is particularly beneficial in detecting cancers that are difficult to identify in their early stages, such as lung and pancreatic cancer.

### **2. Faster Diagnosis and Treatment Planning**
AI-powered imaging tools can analyze scans in seconds, significantly reducing the time required for diagnosis. This allows doctors to start treatment earlier, improving patient outcomes.

### **3. Cost-Effective and Scalable Solutions**
By automating image analysis, generative AI reduces the workload of radiologists and minimizes the need for repeated scans. This leads to cost savings for both hospitals and patients, making cancer diagnosis more accessible.

### **4. Enhanced Medical Training and Research**
AI-generated synthetic images provide medical students and researchers with a vast dataset for training and experimentation. This accelerates the development of new diagnostic techniques and treatment strategies.

## Challenges and Ethical Considerations

Despite its potential, the integration of generative AI in cancer imaging comes with challenges:

### **1. Data Privacy and Security**
Medical imaging involves sensitive patient data. Ensuring that AI models comply with **Hong Kong’s Personal Data (Privacy) Ordinance (PDPO)** and other international regulations is crucial to maintaining patient confidentiality.

### **2. AI Bias and Reliability**
AI models are only as good as the data they are trained on. If training datasets lack diversity, AI may produce biased results, leading to disparities in diagnosis and treatment. Continuous monitoring and validation of AI models are necessary to ensure fairness and accuracy.

### **3. Integration with Existing Healthcare Systems**
Implementing AI-driven imaging solutions requires significant investment in infrastructure and training for medical professionals. Hospitals and clinics in Hong Kong must ensure seamless integration with existing medical workflows.

### **4. Ethical Concerns in AI-Generated Data**
The use of synthetic medical images raises ethical questions about data authenticity and potential misuse. Clear guidelines must be established to regulate the use of AI-generated medical data.

## The Future of AI-Driven Cancer Imaging in Hong Kong

Hong Kong is rapidly embracing AI-driven healthcare solutions, with institutions such as **The Chinese University of Hong Kong (CUHK) and The University of Hong Kong (HKU)** leading research in AI applications for medical imaging. Government