PSB 2026 proceedings are published as Open Access chapters by World Scientific Publishing Company and distributed under the terms of the Creative Commons Attribution (CC BY) 4.0 License.

PSB Proceedings for All Years

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A PDF of the full PSB 2026 Proceedings is available.

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Table of Contents

• Preface
• AI and Machine Learning in Clinical Medicine: Bridging or Separating Model Intelligence and Human Expertise
• Biological Molecular Function: Methods and Benchmarks for Finding Function in Biological Dark Matter
• Fairness and Bias in Biomedical AI/ML: Defining Goals and Putting Them into Practice
• Precision Medicine: Integrating Large-Scale Data and Intermediate Phenotypes for Understanding Health and Treating Disease
• Systems Biology And Network Analysis: From Multi-Omics Integration To Biological Mechanisms
• Workshops

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Preface

AI and Machine Learning in Clinical Medicine: Bridging or Separating Model Intelligence and Human Expertise

Session Introduction

Fateme Nateghi Haredasht, Joseph D. Romano, Brett K Beaulieu-Jones, Dokyoon Kim, Alexander Ioannidis, Geoffrey H Tison, Roxana Daneshjou, Jonathan H. Chen; Pacific Symposium on Biocomputing 31:1-11(2026)

Inference Gap in Domain Expertise and Machine Intelligence in Named Entity Recognition: Creation of and Insights from a Substance Use-related Dataset

Sumon Kanti Dey, Jeanne M. Powell, Azra Ismail, Jeanmarie Perrone, Abeed Sarker; Pacific Symposium on Biocomputing 31:12-26(2026)

ColonCrafter: A Depth Estimation Model for Colonoscopy Videos Using Diffusion Priors

Romain Hardy, Tyler M. Berzin, Pranav Rajpurkar; Pacific Symposium on Biocomputing 31:27-41(2026)

A Clinician-Guided Framework for Endoscopic AI: Developing PanEndoAtlas and Benchmarking Foundation Models Across the Full GI Spectrum

Shreya Johri, Luyang Luo, Hong-Yu Zhou, Todd Brenner, Sami Elamin, Mark Enrik Geissler, Tyler M. Berzin, Pranav Rajpurkar; Pacific Symposium on Biocomputing 31:42-56(2026)

Higher-order Interaction Matters: Modeling Epidemics via Dynamic Hypergraph Neural Networks

Songyuan Liu, Shengbo Gong, Tianing Feng, Zewen Liu, Max S.Y Lau, Wei Jin; Pacific Symposium on Biocomputing 31:57-70(2026)

Scoring Physician Risk Communication in Prostate Cancer Using Large Language Models

Guillermo Lopez-Garcia, Dongfang Xu, Michael Luu, Renning Zheng, Timothy J. Daskivich, Graciela Gonzalez-Hernandez; Pacific Symposium on Biocomputing 31:71-84(2026)

SeizureFormer: A Multi-Scale Transformer for Seizure Risk Forecasting from RNS-Derived Biomarkers

Tianning Feng, Juntong Ni, Wei Jin, Ezequiel Gleichgerrcht; Pacific Symposium on Biocomputing 31:85-98(2026)

3DReasonKnee: Advancing Grounded Reasoning in Medical Vision Language Models

Sraavya Sambara, Sung Eun Kim, Xiaoman Zhang, Luyang Luo, Shreya Johri, Mohammed Baharoon, Du Hyun Ro, Pranav Rajpurkar ; Pacific Symposium on Biocomputing 31:99-113(2026)

Abstention and Threshold Identification for Uncertainty Management in Clinical Decision Tools: A Case Study using Human-In-The-Loop Pediatric Autism Classifiers

Aiden Ko, Aaron Kline, Kaitlyn Dunlap, SaiMourya Surabhi, Parnian Azizian, Peter Y. Washington, Dennis P. Wall; Pacific Symposium on Biocomputing 31:114-129(2026)

Evaluation of Large Language Models as Emergency Department Revisit Predictors

Emma Chen, Luyang Luo, Fatma Gunturkun, Sraavya Sambara, Rushil Arora, Boyang Tom Jin, Pranav Rajpurkar, David A. Kim; Pacific Symposium on Biocomputing 31:130-143(2026)

Speaker Role Identification in Clinical Conversations

Andrew Zolensky, Kuk Jin Jang, Janice Sabin, Andrea Hartzler, Basam Alasaly, Sriharsha Mopidevi, Mark Liberman, Kevin Johnson; Pacific Symposium on Biocomputing 31:144-157(2026)

