Scientific Posters
Sub-insight Learning Disentangles Heterogeneous MDD Trial Data, Boosting Predictive Accuracy and Patient Stratification for Escitalopram Response
Leveraging ML-derived Patient Personas to Assess Functional Unblinding in Ketamine Trials for Major Depressive Disorder (MDD)
Detecting Site-Level Anomalies via Paradoxical Patient Analysis in an Alzheimer’s Disease Clinical Trial
Testing Machine Learning of Multimodal Digital Markers for Early Detection of Cognitive Impairment in Alzheimer’s Disease
Precision in Psychiatry Trials: A Novel Mathematically-Augmented Machine Learning Approach for Identifying Patient Personas for Tailored Antipsychotic Therapy for the CATIE Schizophrenia Trial
Leveraging Alternative AI/ML Technologies to Identify Predictive Biomarkers for Chemotherapy Selection: An Analysis of the COMPASS Trial Evaluating Chemotherapy Response in Advanced PDAC
Preferential Drug Response Model in a Schizophrenia Trial via an Alternative AI Method - Revisiting the CATIE Schizophrenia Trial
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
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
Evaluating Drug Efficacy: Leveraging Machine Learning Insights For Placebo Response Modeling
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
NetraAI Reveals Subpopulations of Bulbar and Limb ALS Using Transcriptomic Analysis
