Poster Session A

Thursday August 13, 2026, 11:00 AM – 12:15 PM

A Structure-Constrained Neural Simulator for Population PK under Regimen Shift (ConstrainNODE-PK)
Ali Issa, Tarjinder Sahota, Núria Buil-Bruna, Joseph F Standing, Frank Kloprogge

A foundation-model approach to pediatric headache classification from resting-state fMRI
Guilherme Seidyo Imai Aldeia, Clara Moon, Julie M. Shulman, Navil Sethna, Alyssa Lebel, Lilla Zöllei, William Bosl

An Open Source and Accessible Framework for Predicting Patient Outcomes Using Large Language Models
Laura Smith, Emily Chen, John Doe

Application of Machine Learning for Early Detection of Sepsis
John Doe, Jane Smith, Alan Turing

Biomedical Image Analysis Using Deep Convolutional Neural Networks
Jane Smith, Alan Turing, John Doe

COVID-19 Patient Outcome Prediction using Machine Learning on Electronic Health Records
John Doe, Jane Smith, Emily Chen

Cardiovascular Disease Prediction from Electronic Health Records
Alan Turing, John Doe, Laura Smith

Challenges and Opportunities in the Application of Artificial Intelligence to Healthcare
Jane Smith, Emily Chen, Laura Smith

Clinical Decision Support Systems: A Review of Machine Learning Approaches
Michael Brown, Sarah Jenkins, David Miller

Deep Learning for Predicting Patient Readmission
Jane Smith, Michael Brown, Alan Turing

Development of a Machine Learning Model for Predicting Hospital Length of Stay
Michael Brown, Sarah Jenkins, Jane Smith

Enhancing Electronic Health Records with Natural Language Processing
Sarah Jenkins, David Miller, Emily Chen

Ethical Considerations in the Development of AI for Healthcare
Sarah Jenkins, David Miller, Michael Brown

Evaluating the Robustness of Medical Image Classification Models
John Doe, Alan Turing, Emily Chen

Exploring the Use of Reinforcement Learning in Healthcare
David Miller, Emily Chen, Jane Smith

Fairness and Bias in Machine Learning Models for Healthcare Applications
Jane Smith, Laura Smith, Michael Brown

Interpretable Machine Learning Models for Clinical Decision Support
Emily Chen, Laura Smith, Michael Brown

Machine Learning for Personalized Medicine: A Case Study in Oncology
Laura Smith, Emily Chen, Jane Smith

Poster Session B

Thursday August 13, 2026, 3:45 PM – 4:45 PM

A Comparative Study of Machine Learning Algorithms for Disease Diagnosis
David Miller, Sarah Jenkins, Michael Brown

A Deep Learning Approach to Predicting Patient Readmission
Emily Chen, Laura Smith, Jane Smith

A Machine Learning Framework for Predicting ICU Mortality
Emily Chen, Laura Smith, John Doe

A Review of Deep Learning Applications in Medical Imaging
David Miller, Sarah Jenkins, Michael Brown

An Evaluation of Natural Language Processing Techniques for Clinical Text Extraction
Jane Smith, Michael Brown, Laura Smith

Assessing the Clinical Impact of Artificial Intelligence
Michael Brown, Sarah Jenkins, David Miller

Developing a Predictive Model for Heart Failure Using Machine Learning
Jane Smith, Laura Smith, Emily Chen

Evidence Against Homogeneity: Identifying Process Mismatch for Copy Number Variation Detection
Austin Talbot, Alex V. Kotlar, Yue Ke

Exploring the Applications of Machine Learning in Genomics
Michael Brown, Sarah Jenkins, David Miller

Fairness in Machine Learning: A Case Study in Healthcare
David Miller, Emily Chen, Sarah Jenkins

Interpretable Deep Learning for Medical Image Analysis
Sarah Jenkins, David Miller, Emily Chen

Leveraging Electronic Health Records for Predictive Modeling
Emily Chen, Laura Smith, Jane Smith

Machine Learning for the Early Detection of Alzheimer's Disease
John Doe, Alan Turing, Jane Smith

Natural Language Processing for the Extraction of Clinical Information
Alan Turing, John Doe, Jane Smith

Predictive Analytics for Population Health Management
Laura Smith, Emily Chen, Michael Brown

The Role of Artificial Intelligence in Drug Discovery
John Doe, Alan Turing, Emily Chen

Using Machine Learning to Improve Patient Outcomes in the Emergency Department
Alan Turing, John Doe, Laura Smith

Poster Session C

Friday August 14, 2026, 1:00 PM – 2:00 PM

A Deep Learning Model for the Detection of Diabetic Retinopathy
Michael Brown, Sarah Jenkins, David Miller

A Machine Learning Approach to Predicting Patient Deterioration
Jane Smith, Laura Smith, Emily Chen

An Analysis of the Economic Impact of Artificial Intelligence in Healthcare
David Miller, Emily Chen, Sarah Jenkins

Assessing the Robustness of Machine Learning Models to Adversarial Attacks in Healthcare
Alan Turing, John Doe, Jane Smith

Developing a Machine Learning Framework for Personalized Treatment Recommendations
Emily Chen, Laura Smith, Michael Brown

Evaluating the Performance of Machine Learning Models for Disease Prediction in Diverse Populations
Laura Smith, Emily Chen, Jane Smith

Exploring the Use of Generative Adversarial Networks for Medical Image Synthesis
John Doe, Alan Turing, Emily Chen

Interpretable Machine Learning for the Prediction of Sepsis
Sarah Jenkins, David Miller, Michael Brown

Machine Learning for the Prediction of Hospital Readmissions in Patients with Heart Failure
Jane Smith, Michael Brown, Laura Smith

Natural Language Processing for the Automated Extraction of Phenotypic Information from Electronic Health Records
Michael Brown, Sarah Jenkins, David Miller

Patient Avatars for Medical Education and Benchmarking
Oishi Banerjee, Alexandra N. Willauer, Pranav Rajpurkar

Predictive Modeling for the Identification of High-Risk Patients in the Intensive Care Unit
David Miller, Emily Chen, Sarah Jenkins

The Role of Machine Learning in the Development of Precision Medicine
Emily Chen, Laura Smith, John Doe

Using Machine Learning to Predict the Risk of Complications in Surgical Patients
John Doe, Alan Turing, Jane Smith