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Đội ngũ Phở
Đọc tiếp →Lâm sàng & Y tế
AI hỗ trợ ra quyết định lâm sàng, tóm tắt bệnh án, giáo dục y khoa và mô hình ngôn ngữ cho chăm sóc sức khoẻ.
92 bài báo trong chủ đề này (ICML 2026).
Bài viết liên quan
★ Spotlight
Lâm sàng & Y tế
ClinTutor-R1: Advancing Scalable and Robust One-to-Many Alignment in Clinical Socratic Education
Zhitao He, Haolin Yang, Zeyu Qin, Yi R. Fung
Vì sao đáng đọc — LLM dạy một-kèm-một thì tốt, nhưng buổi đi buồng dạy nhiều học viên cùng lúc lại là bài toán khác. Cách tiếp cận one-to-many này gần với thực tế đào tạo lâm sàng, và là góc nhìn hữu ích cho ai xây trợ lý giáo dục y khoa.
★ Spotlight
Lâm sàng & Y tế Hệ gen
HypoSpace: A Diagnostic Benchmark for Set-Valued Hypothesis Generation under Underdetermination and Sublinear Coverage Bounds
Tingting Chen, Beibei Lin, Zifeng Yuan, Qiran Zou +4
Many scientific problems are underdetermined: multiple distinct hypotheses are equally consistent with the same observations. In such settings, effective inference requires not…
★ Spotlight
Lâm sàng & Y tế
Listening Through the Noise: Cauchy-Driven Diffusion Bridges for Robust Gastrointestinal Auscultation and Clinical Benchmarking
Dian Ding, Liren Dong, Yu Lu, Juntao Zhou +4
Gastrointestinal (GI) motility assessment via bowel sounds (BS) offers a non-invasive alternative to resource-intensive clinical standards. However, the diagnostic utility of BS…
★ Spotlight
Lâm sàng & Y tế
Seizure-Semiology-Suite($S^3$): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding
Lina Zhang, Tonmoy Monsoor, Peizheng Li, Jiarui Cui +4
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret involuntary, and…
★ Spotlight
Lâm sàng & Y tế
SleepLM: Natural-Language Intelligence for Human Sleep
Zongzhe Xu, Zitao Shuai, Eideen Mozaffari, Ravi Shankar Aysola +2
We present SleepLM, a family of sleep-language foundation models that enable human sleep alignment, interpretation, and interaction with natural language. Despite the critical…
★ Spotlight
Lâm sàng & Y tế
SurvDiff: A Diffusion Model for Generating Synthetic Data in Survival Analysis
Marie Brockschmidt, Maresa Schröder, Stefan Feuerriegel
Survival analysis is a cornerstone of clinical research by modeling time-to-event outcomes such as metastasis, disease relapse, or patient death. Unlike standard tabular data,…
Lâm sàng & Y tế
A Geometric Lens on Physics-Aligned Data Compression
Aleix Segui Ugalde, Wesley Armour
In AI for Science, physics-informed losses are increasingly used to train learned compressors for scientific data, but their rate--distortion implications remain poorly…
Lâm sàng & Y tế
A Regime-Aware Trajectory Prediction Framework for 1000+ Systems Biology Models
Heng Rao, Jason Zipeng Zhang, Yu Gu, Zhenghao Liu +4
Predicting long-horizon trajectories of biological dynamical systems remains challenging due to substantial system heterogeneity. Most existing machine learning approaches are…
Lâm sàng & Y tế
Agentic Framework for Epidemiological Modeling
Rituparna Datta, Zihan Guan, Baltazar Espinoza, Yiqi Su +4
Epidemic modeling is essential for public health planning, yet traditional approaches rely on fixed model classes that require manual redesign as pathogens, policies, and scenario…
Lâm sàng & Y tế
Asymmetric Contrastive Objectives for Efficient Phenotypic Screening
Luke Nightingale, Joseph Tuersley, Scott Warchal, Andrea Cairoli +4
