🕵🏼 Jan Zachnik’s Post

Generative AI offers immense potential to transform clinical trials in several ways – from patient matching to technical writing – and accelerate the pace of overall drug discovery. This article delves deep into the multifaceted applications of generative AI in the field of clinical trials. #ai #generativeai #llm #aiinhealthcare #aimedicine

Deep Learning Framework Predicts Drug Effectiveness and Treatment Outcomes - DistilINFO Hospital IT Summary: #DeepLearningFramework: A new blog post discusses how a deep learning framework is being used to predict drug effectiveness and treatment outcomes in healthcare. #Introduction: The blog post introduces the concept of using deep learning technology in healthcare to improve patient outcomes and optimize treatment plans. #Challenges in Drug Effectiveness Prediction: The challenges in predicting drug effectiveness are outlined, including the complexity of patient data and the need for accurate predictions. #Benefits of Deep Learning Framework: The blog post highlights the benefits of using a deep learning framework, such as improved accuracy in predicting drug effectiveness and personalized treatment plans. #Case Studies: Several case studies are presented to demonstrate the effectiveness of the deep learning framework in predicting drug outcomes and treatment effectiveness. #Future Applications: ai.mediformatica.com #model #this #medical #learning #clinical #outcomes #clinicaltrials #deeplearning #hospital #stroke #advanced #applications #digitalhealth #healthit #healthtech #healthcaretechnology @MediFormatica (https://buff.ly/4bkr71o)

Sharing some thoughts on #AI in #ClinicalTrials - here’s my latest article on 𝐅𝐚𝐬𝐭 𝐂𝐨𝐦𝐩𝐚𝐧𝐲 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐯𝐞 𝐁𝐨𝐚𝐫𝐝 - Will look forward to your comments below 👇...... Thank you Fast Company Executive Board...🙏🙏 #AI, #Diversity, #InclusiveTrials, #HybridTrials, #DCT, #Telemedicine, #Datascience

Join us for a webinar brought to you by Syneos Health on Monday, 5th February at 9am CST, 3pm GMT, 4pm CET as panellists Robert Zambon and Terttu Haring unpack what’s new in the industry, exploring current perspectives surrounding #AI and ML in #clinicaltrials, disruptive and incremental use cases, outstanding challenges, and how sponsors can navigate a rapidly advancing #technology landscape. https://lnkd.in/eVFcrKam

A study by Mass General Brigham revealed that generative AI, specifically a system based on OpenAI's GPT-4 model named RECTIFIER, outperformed human researchers in screening patients for clinical trials. Achieving a 97.9% accuracy in identifying symptomatic heart failure—significantly higher than the 91.7% by study staff—RECTIFIER also cuts costs to mere cents per patient. But there are still concerns. Read what the researchers are worried about: https://lnkd.in/gUb8hncN #HealthcareInnovation #ClinicalTrials #GenerativeAI #HealthTech #AIinHealthcare

We recently asked you to share your perspectives on how #AI will influence inclusion in clinical trials. Most respondents believed this technology will play a major role in improving access. Here's one perspective on how this could occur by using AI to “widen the net” of #clinicaltrialrecruitment. https://lnkd.in/emFmvtXz

My post on clinical practice guidelines (CPGs) vs. machine learning inferences; the potential pitfalls of relying on machine learning inferences; the legal concept of "the standard of care" and its relationship and subtle differences with CPGs; and implications for physician liability. I also discuss the validation and certification of AI and large language models (LLMs) and clinical decision making as arguing from the evidence. #ai #algorithms #health #medicine

The #clinicaltrials industry will witness a transformative approach with AI. From driving innovation to making the trials more patient-centric to enhancing efficiency to improving patient recruitment and more, #artificialintelligence will make a huge difference in the industry. Read our full blog to know how the future uses of #AI in clinical trials. Contact us to explore how our AI capabilities can help your studies: https://bit.ly/3QW3svT #ClinicalResearch #Blogs #LifeSciences 

There are a lot of areas where AI/ML could potentially improve in how we design and conduct clinical trials. Having a high quality dataset for AI system training is crucial here, this is not different at all from other industries. "The biggest challenge delaying widespread adoption and success is improving the breadth, quality, diversity, and accessibility of the underlying data, on which these AI systems are trained. Without addressing this head on, we will continue to see biases perpetuated and hallucinations that contain false or misleading information." https://lnkd.in/gJchghgf