Learning Causally Predictable Outcomes from Psychiatric Longitudinal Data

Eric V. Strobl; Pacific Symposium on Biocomputing 31:158-172(2026)

Quantifying surprise in clinical care: Detecting highly informative events in electronic health records with foundation models

Michael C. Burkhart, Bashar Ramadan, Luke Solo, William F. Parker, Brett K. Beaulieu-Jones; Pacific Symposium on Biocomputing 31:173-188(2026)

Retrieval Augmented Guardrails for AI Drafted Patient Portal Messages: Error Taxonomy Construction and Large-Scale Evaluation

Wenyuan Chen, Fateme Nateghi Haredasht, Kameron C. Black, François Grolleau, Emily Alsentzer, Jonathan H. Chen, Stephen P. Ma ; Pacific Symposium on Biocomputing 31:189-204(2026)

Leveraging Large Language Models for Adverse Drug Event Detection: A Comparative Study of Token and Span-Based Named Entity Recognition

Howard Prioleau, Saurav Aryal, Jeremy Blackstone; Pacific Symposium on Biocomputing 31:205-218(2026)

Towards Automated Analysis of Gaze Behavior from Consumer VR Devices for Neurological Diagnosis

Lio Schmitz, Markus Plack, Berkan Koyak, Muhammad Ehsan Ullah, Ahmad Aziz, Reinhard Klein, Zorah Lähner, Hannah Dröge; Pacific Symposium on Biocomputing 31:219-235(2026)

Automated Chest X-ray Report Generation Remains Unsolved

Xiaoman Zhang, Julian Nicolas Acosta, Xiaoli Yang, Subathra Adithan, Luyang Luo, Hong-Yu Zhou, Joshua Miller, Ouwen Huang, Zongwei Zhou, Ibrahim Ethem Hamamci, Shruthi Bannur, Kenza Bouzid, Xi Zhang, Zaiqiao Meng, Aaron Nicolson, Bevan Koopman, Inhyeok Baek, Hanbin Ko, Mercy Prasanna Ranjit, Shaury Srivastav, Sriram Gnana Sambanthan, Pranav Rajpurkar; Pacific Symposium on Biocomputing 31:236-250(2026)

ReXVQA: A Large-scale Visual Question Answering Benchmark for Generalist Chest X-ray Understanding

Ankit Pal, Jung-Oh Lee, Xiaoman Zhang, Malaikannan Sankarasubbu, Seunghyeon Roh, Won Jung Kim, Meesun Lee, Pranav Rajpurkar; Pacific Symposium on Biocomputing 31:251-264(2026)

Detecting PTSD in Clinical Interviews: A Comparative Analysis of NLP Methods and Large Language Models

Feng Chen, Dror Ben-Zeev, Gillian Sparks, Arya Kadakia, Trevor Cohen; Pacific Symposium on Biocomputing 31:265-279(2026)

ED-Explain: Personalized Video Instructions for Patients Discharged from the Emergency Department

Luyang Luo, Emma Chen, Xiaoman Zhang, Julian Nicolas Acosta, Boyang Tom Jin, Fatma Gunturkun, Christian Rose, Carl Preiksaitis, Brian Suffoletto, Pranav Rajpurkar, David A. Kim; Pacific Symposium on Biocomputing 31:280-293(2026)

The Intention-Execution Disconnect in Medical AI: The ReXecution Framework for Evaluating Real-World Clinical Performance

Oishi Banerjee, Lucas Bijnens, Subathra Adithan, Pranav Rajpurkar; Pacific Symposium on Biocomputing 31:294-308(2026)

Leveraging Generative AI for Interpretable Clinical Decision Making Through Causal Graphs

Mehmet Eren Ahsen, Rand Kittani, Travis Gerke, Laya Krishnan, Sean Rogan, Erick R. Scott; Pacific Symposium on Biocomputing 31:309-323(2026)

Leveraging Large Language Models to Derive Multiple Sclerosis Progression Assessments from Clinical Notes: A Feasibility Study

Sy Hwang, Sunil Thomas, Heather Williams, Tom Hutchinson, Emily Schriver, Ashley Batugo, Amit Bar-Or, Vishakha Sharma, Frederik Buijs, Christopher Perrone, Danielle Mowery; Pacific Symposium on Biocomputing 31:324-337(2026)

WATCH-SS: Developing a Trustworthy and Explainable Modular Framework for Detecting Cognitive Impairment from Spontaneous Speech

Sydney Pugh, Matthew Hill, Sy Hwang, Rachel Wu, Kuk Jang, Stacy Iannone, Karen O'Connor, Kyra O'Brien, Eric Eaton, Kevin Johnson; Pacific Symposium on Biocomputing 31:338-353(2026)

