Clinical Risk Prediction

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Clinical risk prediction estimates the likelihood and timing of outcomes such as deterioration, complications, readmission, or disease onset to support screening and care decisions. Methods range from logistic and Cox regression and clinical scores to gradient-boosted trees, survival models, temporal neural networks, and multimodal systems combining EHR data, notes, images, and wearable signals. Current work also explores calibration, uncertainty estimates, explainability, and privacy-preserving learning across hospitals. A central challenge is ensuring that strong results reflect genuine future risk and remain reliable across populations and settings, rather than being inflated by data leakage or weakened by distribution shift.

Latest papers

218 papers21 papers in the last four weeks, down 5% on the four weeks before. 0.1% of all new papers.

Deep Kernel Learning for Stratifying Glaucoma Trajectories
May 1, 2026Bruce Rushing, Angela Danquah, Alireza Namazi +2Deep Kernel Learning Clinical Outcome Prediction
Research Computing, University of Virginia · School of Data Science, University of Virginia · School of Medicine, University of Virginia
From Prediction to Practice: A Task-Aware Evaluation Framework for Blood Glucose Forecasting
May 1, 2026Alireza Namazi, Heman ShakeriHealthcare Clinical Decision Support
Department of Computer Science University of Virginia Charlottesville, VA, USA · School of Data Science University of Virginia Charlottesville, VA, USA
PROMISE-AD: Progression-aware Multi-horizon Survival Estimation for Alzheimer's Disease Progression and Dynamic Tracking
Apr 30, 2026Qing Lyu, Jeremy Hudson, Mohammad Kawas +3Alzheimer's Disease Survival Analysis
Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510 USA · Department of Radiology Oncology, Wake Forest University School of Medicine, Winston-Salem, NC 27157 USA · Department of Applied Mathematics & Statistics and Department of Computer Science, Stony Brook University, Stony Brook, NY 11794 USA
Simulating clinical interventions with a generative multimodal model of human physiology
Apr 30, 2026Guy Lutsker, Gal Sapir, Jordi Merino +7Multivariate Time Series Forecasting Healthcare
Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. · Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel. · NVIDIA, Tel Aviv, Israel. +5
Dialysis Risk Prediction and Treatment Effect Estimation for AKI patients using Longitudinal Electronic Health Records
Apr 27, 2026Kalyani P. Pande, Evan Yang, Bryan Zhu +3Causal Effect Estimation Healthcare
Stony Brook University, Stony Brook, NY, USA
EndoGov: A knowledge-governed multi-agent expert system for endometrial cancer risk stratification
Apr 26, 2026Weiye Dai, Liyun Shi, Zanxiang He +4Clinical Decision Support Multi-Agent Systems
aShenzhen Technology University, Shenzhen, China · bShenzhen People’s Hospital, Shenzhen, China · dShenzhen University, Shenzhen, China +1
Impact of Age Specialized Models for Hypoglycemia Classification
Apr 26, 2026Beyza Cinar, Maria MaleshkovaType 1 Diabetes Time Series Classification
Data Engineering · Helmut Schmidt University · Germany
Reliable Self-Harm Risk Screening via Adaptive Multi-Agent LLM Systems
Apr 24, 2026Meghana Karnam, Ananya JoshiAI Agent Reliability Multi-Agent LLM Systems
Johns Hopkins University Baltimore, USA
Reliability Auditing for Downstream LLM tasks in Psychiatry: LLM-Generated Hospitalization Risk Scores
Apr 23, 2026Shevya Panda, Shinjini Bose, Ananya JoshiPrompt Sensitivity LLM Auditing
Johns Hopkins University Baltimore, USA
Causal-Transformer with Adaptive Mutation-Locking for Early Prediction of Acute Kidney Injury
Apr 22, 2026Weizhi Nie, Haolin ChenCausal Interpretability Longitudinal EHR Modeling
School of Electrical and Information Engineering, Tianjin University
Clinically Interpretable Sepsis Early Warning via LLM-Guided Simulation of Temporal Physiological Dynamics
Apr 22, 2026Weizhi Nie, Zhen Qu, Weijie Wang +4Interpretable ML LLM-Based Time Series Forecasting
School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, Tianjin, China · Department of Information Engineering and Computer Science, University of Trento, Trento, Trentino, Italy · Department of Orthopedics, Affiliated Kunshan Hospital of Jiangsu University, Kunshan, Jiangsu, China +3
Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records
Apr 22, 2026John Xiang, Rohith Ravindranath, Sophia Y. WangClinical Risk Prediction Glaucoma Detection
Department of Ophthalmology, Byers Eye Institute, Stanford University, Stanford, California, USA
LLMs for Cardiovascular Risk Prediction from Structured Clinical Data
Apr 21, 2026Jeba Maliha, Md Rafiul KabirMedical LLMs Clinical Risk Prediction
Central Michigan University, Mount Pleasant, MI, USA
REVEAL: Multimodal Vision-Language Alignment of Retinal Morphometry and Clinical Risks for Incident AD and Dementia Prediction
Apr 20, 2026Seowung Leem, Lin Gu, Chenyu You +2Alzheimer's Disease Medical Imaging
J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, United2026 States · Research Institute of Electrical Communication, Tohoku University, Japan · Department of Applied Mathematics & Statistics, Stony Brook University, United StatesApr +1
