Clinical Prediction

Latest papers 201

30 papers in the last four weeks, up 30% on the four weeks before. 0.2% of all new papers.

Pretty Good Measurement for Radiomics: A Quantum-Inspired Multi-Class Classifier for Lung Cancer Subtyping and Prostate Cancer Risk Stratification
Feb 27, 2026Giuseppe Sergioli, Carlo Cuccu, Giovanni Pasini +4Multiclass Classification Quantum-Inspired ML
Università degli Studi di Cagliari, Via Is Mirrionis 1, Cagliari, 09123, Italy · Institute of Bioimaging and Complex Biological Systems - National Research Council (IBSBC - CNR), Cefalù, 90015, Italy · National Laboratory of South, National Institute for Nuclear Physics(LNS-INFN), Catania, 95125, Italy
MINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening
Feb 27, 2026Vrushank Ahire, Yogesh Kumar, Anouck Girard +1Cross-Modal Knowledge Distillation Alzheimer's Disease
Department of Computer Science and Engineering, Indian Institute of Technology Ropar, India · Embry-Riddle Aeronautical University, Florida, USA
PREBA: Surgical Duration Prediction via PCA-Weighted Retrieval-Augmented LLMs and Bayesian Averaging Aggregation
Feb 27, 2026Wanyin Wu, Kanxue Li, Baosheng Yu +4Clinical Prediction Retrieval-Augmented Generation
Wanyin Wu, Haoyun Zhao, and Dapeng Tao are with the School of Information Science and Engineering, Yunnan University, Kunming 650500, China. · Kanxue Li and Yibing Zhan are with the School of Computer Science, Wuhan University, Wuhan 430072, China. · Baosheng Yu is with the Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 639798. +1
Sample Size Calculations for Developing Clinical Prediction Models: Overview and pmsims R package
Feb 26, 2026Diana Shamsutdinova, Felix Zimmer, Oyebayo Ridwan Olaniran +4Clinical Prediction Statistical Power Analysis
Department of Biostatistics and Health Informatics, King’s College London · NIHR Biomedical Research Centre, Maudsley NHS Trust
Global Interpretability via Automated Preprocessing: A Framework Inspired by Psychiatric Questionnaires
Feb 26, 2026Eric V. StroblInterpretable ML Clinical Outcome Prediction
Department of Biomedical Informatics, University of Pittsburgh.
An Explainable Ensemble Framework for Alzheimer's Disease Prediction Using Structured Clinical and Cognitive Data
Feb 26, 2026Nishan MitraAlzheimer's Disease Classification Clinical Prediction
Computer Science & Engineering (AI&ML), Institute of Engineering & Management, Kolkata, India
Predicting Multi-Drug Resistance in Bacterial Isolates Through Performance Comparison and LIME-based Interpretation of Classification Models
Feb 25, 2026Santanam Wishal, Riad SaharaClinical Prediction
Universitas Siber Asia
Early Risk Stratification of Dosing Errors in Clinical Trials Using Machine Learning
Feb 25, 2026Félicien Hêche, Sohrab Ferdowsi, Anthony Yazdani +2Clinical Risk Prediction Clinical Prediction
Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland · Actelion Pharmaceuticals Ltd, Basel, Switzerland
PaReGTA: A Temporally Aware LLM-Based Patient Representation Framework for EHR Analytics
Feb 23, 2026Kihyuk Yoon, Lingchao Mao, Catherine Chong +3Longitudinal EHR Modeling Representation Learning
Georgia Institute of Technology · Meta · Mayo Clinic
Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark
Feb 23, 2026Lalitha Pranathi Pulavarthy, Raajitha Muthyala, Aravind V Kuruvikkattil +3Human-AI Collaboration Clinical Prediction
Dept. Biomedical Eng. & Informatics, Indiana University Indianapolis, Indianapolis, USA
Making Conformal Predictors Robust in Healthcare Settings: a Case Study on EEG Classification
Feb 23, 2026Arjun Chatterjee, Sayeed Sajjad Razin, John Wu +3Conformal Prediction Clinical Prediction
University of Illinois Urbana-Champaign, Urbana, IL 61801, USA · PyHealth · Bangladesh University of Engineering and Technology
Position: Evaluation of ECG Representations Must Be Fixed
Feb 19, 2026Zachary Berger, Daniel Prakah-Asante, John Guttag +1Representation Learning Electrocardiogram Classification
Massachusetts Institute of Technology, Cambridge, MA, USA · Massachusetts General Hospital, Boston, MA, USA
MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Tabular Prediction
Feb 10, 2026Zizheng Zhang, Yiming Li, Justin Xu +6Interpretable ML Clinical Prediction
Microsoft Research · University of Oxford
ECGFlowCMR: Pretraining with ECG-Generated Cine CMR Helps Cardiac Disease Classification and Phenotype Prediction
Jan 28, 2026Xiaocheng Fang, Zhengyao Ding, Guangkun Nie +9Synthetic Data Pretraining Medical Diagnosis
State Key Laboratory of General Artificial Intelligence, Peking University · School of Intelligence Science and Technology, Peking University, Beijing, China · Polytechnic Institute of Zhejiang University, Zhejiang University, Hangzhou, China +4
ROOFS: RObust biOmarker Feature Selection
Jan 8, 2026Anastasiia Bakhmach, Paul Dufossé, Simon Charpigny +4Scientific Discovery Clinical Prediction
1*COMPO Team (COMPutational Pharmacology and clinical Oncology), Inria Sophia Antipolis – Méditerranée, Inserm U1068, CNRS UMR7258, Institut Paoli-Calmettes, Aix-Marseille University, Marseille, France. · 2Veracyte SAS, Marseille, France. · 3Assistance Publique-Hôpitaux de Marseille (APHM), Marseille, France. +1
Improving Forecasts of Suicide Attempts for Patients with Little Data
Nov 22, 2025Genesis Hang, Annie Chen, Hope Neveux +2Latent Variable Models Gaussian Processes
Wellesley College · Harvard University
General Demographic Pre-trained Models for Enhancing Predictive Performance Across Diseases and Population
Sep 9, 2025Li-Chin Chen, Ji-Tian Sheu, Yuh-Jue ChuangHealthcare Representation Learning
Data Analytics and Digital Transformation Research Center National Taiwan University Taipei, Taiwan · Department of Health Care Management Chang Gung University Taoyuan, Taiwan
Glucose-ML: A collection of longitudinal diabetes datasets for development of robust AI solutions
Jul 18, 2025Temiloluwa Prioleau, Baiying Lu, Yanjun CuiForecasting Benchmarks Blood Glucose Forecasting
Department of Computer Science Emory University Atlanta, GA 30322 · Department of Computer Science Dartmouth College Hanover, NH 03755
Discovering Hierarchy-Grounded Domains with Adaptive Granularity for Clinical Domain Generalization
Jun 8, 2025Pengfei Hu, Xiaoxue Han, Fei Wang +1Healthcare Domain Generalization
School of Computing Stevens Institute of Technology Hoboken, New Jersey, United States · Weill Cornell Medicine Cornell University New York, New York, United States
Hierarchical Sparse Bayesian Multitask Learning for Disease Prediction in Pooled Microbiome Studies
Feb 4, 2025Haonan Zhu, Andre R. Goncalves, Camilo Valdes +10Clinical Outcome Prediction Multi-Task Learning
Lawrence Livermore National Laboratory · Electrical and Computer Engineering, University of Michigan
Unveiling the Unborn: Advancing Fetal Health Classification through Machine Learning
Sep 30, 2023Sujith K MandalaMedical Diagnosis Clinical Prediction