MedAgentBench v2: Improving Medical LLM Agent Design

Eric Chen, Sam Postelnik, Kameron Black, Yixing Jiang, Jonathan Chen; Pacific Symposium on Biocomputing 31:354-371(2026)

Automated Evaluation of Large Language Model Response Concordance with Human Specialist Responses on Physician-to-Physician eConsult Cases

David JH Wu, Fateme Nateghi Haredasht, David Wu, Vishnu Ravi, Liam G. McCoy, Yingjie Weng, Kanav Chopra, Selin S. Everett, George Nageeb, Wenyuan Chen, Stephen P. Ma, Saloni Kumar Maharaj, Jessica Tran, Leah Rosengaus, Lena Giang, Olivia Jee, Ethan Goh, Jonathan H. Chen; Pacific Symposium on Biocomputing 31:372-387(2026)

MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries

François Grolleau, Emily Alsentzer, Timothy Keyes, Philip Chung, Akshay Swaminathan, Asad Aali, Jason Hom, Tridu Huynh, Thomas Lew, April Liang, Weihan Chu, Natasha Steele, Christina Lin, Jingkun Yang, Kameron Black, Stephen Ma, Fateme N. Haredasht, Nigam H. Shah, Kevin Schulman, Jonathan H. Chen; Pacific Symposium on Biocomputing 31:388-399(2026)

Asking the Right Questions: Benchmarking Large Language Models in the Development of Clinical Consultation Templates

Liam G. McCoy, Fateme Nateghi Haredasht, Kanav Chopra, David Wu, David JH Wu, Abass Conteh, Sarita Khemani, Saloni Kumar Maharaj, Vishnu Ravi, Arth Pahwa, Yingjie Weng, Leah Rosengaus, Lena Giang, Kelvin Zhenghao Li, Olivia Jee, Daniel Shirvani, Ethan Goh, Jonathan H. Chen; Pacific Symposium on Biocomputing 31:400-416(2026)

Biological Molecular Function: Methods and Benchmarks for Finding Function in Biological Dark Matter

Session Introduction

Jason McDermott, Yana Bromberg, Hannah Carter, Travis Wheeler; Pacific Symposium on Biocomputing 31:417-424(2026)

Implicitly and Differentiably Representing Protein Surfaces and Interfaces

Cory B. Scott, Charlie Rothschild, Benjamin E. Nye; Pacific Symposium on Biocomputing 31:425-437(2026)

Steering Protein Generative Models at Test-Time for Guided AAV2 Capsid Design

Ben Viggiano, Wenhui Sophia Lu, Xiaowei Zhang, Luis S. Mille-Fragoso, Xiaojing J. Gao, Euan Ashley, Wing Hung Wong; Pacific Symposium on Biocomputing 31:438-451(2026)

HALO: Hybrid Attention Model for Subcellular Localization

Shafayat Ahmed, Nazifa Ahmed Moumi, Liqing Zhang; Pacific Symposium on Biocomputing 31:452-464(2026)

PertSpectra: Interpretable Matrix Factorization for Predicting Functional Impact of Genetic Perturbation Experiments

Seowon Chang, Anna Shcherbina, Tal Ashuach, Shahin Mohammadi, Stephanie See, Ninad Ranadive, Emily Fox, Navpreet Ranu; Pacific Symposium on Biocomputing 31:465-479(2026)

Large Language Models Identify Causal Genes in Complex Trait GWAS

Suyash S. Shringarpure, Wei Wang, Sotiris Karagounis, Xin Wang, Anna C. Reisetter, Adam Auton, Aly A. Khan; Pacific Symposium on Biocomputing 31:480-493(2026)

Gene-R1: Reasoning with Data-Augmented Lightweight LLMs for Gene Set Analysis

Zhizheng Wang, Yifan Yang, Qiao Jin, Zhiyong Lu; Pacific Symposium on Biocomputing 31:494-507(2026)

LLM Agent Based Protein Function Prediction

Fernando Zhapa-Camacho, Olga Mashkova, Robert Hoehndorf, Maxat Kulmanov; Pacific Symposium on Biocomputing 31:508-519(2026)

Fairness and Bias in Biomedical AI/ML: Defining Goals and Putting Them into Practice

Session Introduction

Nicole Martinez-Martin, Mildred Cho, Abdoul Jalil Djiberou Mahamadou, Madalena Ng; Pacific Symposium on Biocomputing 31:520-523(2026)

