Vindhyaa Saravanan’s Post

🚨 𝐄𝐱𝐜𝐢𝐭𝐢𝐧𝐠 𝐧𝐞𝐰𝐬! 🚨 I'm thrilled to share that my article titled "𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐀𝐩𝐩𝐫𝐨𝐚𝐜𝐡𝐞𝐬 𝐟𝐨𝐫 𝐄𝐚𝐫𝐥𝐲 𝐀𝐥𝐳𝐡𝐞𝐢𝐦𝐞𝐫’𝐬 𝐃𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐏𝐚𝐭𝐢𝐞𝐧𝐭𝐬 𝐰𝐢𝐭𝐡 𝐒𝐮𝐛𝐣𝐞𝐜𝐭𝐢𝐯𝐞 𝐂𝐨𝐠𝐧𝐢𝐭𝐢𝐯𝐞 𝐃𝐞𝐜𝐥𝐢𝐧𝐞: 𝐀 𝐒𝐲𝐬𝐭𝐞𝐦𝐚𝐭𝐢𝐜 𝐋𝐢𝐭𝐞𝐫𝐚𝐭𝐮𝐫𝐞 𝐑𝐞𝐯𝐢𝐞𝐰" has been 𝐚𝐜𝐜𝐞𝐩𝐭𝐞𝐝 for presentation at the 𝐈𝐧𝐭𝐞𝐫𝐧𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐂𝐨𝐧𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐨𝐧 𝐀𝐠𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝟐𝟎𝟐𝟓! 🎉🎉 In this work, I explore how Machine learning and Deep Learning methods can revolutionize Alzheimer’s disease detection at a preclinical stage, precisely for individuals with Subjective Cognitive Decline, potentially offering new avenues for timely intervention. By analyzing various ML and DL models, data types, and preprocessing techniques, our work highlights the potential of AI in providing early detection methods that could radically improve patient outcomes and offer more cost-effective solutions for healthcare systems. I’m incredibly proud to share this milestone and extend my heartfelt thanks to Nourhène Ben Rabah and Bénédicte Le Grand for their invaluable contributions and support throughout this research journey.🙏 I'm excited to share our findings at ICAART 2025 and look forward to the discussions it will spark as we continue to push the boundaries of AI in healthcare. #AI #MachineLearning #DeepLearning #Alzheimers #HealthcareInnovation #SCD #ResearchPaper #ICAART2025 #ICAART #AlzheimerDetection #ArtificialIntelligence #AIConferences

🌟 Transforming Infant Healthcare with AI ? 🌟 At Chelonia Applied Science, we are continuously exploring the frontiers of healthcare innovation. A recent review in #Frontiers in Digital Health underscores a critical area of our interest—applying AI learning to revolutionize infant disease detection and prediction. 👶 Why It Matters: Early diagnosis in infants can change lives. AI’s capability to analyze vast datasets from clinical and demographic information offers unprecedented precision in detecting conditions during the most vulnerable first year of life. 🔬 Research Insights: Between 2018 and 2022, studies leveraging AI for infant healthcare have shown promising growth. Techniques like deep neural networks have become increasingly popular, although traditional methods still hold significant value, particularly in data-constrained environments. 💡 Chelonia’s Vision: We believe in harnessing the power of AI to not only advance infant health but also to accelerate drug discovery processes. Our commitment is to integrate these technologies to develop solutions that are not just innovative but also ethical and sustainable. 🤖 Looking Ahead: The continuous advancements in AI provide a robust foundation for developing tools that could soon be standard in clinical settings, enhancing diagnostic procedures and ensuring better outcomes for our youngest patients. 👉 Follow us on LinkedIn and X 📫 Register to our newsletter (issued no more than 5 times per year) https://lnkd.in/e8JxcBdF Join us as we continue to push the boundaries of what's possible in healthcare and drug discovery. The future is here, and it’s digital! #CheloniaSwiss #HealthcareInnovation #AIinHealthcare #DigitalHealth #DrugDiscovery #InfantHealth #MachineLearning

