Clinical trials are the engine of medical innovation, but traditional methods can’t keep up with modern research. In part 3 of our AWS Health Innovation Podcast compilation, hear from Deep 6 AI, Lokavant, and Science 37 as they revolutionize trial operations. 📌 Deep 6 AI: Uses AI and NLP to match patients to trials via EMRs. 📌 Lokavant: Offers analytics for site/safety monitoring and enrollment forecasting. 📌 Science 37: Provides trial access to diverse populations through a virtual model. 🔉 https://go.aws/3xsoqw1 #HealthInnovation #BioTech #Startups
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Helping healthcare startups de-risk and grow | Healthcare Innovator | Ex Philips VP | Public speaker
What works here might not work there - The realities of Healthcare AI I recently met and spoke to several founders of Healthcare AI startups. All of them talked about the difficulties in scaling to many customers due to the differences they encounter in datasets. Sharing this article where I tried to summarize the most common biases you should be aware of and provide a few other tips. The 10 types of dataset biases are grouped into: 🌎 Population & Cohort related ⚕️ Medical practice related 🏷 Labeling & Curation related Key tips: 🔹 Be aware of the biases and evaluate your risk 🔹 Avoid black box AI for robustness & explainability 🔹 Involve clinicians in the process 🔹 Prepare for ongoing monitoring and improvement ♻ If you found this helpful, please share or repost.
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Professional Mentor and Consultant. CEO. Leadership / Strategy / Healthcare/ SW/ Operations and Service - Enabling companies meeting their vision
Facinating era in which AI challenge will drive to standardisation in medical practice.
Helping healthcare startups de-risk and grow | Healthcare Innovator | Ex Philips VP | Public speaker
What works here might not work there - The realities of Healthcare AI I recently met and spoke to several founders of Healthcare AI startups. All of them talked about the difficulties in scaling to many customers due to the differences they encounter in datasets. Sharing this article where I tried to summarize the most common biases you should be aware of and provide a few other tips. The 10 types of dataset biases are grouped into: 🌎 Population & Cohort related ⚕️ Medical practice related 🏷 Labeling & Curation related Key tips: 🔹 Be aware of the biases and evaluate your risk 🔹 Avoid black box AI for robustness & explainability 🔹 Involve clinicians in the process 🔹 Prepare for ongoing monitoring and improvement ♻ If you found this helpful, please share or repost.
What works here might not work there - dealing with AI and diversity in Healthcare data
focusonvalue.biz
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AI Product Management | Gen AI | AI for Medical Imaging | Computer Vision | Med Tech | Regulatory | Global Product Lead | Department Manager |
📚 Highly Recommend Reading: "Deep Medicine" by Eric Topol 🚀Nice company on a long bus-ride. Back in 2019, as I was embarking on my journey into product management for AI in healthcare, I first picked up "Deep Medicine”by Eric Topol. This book was years ahead of its time! It focused on how AI could transform healthcare by giving time bck for enhancing the crucial connection between caregivers and patients. 🌐 Now, in 2024, with the rapid developments in generative AI, like GPT-4o, Med-Gemini, aninflux of solutions for ambient reporting, AI for improved diagnostics, revisiting this book has been incredibly insightful and fills me with new ideas🤖💡 Whether you're involved in healthcare or intrigued by the impact of AI, "Deep Medicine" is a must-read. I’m also looking forward to sharing more thoughts in an upcoming blog post! 📝 #AIinHealthcare #DeepMedicine #EricTopol #BookRecommendation #GenAI
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It’s all about Start-ups! AllAboutAI prefers to work together and build a tailor-made data science & AI concept together. The core team sees the value of AI in collaborating with and bringing together AI providers and companies with AI questions. We have welcomed Oxaigen to our network and they are a health-tech start-up that uses AI to increase resilience and reduce strain in the healthcare sector. They do this by building a data-first infrastructure for hospitals and developing clinical decision support systems that utilize machine learning algorithms for real-time patient recommendations, with an emphasis on intensive care medicine and Reinforcement Learning. Read more about Oxaigen on https://lnkd.in/eWXXKN6b and join our network now! #allaboutai #artificialintelligence
