Archives: “Archives”

Patrick Kevin Gleeson, MD, MSCE

https://www.coltonconsortium.org/directory/patrick-kevin-gleeson-md-msce/

NRSA Postdoctoral Fellow, Department of Medicine (Pulmonary, Allergy and Critical Care), Perelman School of Medicine, University of Pennsylvania Dr. Patrick Gleeson is an Instructor of Medicine within the Division of […]

Rebecca Haberman, MD

https://www.coltonconsortium.org/directory/rebecca-haberman-md/

Assistant Professor, Department of Medicine, NYU Grossman School of Medicine / NYU Langone Health Associate Director, Psoriatic Arthritis Center, NYU Grossman School of Medicine / NYU Langone Health Assistant Director, […]

Aristotelis Tsirigos, PhD

https://www.coltonconsortium.org/directory/aristotelis-tsirigos-phd/

Professor, Department of Medicine, NYU Grossman School of Medicine / NYU Langone Health Professor, Department of Pathology, NYU Grossman School of Medicine / NYU Langone Health Co-Director, Division of Precision […]

Danielle Mowery, PhD, FAMIA

https://www.coltonconsortium.org/directory/danielle-mowery-phd-famia/

Assistant Professor, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania Dr. Danielle Mowery is an Assistant Professor of Informatics in the Department of Biostatistics, Epidemiology […]

Early Detection and Diagnosis of Autoimmune Diseases Using Foundation AI Models

https://www.coltonconsortium.org/projects/early-detection-and-diagnosis-of-autoimmune-diseases-using-foundation-ai-models/

Applying self-supervised AI to multi-modal electronic health records — integrating clinical notes, labs, and imaging — this project builds scalable diagnostic models to detect autoimmune diseases earlier and more precisely.

Developing a Multi-parameter Prognostic Prediction Model for Disability Ranks and Progression of Patients with Multiple Sclerosis at the Early Stages of the Disease

https://www.coltonconsortium.org/projects/developing-a-multi-parameter-prognostic-prediction-model-for-disability-ranks-and-progression-of-patients-with-multiple-sclerosis-at-the-early-stages-of-the-disease/

Integrating clinical, imaging, and biological data from large real-world MS cohorts, this project builds a machine learning model to predict disability progression early and enable personalized treatment decisions.

A Data-Driven Framework for Predicting and Managing Flares in Inflammatory Bowel Disease

https://www.coltonconsortium.org/projects/a-data-driven-framework-for-predicting-and-managing-flares-in-inflammatory-bowel-disease/

Combining machine learning with microbiome and metabolomic data from 4,000+ IBD patients, this project develops tools to predict disease flares, identify therapeutic targets, and enable personalized flare prevention.

Wearables and AI Framework for Inflammatory Arthritis Assessment and Management

https://www.coltonconsortium.org/projects/wearables-and-ai-framework-for-inflammatory-arthritis-assessment-and-management/

Using wearable sensors and machine learning to analyze real-world movement and sleep data, this project aims to predict treatment response earlier and enable more personalized care for inflammatory arthritis.

Biomarker Discovery for Early Prediction of Autoimmunity in Immunotherapy Patients Through Deep Immune Profiling and Temporal Graph Convolutional Networks

https://www.coltonconsortium.org/projects/biomarker-discovery-for-early-prediction-of-autoimmunity-in-immunotherapy-patients-through-deep-immune-profiling-and-temporal-graph-convolutional-networks/

Using temporal graph machine learning and deep immune profiling to predict which cancer immunotherapy patients will develop autoimmune adverse events before they occur.

High-Throughput Center for AutoImmune Therapeutic Discovery (HIT-AI)

https://www.coltonconsortium.org/projects/high-throughput-center-for-autoimmune-therapeutic-discovery-hit-ai/

Systematically identifying and validating repurposed FDA-approved drugs for over 160 autoimmune diseases using AI, knowledge graphs, and high-throughput experimental screening.