POSTERS
Novel Machine Learning Approach Outperforms Traditional Approaches in Major Depressive Disorder Clinical Trials
Predictive Biomarker Discovery in Schizophrenia Using Advanced Machine Learning to Decode Heterogeneity
NetraAI Reveals Subpopulations of Bulbar and Limb ALS Using Transcriptomic Analysis
An AI aprroach to unravelling treatment response in pancreatic cancer: Insights from the COMPASS trial leveraging large language models (LLMs)
Using Machine Learning to Explore Multimodal Digital Markers for Early Detection of Cognitive Impairment in Alzheimer’s Disease
Introducing the Treatment Attitude Profile (TAP) Scale for Placebo Response Persona Discovery Using Attractor AI Technologies: Applications in Clinical Trial Patient Enrichment
The power of NetraAI: Precision medicine in oncology through sub-insight learning from small data sets
NetraAI-driven discovery of novel biomarkers in MSI-high colon cancer for precision immunotherapy
Using NetraAI to Discover Parkinson’s Disease Subtypes: Generative AI Reveals Transcriptomic Personas Linking Mitochondrial, Microbiome, and Immune Signaling
Evaluating Drug Efficacy: Leveraging Machine Learning Insights For Placebo Response Modeling
Identifying Efficacy Variables for the Use of Escitalopram in Mild Major Depression Disorder (MDD): Implications for Treatment-Resistant MDD Trials
NetraAI: Understanding Patient Populations Beyond Disease Labels for De-Risking Clinical Trials with Large Language Models
Uncovering an Association Between Oligodendroglioma and the Human Papillomavirus (HPV) Through Molecular Subpopulation Analysis Using NetraAI
Understanding treatment response in pancreatic cancer: NetraAI provides genetic differentiation in FOLFIRINOX and Gemcitabine response
Using AI on Data from Anxiety and Schizophrenia Trials to Identify Causal Clusters of Variables for Drug & Placebo Response Via Long Range Memory to Improve Clinical Trial Outcomes