🌿 2024 Reflection: Reimagining Healthcare Through Nature’s Wisdom and AI’s Purpose. I’ve been reflecting on how healthcare can evolve from AI mimicking nature to transform how we work and live. And while these are optimistic views, it helps me to project a future we want to manifest and live in and perhaps you might feel the same. ✨ Purpose in Practice: Purpose will become the currency of work, empowering us to reconnect with why we do what we do. With AI taking over repetitive tasks, providers can focus on what matters most—connecting with patients and building trust, prioritizing empathy and creativity. 🌱 Decentralized Resilience: Nature thrives through decentralized, adaptive ecosystems. Similarly, healthcare must move beyond centralized models to create local, tailored solutions—AI-powered telehealth, mobile clinics, and community-based care hubs that adapt to meet diverse needs. 💡 Data as Collective Power and new Income Streams: Just as ecosystems share resources, we can harness anonymized health data to drive population health research. Imagine a future where contributing to research not only advances science but creates income for individuals, turning data into a shared resource for good. This shift empowers people to take ownership of their health data and participate in building healthier societies. 🤖 AI as a Wellness Partner: This year I’ve done the most work bringing clarity on the role of AI in prevention. Personal AI health coaches could guide us toward healthier lives, shifting the focus from treating illness to nurturing wellbeing, by activating our agency. Looking ahead, we have an almost impossible task of redesigning healthcare systems that are inspired by nature’s wisdom—adaptive, inclusive, and purpose-driven. But it has given me purpose. How do you envision the future of healthcare? Let’s shape it together. 🌟 Yes, I used the help of ChatGPT to structure my thinking into a post format. #YearEndReflection #AIInHealthcare #Biomimicry #PurposeDrivenInnovation #PreventativeCare #DecentralizedHealth https://lnkd.in/e-rM42zR

🌟 Dive into the Future of Medicine with AI! 🌟 Ever wondered how artificial intelligence is transforming the world of healthcare? 🏥 The latest article from Prompt Dynasty explores the incredible ways AI is revolutionizing medical research, disease detection, and treatment plans. From smarter medical imaging to personalized cancer treatments, and even AI-powered mental health support, the future is here! 🚀 Key Highlights: 🔬 AI aiding doctors and scientists with data analysis and predictions. 📸 Advanced medical imaging for early disease detection. 🎗️ Personalized treatment plans for breast cancer. 💬 AI chatbots providing instant health information and mental health support. ⚖️ Ethical considerations in AI development. 🌐 Exciting future prospects with ongoing research. Read the full article now and join the conversation! How do you see AI impacting healthcare? 🤖💉 👉 [Explore the Full Article](https://lnkd.in/g-CMbWtk) Don’t forget to like, comment, and share if you found it fascinating! 🙌 #HealthTech #ArtificialIntelligence #MedicalInnovation #AIFuture #HealthcareRevolutionhttps://lnkd.in/g-CMbWtk

Excited to share our recent work on #GenerativeAI in healthcare imaging! 🎉🧠 We've leveraged the power of #DiffusionModels to explore disparities in large imaging datasets, specifically focusing on pelvic X-rays. Our approach offers a novel way to uncover subtle patterns and potential biases without manually reviewing hundreds of thousands of images. Key highlights: • Trained a model on ~500K pelvic X-rays, conditioning it on demographic info • Created #counterfactual videos to visualize transitions between demographic groups • Observed differences in interacetabular distance, osteoarthritis severity, and other features • Notably, found a higher degree of osteoarthritis in Black patients, pointing to potential disparities in care access and timing. This research has significant implications for #HealthEquity and the development of AI in healthcare. It demonstrates how we can leverage advanced AI techniques to identify and address potential biases in medical datasets and ultimately improve patient care for all demographics. Curious to learn more? Check out our full article for an in-depth look at our methodology, findings, and the broader implications for #GenerativeAI in healthcare: https://lnkd.in/gvYXa3uF A huge thanks to my incredible team and collaborators: Pouria Rouzrokh, MD, MPH, MHPE, Bradley Erickson, Dr. Hillary Garner, Dr. Doris Wenger, Michael Taunton, and Cody Wyles. What are your thoughts on using generative AI to address healthcare disparities? #ArtificialIntelligence #HealthcareAI #MedicalImaging PS Listen to an excerpt of the paper generated with #NotebookLM.👇

📰 News: 📰 🚀 --AI Outperforms Humans in Heart Health! New Study Findings-- Hey everyone! Got some groundbreaking news that blends tech with life-saving potential. A recent study, the DRAI MARTINI study, presented at the ESC Congress 2024, reveals some jaw-dropping stats on how AI is leading the way in heart rhythm disorder detection. Spoiler alert: the AI algorithm outperforms human specialists by a long shot! Here are the key takeaways: - The novel AI algorithm, DeepRhythmAI -DRAI-, developed by Medicalgorithmics, has a stunning --98.6% sensitivity-- in detecting critical arrhythmias, compared to --80.3% by human technicians--. - The study involved over --14,600 patients-- who were monitored for an average of --14 days--. Talk about thorough! - Human technicians missed diagnoses --14 times more often-- than when using the AI. Yikes! This research emphasizes the incredible potential of AI in improving the accuracy of medical diagnostics, which could be a game-changer in cardiac care. Ready to dive deeper? Let’s chat! Share your thoughts and experiences about AI in healthcare—how do you think it will reshape the future? Don't forget to follow the Bernier Group for more exciting updates and insights. 👇 #AIDriven #Digital #AI #Data #SMB #SME #Strategy #Innovation #Business #ArtificialIntelligence #AnniQ https://lnkd.in/edq5y42a

