📈 AI Boosts Cancer Detection, 🏥 Microsoft's Radiology Partnership, 🤖 Insilico's Research Tool, & More – Discover the Latest in Med AI! 🚀
Updates on Artificial Intelligence & Emerging Technologies in Medicine 🤖💊
“Artificial Intelligence and machine-learning is not something to be feared but to be embraced. AI can help to sort through data in a split second instead of taking hundreds of hours for you or me to do it. It’s designed to work with our teams to help them be more efficient and creative.” - Mika Yamamoto, Chief Customer and Marketing Officer at Freshworks
Dear Med AI Enthusiast,
Welcome to The ‘Med AI’ Capsule newsletter! Here’s your inside look at how AI and emerging technologies are transforming medicine. ⚕
Whether you're a medical professional 👩⚕️, a tech enthusiast 💻, or simply curious 🧠, The 'Med AI' Capsule is for you!
Stay informed 📰 about the latest updates and insights into the world 🌍 of AI and emerging technologies in medicine.
Let the adventure begin! I’m thrilled to have you with me. 🚀
In today’s capsule:
5 News Updates
4 Latest Research Papers
3 Industry Innovators
2 Upcoming Events
1 Knowledge Resource
Reading Time: 7-10 minutes
News Updates 📰
1. 📈 AI Tool 'C the Signs' Boosts Cancer Detection Rates in English GP Practices
Artificial intelligence program "C the Signs" has increased cancer detection rates in England, boosting from 58.7% to 66.0%. The AI tool, which scans GP records to find hidden patterns, helped boost detection rates in practices using the technology.
Why Important: Enhancing early cancer detection, this AI tool supports the NHS goal to diagnose 75% of cancers by stage one or two by 2028.
“Despite increased demand and pressure on services, record numbers of people are being checked and treated for cancer, and we are now diagnosing a higher proportion of cancers at an early stage, increasing people’s chances of survival.” - Prof Peter Johnson, National Clinical Director for Cancer at NHS England
Caution: Experts warn of overstating AI’s potential; ongoing evaluation and integration with other diagnostics are crucial.
2. 🤝 Microsoft Partners with Mass General Brigham and UW Health to Advance AI in Radiology
Microsoft is collaborating with Mass General Brigham, UW School of Medicine and Public Health, and UW Health to develop AI models for radiology using Azure and Nuance.
Why Important: This partnership aims to enhance radiologists' ability to interpret medical images, generate reports, and classify diseases, improving clinical workflows and patient care.
"Foundation models fine-tuned on Mass General Brigham's vast multimodal longitudinal data assets can enable a shorter development cycle of AI/ML-based software as a medical device and other clinical applications, for example, to automate the segmentation of organs and abnormalities in medical imaging and increase radiologists' efficiency and consistency." - Dr. Keith J. Dreyer, chief data science officer and chief imaging officer at Mass General Brigham and leader of the Mass General Brigham AI business
Caution: Ensuring high-quality care requires careful and responsible development and evaluation of these AI tools to prevent compromising standards.
3. 📝 Insilico Medicine Launches AI Assistant for Medical Research Papers
Insilico Medicine has introduced DORA, an AI assistant to help draft academic papers, case studies, and grant applications, with a free trial available later this year.
Why Important: DORA aims to support early-career researchers and non-native English speakers, enabling them to contribute more effectively to medical research.
“The reason why we’re doing this is to help enable people who, potentially, may not have exactly the same level of research capabilities or support as people in top-tier institutions.” - Alex Zhavoronkov, Insilico founder and CEO
Caution: Ensuring accuracy and avoiding AI hallucinations requires multiple rounds of generation and human proofreading, prioritizing precision over speed.
4. 🩻 Saudi AI Model MiniGPT-Med to Advance Radiology Diagnosis
King Abdullah University of Science and Technology (KAUST) and the Saudi Data and Artificial Intelligence Authority (SDAIA) have released MiniGPT-Med, a vision-interfaced AI model for radiology.
Why Important: MiniGPT-Med significantly improves the accuracy and efficiency of diagnosing 14 diseases across various imaging modalities, supporting overloaded radiologists and potentially saving lives in emergencies.