Feb 27, 2026J/K move · Enter open · S save

Pretty Good Measurement for Radiomics: A Quantum-Inspired Multi-Class Classifier for Lung Cancer Subtyping and Prostate Cancer Risk Stratification

Giuseppe Sergioli, Carlo Cuccu, Giovanni Pasini, Alessandro Stefano+3

Università degli Studi di Cagliari, Via Is Mirrionis 1, Cagliari, 09123, Italy · Institute of Bioimaging and Complex Biological Systems - National Research Council (IBSBC - CNR), Cefalù, 90015, Italy · National Laboratory of South, National Institute for Nuclear Physics(LNS-INFN), Catania, 95125, Italy

Multiclass Classification Quantum-Inspired ML Clinical Prediction Radiomics Histopathology Image Classification

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We investigate a quantum-inspired approach to supervised multi-class classification based on the Pretty Good Measurement (PGM), viewed as an operator-valued decision rule derived from quantum state discrimination. The method associates each class with an encoded mixed state and performs classification through a single POVM construction, thus providing a genuinely multi-class strategy without reduction to pairwise or one-vs-rest schemes. In this perspective, classification is reformulated as the discrimination of a finite ensemble of class-dependent density operators, with performance governed by the geometry induced by the encoding map and by the overlap structure among classes. To assess the practical scope of this framework, we apply the PGM-based classifier to two biomedical radiomics case studies: histopathological subtyping of non-small-cell lung carcinoma (NSCLC) and prostate cancer (PCa) risk stratification. The evaluation is conducted under protocols aligned with previously reported radiomics studies, enabling direct comparison with established classical baselines. The results show that the PGM-based classifier is consistently competitive and, in several settings, improves upon standard methods. In particular, the method performs especially well in the NSCLC binary and three-class tasks, while remaining competitive in the four-class case, where increased class overlap yields a more demanding discrimination geometry. In the PCa study, the PGM classifier remains close to the strongest ensemble baseline and exhibits clinically relevant sensitivity--specificity trade-offs across feature-selection scenarios.