OC-Distill: Ontology-aware Contrastive Learning with Cross-Modal Distillation for ICU Risk Prediction
Apr 18, 2026Zhongyuan Liang, Junhyung Jo, Hyang-Jung Lee +2Contrastive Learning Cross-Modal Knowledge Distillation
Computational Precision Health UC Berkeley, UCSF · Samsung Advanced Institute of Technology (SAIT) · Computational Precision Health UC Berkeley, UCSF[cs.LG]
Nationwide EHR-Based Chronic Rhinosinusitis Prediction Using Demographic-Stratified Models
Apr 16, 2026Sicong Chang, Yidan Shen, Justina Varghese +7Medical Diagnosis Clinical Prediction
Electrical and Computer Engineering University of Houston Houston, USA · Otolaryngology Houston Methodist Hospital Houston, USA · Information Science Technology, University of Houston & Otolaryngology, Houston Methodist Hospital Houston, USA
CURA: Clinical Uncertainty Risk Alignment for Language Model-Based Risk Prediction
Apr 16, 2026Sizhe Wang, Ziqi Xu, Claire Najjuuko +2Language Model Calibration LLM Uncertainty Estimation
Washington University in St. Louis
Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings
Apr 16, 2026Wenhui Cui, Nicholas Swingle, Anand A. Joshi +2Clinical Outcome Prediction Clinical Risk Prediction
Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, CA, USA · Epilepsy Center, Cleveland Clinic Neurological Institute, OH, USA
CSRA: Controlled Spectral Residual Augmentation for Robust Sepsis Prediction
Apr 16, 2026Honglin Guo, Rihao Chang, He Jiao +3Sepsis Prediction Clinical Prediction
Tianjin University, Tianjin 300072, China · Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China · Tianjin Medical University General Hospital, Tianjin 300052, China
Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors
Apr 15, 2026Vojtěch Novák, Ivan Zelinka, Lenka Přibylová +3Clinical Outcome Prediction Clinical Risk Prediction
Department of Computer Science, Technical University of Ostrava, Czech Republic · IT4Innovations National Supercomputing Center, Ostrava, Czech Republic · Department of Applied Mathematics, Technical University of Ostrava, Czech Republic +3
Fall Risk and Gait Analysis in Community-Dwelling Older Adults using World-Spaced 3D Human Mesh Recovery
Apr 13, 2026Chitra Banarjee, Patrick Kwon, Ania Lipat +3Gait Analysis Healthcare
College of Medicine, UCF · Institute of AI, UCF · College of Nursing, UCF +1
LoGo-MR: Screening Breast MRI for Cancer Risk Prediction by Efficient Omni-Slice Modeling
Apr 13, 2026Xin Wang, Yuan Gao, George Yiasemis +13Medical Image Analysis Clinical Risk Prediction
Netherlands Cancer Institute · Radboud University Medical Center · University Medical Center Utrecht +1
TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection
Apr 12, 2026Sihang Zeng, Young Won Kim, Wilson Lau +4Clinical Risk Prediction Longitudinal EHR Modeling
Truveta Inc., Bellevue, WA, United States. · University of Washington, Seattle, WA, United States. · Fred Hutch Cancer Center, Seattle, WA, United States.
Frailty Estimation in Elderly Oncology Patients Using Multimodal Wearable Data and Multi-Instance Learning
Apr 8, 2026Ioannis Kyprakis, Vasileios Skaramagkas, Georgia Karanasiou +10Clinical Prediction Clinical Risk Prediction
ECE Dept. HMU FORTH-ICS Heraklion, Greece · FORTH-BRI Ioannina, Greece · Univ. of Ioannina (Med.) Physiology Lab Ioannina, Greece +6
A Clinical Point Cloud Paradigm for In-Hospital Mortality Prediction from Multi-Level Incomplete Multimodal EHRs
Apr 6, 2026Bohao Li, Tao Zou, Junchen Ye +2Electronic Health Records Clinical Risk Prediction
Beihang University, Beijing, China · The Hong Kong Polytechnic University, Hong Kong, China
Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints
Apr 2, 2026Minh-Khoi Pham, Thang-Long Nguyen Ho, Thao Thi Phuong Dao +8Tabular Foundation Models Retrieval-Augmented ICL
School of Computing, Dublin City University, Dublin, Ireland · ADAPT Centre, Dublin City University, Dublin, Ireland · University of Science, Vietnam National University, Ho Chi Minh City, Vietnam +5
MATA-Former & SIICU: Semantic Aware Temporal Alignment for High-Fidelity ICU Risk Prediction
Apr 2, 2026Zhichong Zheng, Xiaohang Nie, Xueqi Wang +3Clinical Risk Prediction Longitudinal EHR Modeling
Tongji University · Shanghai Innovation Institute · Harbin Institute of Technology +1
CARE: Privacy-Compliant Agentic Reasoning with Evidence Discordance
Apr 1, 2026Haochen Liu, Weien Li, Rui Song +6Privacy-Preserving Language Models Healthcare
University of Cambridge · McGill University · MBZUAI - Mohamed bin Zayed University of Artificial Intelligence +2
Multimodal Machine Learning for Early Prediction of Metastasis in a Swedish Multi-Cancer Cohort
Mar 31, 2026Franco Rugolon, Korbinian Randl, Braslav Jovanovic +2Clinical Outcome Prediction Clinical Risk Prediction
Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden
A Latent Risk-Aware Machine Learning Approach for Predicting Operational Success in Clinical Trials based on TrialsBank
Mar 30, 2026Iness Halimi, Emmanuel Piffo, Oumnia Boudersa +11Clinical Risk Prediction
Groupe Sorintellis Inc., Montréal, Québec, Canada · Department of Computer Science and Operations Research, Université de Montréal, Montréal, Québec, Canada · Department of Computer Engineering, École Polytechnique de Montréal, Montréal, Québec, Canada +6