Using Large Language Models to Audit Model Healthcare Biases

Zara N. Ansari, Aaron Fanous, Jesutofunmi A. Omiye, Ank Agarwal, Roxana Daneshjou; Pacific Symposium on Biocomputing 31:524-537(2026)

From Detection to Mitigation: Addressing Bias in Deep Learning Models for Chest X-Ray Diagnosis

Clemence Mottez, Louisa Fay, Maya Varma, Sophie Ostmeier, Curtis Langlotz; Pacific Symposium on Biocomputing 31:538-550(2026)

Deciphering the Influence of Demographic Factors on the Treatment of Pediatric Patients in the Emergency Department

Helena Coggan, Anne Bischops, Pradip Chaudhar, Yuval Barak-Corren, Andrew M. Fine, Ben Y. Reis, Jaya Aysola, William G. La Cava; Pacific Symposium on Biocomputing 31:551-565(2026)

Barriers to Designing Inclusive Ecological Momentary Assessment and Wearable Data Collection Protocols for AI-Driven Substance Use Monitoring in Hawai'i

Yinan Sun, Aditi Jaiswal, Ali Kargarandehkordi, Christopher Slade, Roberto M. Benzo, Kristina T. Phillips, Peter Washington; Pacific Symposium on Biocomputing 31:566-579(2026)

Building Fair and Trustworthy Biomedical AI: A Tool for Identifying Key Decision Points

Nicole Foti, Janet K. Shim, Caitlin McMahon, Sandra Soo-Jin Lee; Pacific Symposium on Biocomputing 31:580-595(2026)

Precision Medicine: Integrating Large-Scale Data and Intermediate Phenotypes for Understanding Health and Treating Disease

Session Introduction

Steven E. Brenner, Nilah M. Ioannidis, Tayo Obafemi-Ajayi, Anne O’Donnell-Luria; Pacific Symposium on Biocomputing 31:596-599(2026)

Integrating Polygenic Risk Improves Generative Forecasting of Disease Trajectories

Chris German, Suyash Shringarpure, Payam Dibaeinia, James Ashenhurst, Bertram L. Koelsch, Adam Auton, Aly A. Khan; Pacific Symposium on Biocomputing 31:600-611(2026)

Integrating Imaging-Derived Clinical Endotypes with Plasma Proteomics and External Polygenic Risk Scores Enhances Coronary Microvascular Disease Risk Prediction

Rasika Venkatesh, Tess Cherlin, Penn Medicine BioBank, Marylyn D. Ritchie, Marie A. Guerraty, Shefali S. Verma; Pacific Symposium on Biocomputing 31:612-628(2026)

Integrating Polygenic Scores with Clinical, Lifestyle, and Social Risk Factors to Improve Heart Failure Risk Prediction

Katie Cardone, Dokyoon Kim, Marylyn D. Ritchie; Pacific Symposium on Biocomputing 31:629-643(2026)

BioLM-NET: An Interpretable Deep Learning Model Combining Prior Biological Knowledge and Contextual LLM Gene Embeddings On Multi-Omics Data To Predict Disease

Jubair Ibn Malik Rifat, Thasina Tabashum, Md Marufi Rahman, Md Farhad Mokter, Sarthak Engala, Serdar Bozdag; Pacific Symposium on Biocomputing 31:644-665(2026)

Impact of Using PRS-CSx and Pruning and Thresholding for Polygenic Partitioning of Apparent Treatment Resistant Hypertension

Hannah M. Seagle, Jeewoo Kim, Alexis T. Akerele, VA Million Veteran Program, Adriana Hung, Jacklyn N. Hellwege, Todd L. Edwards; Pacific Symposium on Biocomputing 31:664-678(2026)

Prototype Learning to Create Refined Interpretable Digital Phenotypes from ECGs

Sahil Sethi, David Chen, Michael C. Burkhart, Nipun Bhandari, Bashar Ramadan, Brett Beaulieu-Jones; Pacific Symposium on Biocomputing 31:679-693(2026)

Deep Learning-based Classification of Patients with Postural Orthostatic Tachycardia Syndrome Using Wearable ECG and Accelerometer Data

Hyunjun Choi, Nicholas Matsumoto, Xi Li, Debbie Teodorescu, Anxhela Kote, Min-Jing Yang, Xiao Liu, Miguel E. Hernandez, Jason H. Moore, Graciela Gonzalez-Hernandez, Peng-Sheng Chen; Pacific Symposium on Biocomputing 31:694-707(2026)

Patch-Level Phenotype Identification Via Weakly Supervised Neuron Selection In Sparse Autoencoders for CLIP-Derived Pathology Embeddings

