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Good morning! 

Welcome to Healthcare AI News, your weekly dose of the latest developments and headlines in the world of healthcare AI.

It’s been another big week for Healthcare AI, and we’re exploring the benefits of Federated Learning AI modules in Healthcare. We also look at the value of Dark Data for customer insights, Amazon is now a healthcare provider, and Mark Cuban's Cost Plus Drug Company’s new collaboration. 

Be sure to read on to see this week's Top headlines, Industry, Tech, and M&A news. 

Let's dive in.

HEADLINE ROUNDUP

• Brain implant startup backed by Bezos and Gates is testing mind-controlled computing on humans (Read more)

• This bra tracks your vital signs (Read more)

• Apple is reportedly closer to bringing no-prick glucose monitoring to the Watch (Read more)

• How AI and machine learning (ML) help prevent sports injuries. (Read more)

• ChatGPT creator Sam Altman thinks we are not far from 'potentially scary' AI. (Read more)

• Severance packages big tech is paying out (Read more)

• A Candid Chat with Microsoft’s National Director for AI in Health. (Read more)

• AI in the workplace is already here. The first battleground? Call centers. (Read more)

• Machine learning approach to predict cardiac surgery-associated acute kidney injury. (Read more)

• Microsoft to demo its new ChatGPT-like AI in Word, PowerPoint, and Outlook soon. (Read more)

• What is the best hospital in the US? ChatGPT's response. (Read more)

💡 Keep reading to catchup on Industry, Tech & Deal flow

THE FEATURE

Why Federated Learning AI Modules are Critical for Advancing AI Healthcare

Balancing the need for better healthcare and protecting our privacy can be tricky. However, there’s a revolutionary solution: Federated Learning. This innovative data-sharing approach allows individuals to share their data to build predictive models while retaining control over their data usage.

Imagine being able to conduct tests in a laboratory without ever having to surrender control of your personal data. This is where federated learning comes in. Federated learning is a privacy-preserving technique that enables data to remain with individuals while contributing to the development of predictive models that benefit the entire community.

🧐 Understanding Federated Learning

In traditional machine learning, data is collected and stored on a central server, but with federated learning, the data remains on the device, and the algorithm is sent to the device for training. This approach enables privacy and security while allowing the algorithm to learn from a larger and more diverse dataset.

In healthcare, federated learning can help identify high-risk individuals, reduce bias in machine learning models, ensure compliance with data protection regulations such as HIPAA and GDPR, and reduce data storage and management costs. 

📈 Innovations in AI Healthcare with Federated Learning

Owkin analyzes health data from US and European hospitals using federated learning to develop new drugs. Bristol Myers Squibb invested $80M in the project. Owkin collaborated with researchers from four hospitals to improve breast cancer treatment using a model trained on data from 650 patients. The model predicts a patient's response to treatment and suggests alternatives.

Rhino Health provides a collaborative platform for healthcare innovators that allows data sharing without moving it. The platform has helped predict respiratory illness outcomes, diagnose brain conditions, detect cancer, and improve rare disease diagnosis in pediatrics. The company raised $11.7M in seed financing, showing a growing interest in the technology.

Healthcare key players in Federated Learning

• Lifebit | Sherpa | Apheris | Datafleets

Tech Leaders in Federated Learning

• Nvidia | Google | Microsoft | IBM | Cloudera

💊 Use Cases for Federated Learning in Health Insurance

• Fraud Detection: Federated learning detects fraud by analyzing data from multiple insurance providers without compromising sensitive information. This reduces costs associated with fraud for insurance companies.

• Personalized Healthcare: Federated learning analyzes data from multiple sources to build better predictive models for personalized healthcare, enabling health insurance companies to identify at-risk patients and provide personalized care plans.

• Clinical Trials: Federated learning improves clinical trial accuracy by analyzing data from multiple sources, helping health insurance companies identify eligible patients and provide better care.

⏳The Way Forward

As we move into the future, federated learning will undoubtedly continue to revolutionize the healthcare industry, allowing for better patient care and more efficient use of data. 

Leaders in the healthcare sector must take action and start considering how to incorporate this technology into their offerings. The benefits of federated learning, including tailored insurance plans, improved diagnostic accuracy, and reduced healthcare costs, cannot be ignored. 

Implementing federated learning will require significant investment in infrastructure and talent, but the potential benefits are well worth it. The future of AI in healthcare is bright, and federated learning AI modules are the key to unlocking its full potential.

INDUSTRY NEWS

• The top 25 women leaders in medical devices of 2023. (Read more)

• Researchers demand regulatory pathways for AI-driven software in healthcare (Read more)

• VA awards millions to veteran suicide tech challenge winners. (Read more)

• Zoom is helping Maine General Health boost its telehealth success. (Read more)

• A way to govern ethical use of artificial intelligence without hindering advancement. (Read more) 

• The crucial role of predictive analytics in precision medicine. (Read more)

• Can healthcare data lessen disease burden for aging Americans? (Read more)

• AI in healthcare: over 100 engineers & 40 years of data. How India’s largest hospital chain made ChatGPT-like tool for doctors. (Read more)

TECH NEWS

• How voice biomarker AI can transform early disease diagnoses. (Read more)

• The value of dark data for customer insights in the healthcare industry. (Read more)

• Open AI Blog: How should AI systems behave, and who should decide? (Read more)

• How healthcare firms leverage AI, machine learning (ML), and cloud for sustainability. (Read more)

• Understanding the Healthcare Cybersecurity War and How to Defend Against It (Read more)

• Amazon’s Cloud Unit Partners With Startup Hugging Face as AI Deals Heat Up (Read more)

• Why are Voice Fraud Threats a Danger to Your Enterprise? (Read more)

• Apexon partners with LambdaTest on digital experience testing (Read more)

DEAL FLOW

• $5.4 Billion United Health Group and LHC deal Closes (Read more)

• Amazon closes $3.9B buyout of health company One Medical (Read more)

• Diathrive Health and Mark Cuban Cost Plus Drug Company announce new collaboration. (Read more)

• Vytalize grabs $100M as value-based healthcare model thrives (Read more)

• UHS Announces New $61M JV; Summa Health Opens $84M Behavioral Health Facility (Read more)

• Aledade acquires value-based care analytics platform Curia (Read more)

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TOP 3 TWEETS OF THE WEEK