Caution: AI in radiology faces challenges like the need for extensive training data, standardization issues, and potential misinterpretations, necessitating ongoing research and development.
5. 🎗️ Qatar Adopts AI-Driven Solution for Breast Cancer Screening Program
Qatar's Primary Health Care Corporation (PHCC) has partnered with Lunit to integrate an AI solution into the national breast screening initiative.
Why Important: The Lunit INSIGHT MMG solution aims to enhance early detection of breast cancer, reducing missed diagnoses and improving survival rates in a country where breast cancer accounts for 32% of all female cancer cases.
Caution: As the first in the Middle East to implement AI across its screening program, it is a must to ensure the technology's accuracy and reliability to maintain high-quality healthcare standards.
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Latest Research Papers 🔬
Autonomous artificial intelligence for diabetic eye disease increases access and health equity in underserved populations | npj Digital Medicine (nature.com) - results from real-world deployment in a large integrated healthcare system suggest that autonomous AI is associated with improvement in overall DED testing adherence, patient access, and health equity.
Can Large Language Models Provide Useful Feedback on Research Papers? A Large-Scale Empirical Analysis | NEJM AI - large language models provide useful feedback on research papers, showing substantial overlap with human reviewers and positive user perceptions, enhancing early manuscript preparation.
Second opinion machine learning for fast-track pathway assignment in hip and knee replacement surgery: the use of patient-reported outcome measures - PMC (nih.gov) - ML models using patient-reported outcome measures effectively support fast-track pathway assignment in hip and knee replacement surgery, improving decision-making and patient outcomes.
The First Generative AI Prompt-A-Thon in Healthcare: A Novel Approach to Workforce Engagement with a Private Instance of ChatGPT - PMC (nih.gov) - successfully engaged healthcare professionals in exploring and responsibly using Generative AI, enhancing their confidence and collaborative innovation.
Industry Innovators 👨🏭
Belong.life - a patient-centric platform leveraging AI, data, and communities to enhance patient engagement and healthcare outcomes. It offers specialized networks for cancer and multiple sclerosis patients, the AI-powered Cancer Mentor app "Dave", and solutions for clinical trial matching and treatment management, all aimed at improving patient education, support, and healthcare experience.
Biodesix - specializes in lung disease diagnostics, utilizing advanced AI and machine learning to develop blood-based tests for better patient outcomes. Their diagnostic solutions focus on personalized medicine, helping to guide treatment decisions and improve healthcare for patients with lung cancer and other lung diseases.
Bluesight - provides supply chain visibility solutions for healthcare, focusing on medication tracking and inventory management to ensure patient safety and operational efficiency. Their platform leverages advanced analytics to reduce drug shortages, manage expired medications, and optimize pharmacy operations.
Upcoming Events 🧑💻
Stay tuned for more updates and details on how to register! 🚀
Knowledge Resource 📚
How to use Generative AI and Prompt Engineering for Clinicians - BMJ Future Health
Generative AI, including tools like ChatGPT, has significant potential in healthcare for tasks like summarizing patient records, generating treatment plans, and translating medical terminology.
Dr. Keith Grimes, a GP and digital health consultant, in this webinar, explains how large language models work, their strengths and weaknesses, and offers practical advice on using generative AI safely in clinical practice. Key points include understanding AI limitations, using prompt engineering techniques, and integrating AI to augment rather than replace clinical judgment.
📢 Important Announcement
Moving forward, this newsletter will no longer be following a fixed schedule. Instead, updates will be shared in a more flexible manner, whenever there are exciting developments. Thank you for your understanding and continued support!
Let’s wrap it up with a poll! 📊
Your feedback is crucial to me, as it helps me understand your interests and improve my offerings. I would appreciate it if you could take a few minutes to share your thoughts about what you've enjoyed and what you think I could do better.
Stay tuned for our upcoming editions as we explore the latest breakthroughs and dive deep into the transformative power of artificial intelligence and emerging technologies, shaping a healthier future. 🚀
Warm regards,
Disclaimer: The content in this newsletter was partly curated and summarised using AI LLMs, which can make mistakes. Please check all important information. For any issues or inaccuracies, please notify me on avneeshkhareonline@gmail.com.