Ran Shaul’s Post

Over the last couple of years Large Language Models (LLMs) have emerged as a disruptive technology with potential to transform healthcare, however the accuracy and reliability of information provided by LLMs can be a matter of life or death, as it could potentially affect healthcare decisions, diagnosis, and treatment plans. In order to address this issue The Open Medical LLM leaderboard provides a comprehensive assessment of each model's medical knowledge and question answering capabilities https://lnkd.in/eusBVbhB

The Open Medical LLM Leaderboard: Real-time Global Peer Review https://lnkd.in/gKJwKw9t A Deep Dive on the Hugging Face Open Medical LLM Leaderboard and how it's changing the conversation on Medical AI. Spoiler alert- there's over 600,000 unique models available to download on Huggingface right now. And that number's just going to increase as the GenAI learning curve continues dropping🤘. Move Fast & Make Things- You love to see it ;). #AI #Huggingface #GenAI #DeepTech #huggingface

Knowing where to use a probabilistic model vs a deterministic model is an art in itself. A great read about this topic is here - https://lnkd.in/e2y6Hnmh. Any generated data has an inherent problem of it being probabilistic instead of deterministic. In case of building models for healthcare this proves to be essential since the method you choose will really impact trustworthiness of the model outcome

Generative AI has changed the way every industry functions, but industries like Healthcare, where data privacy, security & sensitivity have held back such initiatives. At goML, we have identified niche use cases, which make Healthcare professionals’ lives better, delivering value to patients. 80% of a Doctor's time goes into compiling patient notes into a more comprehensible format for compliance & auditing instead of spending time on the patient's diagnosis & right treatment. Through this demo video, we showcase how we worked with a US-based independent Healthcare services provider to leverage GPT-4 & Whisper APIs to build a Doctor & Patient conversation transcription agent with intelligent conversation mapping, diagnosis identification and automated EHR filing. Imagine a voice-based assistant that transcribes realtime doctor - patient conversation, identifies the relevant data & clears out the noise, to finally compile comprehensible notes, clearly highlighting the symptoms, diagnoses and next steps. Eventually, these notes are combined with the patient’s historical data to identify the relevant treatment options. Watch the video (https://lnkd.in/dm453p3x) to see the future of healthcare in action! Visit www.goml.io to know more! #healthcare #AI #generativeAI #GPT4 #Whisper #doctor #medicine #innovation #efficiency #patientcare #goML

This research focuses on making #llms, which are already great at understanding and generating text, even better at answering medical questions. https://lnkd.in/eR84Hynb

The Open Medical LLM Leaderboard: Real-time Global Peer Review https://lnkd.in/gxhReStQ A Deep Dive on the Hugging Face Open Medical LLM Leaderboard and how it's changing the conversation on Medical AI. Spoiler alert- there's over 600,000 unique models available to download on Huggingface right now. And that number's just going to increase as the GenAI learning curve continues dropping🤘. Move Fast & Make Things- You love to see it ;). #AI #Huggingface #GenAI #DeepTech #huggingface

Trust your doctor: Study shows human medical professionals are more reliable than artificial intelligence tools

Great Panel on CMEpalooza: Navigating AI Integration in CME.

🚀 Exciting AI News! 🌟 After ChatGPT's immense success, domain-specific AI tools are taking center stage! Google has launched Med-PalM, an AI marvel in the medical domain. It's been rigorously evaluated using medical exams, research, and real consumer queries. Check it out: https://lnkd.in/gvKRv2MR What's your favorite AI tool in your daily life? 🤔 Let's celebrate the progress and possibilities of AI together! 💡 #AI #MedPalM #Google #TechInnovation

The article discusses the essential steps required to further the utilization of artificial intelligence (AI) in clinical trials.