🚀 Exciting breakthrough in healthcare AI! Researchers have developed Delphi-2M, a groundbreaking AI model based on the GPT architecture, which can predict the progression of over 1,000 diseases using data from 400,000 UK Biobank participants. This model not only forecasts individual health trajectories but also offers insights into disease clusters and their impacts over time. 📊 Validated against 1.9 million Danish health records, Delphi-2M has shown remarkable accuracy in modeling population health, predicting future health outcomes, and matching observed age and sex trends. Its predictions for diseases like septicemia show significant variability among individuals, with AUCs averaging 0.8—comparable to top risk models. 🔍 Delphi-2M utilizes past health records, demographics, and lifestyle factors to generate detailed future health scenarios. It dynamically updates predictions with new data, providing a robust tool for personalized healthcare planning. 💡 Its generative capabilities enable Delphi-2M to create synthetic health trajectories that help train new models while preserving data privacy. This AI model surpasses basic age-sex models in predicting long-term disease burdens and effectively differentiates between high- and low-risk groups over two decades. 🧬 Looking ahead, Delphi-2M's flexible architecture could integrate additional data types like genomics and wearable technology, enhancing its utility in personalized medicine and complex disease interaction analysis. 🌍 As we continue to navigate the complexities of healthcare, Delphi-2M represents a significant step forward in our ability to predict and manage health outcomes at both individual and population levels. #HealthcareInnovation #ArtificialIntelligence #PersonalizedMedicine #DigitalHealth #AIinHealthcare

The Unseen Bias in Healthcare AI 🤔 Coming from a family in the healthcare sector that always loved technology, I’ve seen firsthand how tech can transform patient care—but only if the physician knows how to use it. The same holds for AI today. ➕ AI is amazing -> It is helping clinicians diagnose breast cancer, read X-rays, and predict which patients need more care. The Nobel Prize in Chemistry, announced today, recognized the work of three researchers: David Baker, Demis Hassabis, and John M. Jumper. They used AI to study and create new proteins. Demis, one of the three, was one of the founders of the company Google DeepMind, which focuses on the use of artificial intelligence in healthcare, studying DNA, new molecules, and more. ⚠️ However, AI risks perpetuating racial biases if trained on historical, inequitable data. An algorithm predicting healthcare needs based on spending patterns was found to recommend less care for Black patients due to historically lower healthcare spending. https://lnkd.in/eeRvFk95 🚨 Early warning signs of heart disease might be missed in female patients because the data used to train these models often skews toward male patterns. Diverse data, transparency, and ongoing monitoring are critical to ensure AI helps all patients fairly and responsibly, as Yale School of Medicine points out. https://lnkd.in/ev7zieXq What other challenges do you see for AI in this or other industries? 💬👇 #HealthcareAI #BiasInTech #DataEthics #InclusiveHealthcare #AIinMedicine #HealthInnovation #ResponsibleAI #TechForGood #HealthcareInnovation #MachineLearning #ProductManagement #Mccombs #UT #Fuqua #Duke

🚀 Throwback to the day we presented our final project: "AI in Healthcare"! I’m incredibly proud to have worked on this project alongside my amazing teammates, Mouhsin Tanani and Yassine Moutaoikkil Basskar. With guidance from our supervisor, Mme Ilham Mounir, and tutor, Zakariae LAALIJI, we focused on developing three impactful AI models: 1. Lab Test Interpretation – An AI model that reads and provides results for laboratory tests. 2. Heart Failure Prediction – A model designed to predict heart failure risk. 3. Brain Stroke Prediction – A model that helps predict brain stroke occurrences. We combined these models into a user-friendly mobile application, making it accessible and simplified for users to explore and benefit from. This project allowed me to enhance my technical skills across multiple technologies, while also sharpening my teamwork abilities. I’m grateful to my teammates for their trust and dedication, and I’d also like to thank everyone who contributed to this project in any way, big or small. Onwards and upwards! 🚀 #AI #Healthcare #TechInnovation #Teamwork #Gratitude #FinalProject