May 1, 2026J/K move · Enter open · S save

Deep Kernel Learning for Stratifying Glaucoma Trajectories

Bruce Rushing, Angela Danquah, Alireza Namazi, Arjun Dirghangi+1

Research Computing, University of Virginia · School of Data Science, University of Virginia · School of Medicine, University of Virginia

Deep Kernel Learning Clinical Outcome Prediction Kernel Methods Longitudinal EHR Modeling Clinical Risk Prediction Gaussian Process Regression

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Effectively stratifying patient risk in chronic diseases like glaucoma is a major clinical challenge. Clinicians need tools to identify patients at high risk of progression from sparse and irregularly-sampled electronic health records (EHRs). We propose a novel deep kernel learning (DKL) architecture that leverages a Gaussian Process (GP) backend. The GP's kernel is defined by a transformer-based feature extractor applied to clinical-BERT embeddings to model glaucoma patient trajectories from multimodal EHR data. Our method successfully identifies three clinically distinct patient subgroups. Crucially, the model learns to decouple disease progression from current severity, identifying a high-risk group with a worsening trajectory despite having better average visual acuity than a second, stably poor group. This reveals that the model learns to identify progression risk rather than just the current disease state. This ability to stratify patients based on their risk trajectory progression offers a powerful tool for clinical decision support, enabling targeted interventions for high-risk individuals and improving the management of glaucoma care.