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Holiday season didn't slow down the passion and excitement for Generative AI for life science. The most common question we received from hundreds of life science professionals regarding #GenerativeAI was, "How are other companies using #GenerativeAI?" 😂 You asked, we listened. That's why we hosted a webinar with tech giant Google that explored almost all the use cases of Generative AI across the widest spectrum, from biopharma, Medtech, hospitals to providers, patients, and insurers. The content was so valuable that we will expand the early observation of Generative AI by a couple of posts. First things first, why is Generative AI in healthcare so exciting? In short, for the first time in human history, we can retrieve, summarize, and synthesize large amounts of data that previously would have taken days, weeks, months, or even years. The superpower of surfacing insights in seconds will transform almost every aspect of the healthcare industry. It is such an exciting time! What is your Generative AI strategy? Let's brainstorm together! #google #nyquistai #generativeai #healthcare #innovation #clinicaltrials #regulatoryaffairs
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Talent Acquisition || Technology Hiring|| Strategic Sourcing|| Stakeholder Management|| End to End recruiting KPI || Matching Professionals with opportunity
As research and development leaders embrace the opportunities of automation, they also contend with its challenges. In the latest report, Biopharma Dive speaks with Baba Shetty, President of Technology and Data Solutions and Terttu Haring, President of Clinical Sites and Patients at #SyneosHealth, to better understand current perspectives surrounding artificial intelligence (AI) and machine learning (ML) in clinical trials. Explore disruptive and incremental use cases, outstanding challenges and how sponsors are balancing the knowns and unknowns of a rapidly advancing tech landscape: https://lnkd.in/d8eZPb9h #SyneosHealthLife #WorkHereMattersEverywhere #ClinicalCareers #SyneosHealth #ClinicalSolutions #2023healthtrends #techology #techcareers #artificialintelligence #machinelearning
Artificial Intelligence, Machine Learning and a New Epoch for Clinical Trials
syneoshealth.com
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Two weeks ago I had a chance to be part of a panel discussion at REinvent Ventures in SF about AI in Healthcare and Bioengineering. It was a fascinating mix of research-oriented speakers, talking about how AI will help us open up new frontiers in understanding biology and the human body, and people like myself in healthcare, using AI to help us make practical use of the biology we already understand. There were a lot of great conversations around our 5-Level Framework for AI Automation in Healthcare, which makes it easier to "right size" the roll-out and evaluation of AI in healthcare, maximizing speed and impact while remaining safe and responsible. Because we tend to put all "Healthcare AI" into the same bucket, societies tend to over-regulate lower-risk healthcare AI systems, while under-regulating higher-risk systems. Over the next 2-4 years, nearly all the scaled Healthcare AI interventions will be Level 1 (Back-Office) and Level 2 (Clinical Process improvement). Our learnings here, about how to get nondeterministic algorithms to process medical language with high reliability, will pave the way for a following wave of Clinical Decision Support innovations. https://lnkd.in/eHv85s8V Peter Leyden Joe Boggio Mickey McManus Tom Kalil Freedom Preetham
Zayed Yasin on “How Can AI Accelerate Progress in the Bio World?”
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Partnering with healthcare executives to cut CX costs 90% & grow revenue 50% with Generative AI | Co-founder | Forbes Lister
🎉 📢 Publically releasing our recent emphatically attended Webinar on Achieving Early Impact with Gen AI in Healthcare with Microsoft 🚀 📢 Looking forward to bringing Gen AI solutions to every healthcare institution.. This will allow us to achieve the ultimate mission of eliminating wait times in healthcare globally. Join our journey! #genai #healthtech #ai #startup #voiceai
Achieving Early Impact from Gen AI in Healthcare: KeyReply x Microsoft Webinar
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