Keita Tamura, Yao-zhong Zhang, Yohei Okubo, Seiya Imoto; Pacific Symposium on Biocomputing 31:708-721(2026)

DeepDiff-SHAP: Interpretable Deep Learning for Subgroup- Specific Causal Hypothesis Generation Using Conditional SHAP

Aditya Sriram, Soyeon Kim, Joseph A. Carcillo, Hyun Jung Park; Pacific Symposium on Biocomputing 31:722-737(2026)

Literature-Driven Extraction and Computational Prediction of Causal Statements Linking Genetic Variants to Biological Processes, Pathways and Phenotypes

Jici Jiang, Predrag Radivojac, Benjamin M. Gyori; Pacific Symposium on Biocomputing 31:738-751(2026)

Systems Biology and Network Analysis: From Multi-Omics Integration to Biological Mechanisms

Session Introduction

Gurkan Bebek, Onur Mutlu, Iman Hajirasouliha, Joshua Welch, Serguei Pakhomov; Pacific Symposium on Biocomputing 31:752-754(2026)

Provenance Tracing in Network Diffusion Algorithms

Nure Tasnina, Mark Crovella, Simon Kasif, T. M. Murali; Pacific Symposium on Biocomputing 31:755-769(2026)

REPEL - Random Embedding Perturbation for Enhanced Learning of Protein Function

Di Zhou, Lenore Cowen, Kaiyi Wu, Xiaozhe Hu, Donna Slonim; Pacific Symposium on Biocomputing 31:770-783(2026)

Network Optimal Retrieval of Sparse Perturbations for Steady-State Control

Krithika Krishnan, Tiange Shi, Satyam Kumar, Han Yu, Rachael Hageman Blair; Pacific Symposium on Biocomputing 31:784-798(2026)

Discovery of Disease Relationships via Transcriptomic Signature Analysis Powered by Agentic AI

Ke Chen, Haohan Wang; Pacific Symposium on Biocomputing 31:799-814(2026)

A Random-Walk-Based Learning Framework to Uncover Novel Gene Candidates for Alzheimer’s Disease Therapy

Alena Orlenko, Binglan Li, Neda Khanjani, Mythreye Venkatesan, Li Shen, Marylyn D. Ritchie, Zhiping Paul Wang, Tayo Obafemi-Ajayi, Jason H. Moore; Pacific Symposium on Biocomputing 31:815-829(2026)

DRIVE-KG: Enhancing Variant-Phenotype Association Discovery in Understudied Complex Diseases Using Heterogeneous Knowledge Graphs

Ananya Rajagopalan, Tram Anh Nguyen, Lindsay A. Guare, Andre Luis Garao Rico, Rasika Venkatesh, Lannawill Caruth, Regeneron Genetics Center, Penn Medicine BioBank, Anurag Verma, Marylyn D. Ritchie, Molly A. Hall, Joseph D. Romano, Shefali Setia-Verma; Pacific Symposium on Biocomputing 31:830-848(2026)

Workshops

Advances of AI Methods in Single Cell Spatial Omics

Lana Garmire, Xiuwei Zhang, Joshua Levy; Pacific Symposium on Biocomputing 31:849-851(2026)

AI for Health: Leveraging Artificial Intelligence to Revolutionize Healthcare

Ruowang Li, Brian D. Davison, Tiffani Bright, Lifang He; Pacific Symposium on Biocomputing 31:852-854(2026)

Applications of AI & ML in Biomanufacturing of Cell and Gene Therapies

Eric Neumann, Karen Weisinger, Tom Londo; Pacific Symposium on Biocomputing 31:855-858(2026)

The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research

Ojas A. Ramwala, Nick Weber, Sean D. Mooney; Pacific Symposium on Biocomputing 31:859-864(2026)

Trust, Reproducibility, and Progress: The Roles of Independent Blind Prediction and Assessment and Benchmarking in Computational Biology

Gaia Andreoletti, Serghei Mangul, Predrag Radivojac, Steven E Brenner; Pacific Symposium on Biocomputing 31:865-868(2026)

Funding for this conference was made possible (in part) by R13LM006766 from the National Library of Medicine. The views expressed in written conference materials or publications and by speakers and moderators do not necessarily reflect the official policies of the Department of Health and Human Services; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government.

Funding for this conference was made possible (in part) by Grant # 2531429 from the U.S. National Science Foundation. The views expressed in written conference materials or publications, and by speakers and moderators, does not necessarily reflect the official policies of the U.S. National Science Foundation; nor does mention by trade names, commercial practices, or organizations imply endorsement by the U.S. Government.