Search Results for author:
Found 7 papers, 2 papers with code
Multi-objective generative AI for designing novel brain-targeting small molecules
We design a library of 26, 581 novel and diverse small molecules containing hits with high predicted BBB permeability and favorable predicted safety and toxicity profiles, and that could readily be synthesized for experimental validation in the wet lab.
Empowering Biomedical Discovery with AI Agents
We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms.
Graph AI in Medicine
With diverse data -- from patient records to imaging -- GNNs process data holistically by viewing modalities as nodes interconnected by their relationships.
Multimodal learning with graphs
Artificial intelligence for graphs has achieved remarkable success in modeling complex systems, ranging from dynamic networks in biology to interacting particle systems in physics.
NeuraHealth: An Automated Screening Pipeline to Detect Undiagnosed Cognitive Impairment in Electronic Health Records with Deep Learning and Natural Language Processing
Dementia related cognitive impairment (CI) is a neurodegenerative disorder, affecting over 55 million people worldwide and growing rapidly at the rate of one new case every 3 seconds.
Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records
Automated mining of these notes presents an opportunity to label patients with cognitive impairment in EHR data.
Natural Language Processing to Detect Cognitive Concerns in Electronic Health Records Using Deep Learning
Dementia is under-recognized in the community, under-diagnosed by healthcare professionals, and under-coded in claims data.
