As a researcher myself, I understand firsthand that systematic literature reviews have long been one of the most challenging and time-consuming aspects of clinical research. I'm excited to share that at Keiji AI, we've developed a solution to significantly simplify this critical

💡 Revolutionizing Clinical Research with AI-Powered Code Generation 💻 arxiv.org/abs/2410.21591 Data science is crucial in clinical research, but traditional coding methods can slow down vital insights. The latest advancements in Large Language Models (LLMs) are reshaping how

We just published Clinical Trials Demystified: An AI Researcher’s Guide (Part 2) medium.com/p/clinical-tri…

We just published Clinical Trials Demystified: An AI Researcher’s Guide (Part 2) medium.com/p/clinical-tri… #AI #clinicaltrials #AIforClinicaltrials

Discover how AI agents can automate your systematic review with literature mining.

🚀 AI for Health Webinar – Beyond EHRs: Bridging Clinical Records and External Knowledge for Better Patient Outcomes 🩺💡 Join us for a fantastic talk by Joyce Ho (Emory University) on how we can bridge electronic health records (EHRs) with external knowledge sources like

Excited to share that Dr. Emily Alsentzer from Stanford University will give a talk on Knowledge-Enhanced Machine Learning for Healthcare! Emily’s work is at the cutting edge of clinical AI—blending medical expertise with machine learning to tackle real-world challenges like rare

Excited to host Dr. Tristan Naumann from Microsoft Research tomorrow for a Keiji AI webinar on: 🧠 "Biomedical NLP in the Age of GenAI" 🕒 Tuesday | 3–4 PM EST He’ll share how large language models are transforming real-world evidence (RWE) generation by unlocking insights from

🚀 New Research from Keiji AI! We’re proud to share our latest paper: "A Foundation Model for Human-AI Collaboration in Medical Literature Mining" 📚🤖 [Published on arXiv: arxiv.org/abs/2501.16255] Systematic reviews are the cornerstone of evidence-based medicine—but they're

What if we could enrich incomplete electronic health records to improve healthcare AI applications?Patterns, a Cell Press journal University of Illinois "MediSim: Multi-granular simulation for enriching longitudinal, multi-modal electronic health records" • MediSim is a multi-modal generative framework

🧠 Excited to share our latest breakthrough in medical AI: SECONDGRAM! When studying brain diseases like Alzheimer's and Parkinson's, we need to track changes over time. But here's the problem: only ~12% of patients return for follow-up MRI scans. This leaves us with incomplete

I just published Being a Computer Science Professor: The Ultimate Career in the Age of AI medium.com/p/being-a-comp…

🚀 Missed our latest AI for Health webinar last week? Catch up now on YouTube! 🎥 Watch the talk: “Building Biomedical Datasets for the Future of AI” by Dr. Aaron Lee — a deep dive into the NIH AI-READI project and how it’s transforming Type 2 Diabetes research through large,

🧠 Our new paper on Cell Patterns! MediSim tackles one of the biggest challenges in medical research: incomplete multi-modal patient records. This multi-modal generative model can: ✅ Fill missing visits & medical codes ✅ Generate realistic clinical notes & X-rays ✅ Boost

🚀 Don’t miss today’s AI for Health talk by Dr. David Sontag (MIT) — a rare leader who not only builds state-of-the-art AI algorithms but also translates them into real-world healthcare impact. From foundational models to clinical decision support, his work bridges lab innovation

I just published Powering the Next Generation of Clinical Research: How MCP Unleashes TrialMind Agents medium.com/p/powering-the…

AI agents are redefining clinical trials. From patient-trial matching to literature mining, TrialMind (via Mayo Clinic Platform) is pushing the frontier. 🧠💊 Read more: medium.com/@jimeng_57761/… #AI #ClinicalTrials #RWD #TrialMind #LLM

Excited to share our new perspective in Nature Digital Medicine on adapting generalist AI for specialized medical applications! 🎉 Working with the amazing team at Keiji AI and industry collaborators, we developed a systematic framework addressing a critical challenge: how to