Phenotypic screening experiments produce many microscope images of cells under diverse perturbations, with biologically significant responses often subtle or difficult to identify…
Lâm sàng & Y tế
Automatic Construction of Clinical Scoring Systems with LLM Agents
Silas Ruhrberg Estévez, Christopher Chiu, Mihaela van der Schaar
Modern clinical practice relies on evidence-based guidelines implemented as compact scoring systems composed of a small number of interpretable decision rules. While…
Lâm sàng & Y tế
Benchmarking the Scientific Mind: A Pathology-Derived Biomedical VQA Benchmark for Complex Scientific Reasoning
Ziyu Zhao, Yiyang Liu, Yajiao Wang, Xiaotao Wang +4
Despite progress of Multimodal Large Language Models (MLLMs) in biomedical visual question answering (VQA), existing benchmarks provide limited assessment of their scientific…
Đơn bào Lâm sàng & Y tế
Beyond Accuracy: Latent Perturbations for Cognitive-Aware Diagnosis
Yuting Yan, Yinghao Fu, Wendi Ren, Haozhou Gao +1
Diagnosing rare diseases remains a persistent challenge, often hindered by cognitive anchoring: once clinicians settle on a common diagnosis, they often discount alternative…
Lâm sàng & Y tế
BioAgent Bench: An AI Agent Evaluation Suite for Bioinformatics
Dionizije Fa, Marko Čuljak, Bruno Pandža, Mateo Čupić
We introduce BioAgent Bench, an evaluation suite designed for measuring the performance and robustness of AI agents in common bioinformatics tasks. The suite consists of manually…
Lâm sàng & Y tế
BioProBench: A Corpus and Benchmark for Biological Protocol Reasoning in Autonomous Science
Yuyang Liu, Liuzhenghao Lv, Xiancheng Zhang, Jingya Wang +2
The realization of autonomous scientific experimentation is currently limited by LLMs' struggle to grasp the strict procedural logic and accuracy required by biological protocols.…
Lâm sàng & Y tế
Bridging Dynamics and Data: A Unified Diffusion Framework for Mechanistically-Informed Epidemic Forecasting
Guanghui Min, Tianhao Huang, Ke Wan, Qi R. Wang +1
Reliable epidemic forecasting is critical for public health decision-making yet remains challenging due to data sparsity and the non-stationary nature of disease dynamics. While…
Lâm sàng & Y tế Đơn bào
CellBRIDGE: Learning Cellular Trajectories via Interaction-Aware Alignment
Silas Ruhrberg Estévez, Nicolas Huynh, Tennison Liu, Roderik M. Kortlever +3
Inferring dynamics from population snapshots is a fundamental challenge in machine learning and biology. In scRNA-sequencing (scRNA-seq), destructive measurements preclude direct…
Lâm sàng & Y tế
CLINIC : Evaluating Multilingual Trustworthiness in Language Models for Healthcare
Akash Ghosh, Srivarshinee Sridhar, Raghav Kaushik Ravi, Muhsin Muhsin +2
Integrating language models (LMs) in healthcare systems holds great promise for improving medical workflows and decision-making. However, a critical barrier to their global…
Lâm sàng & Y tế
DC-W2S: Dual-Consensus Weak-to-Strong Training for Reliable Process Reward Modeling in Biological Reasoning
Chi-Min Chan, Ehsan Hajiramezanali, Xiner Li, Edward De Brouwer +4
In scientific reasoning tasks, the veracity of the reasoning process is as critical as the final outcome. While Process Reward Models (PRMs) offer a solution to the coarse-grained…
Lâm sàng & Y tế Chẩn đoán hình ảnh
Deep Learning for BioImaging: What Are We Really Learning?
Ivan Svatko, Maxime Sanchez, Ihab Bendidi, Gilles Cottrell +1
Representation learning has driven major advances in natural image analysis by enabling models to acquire high-level semantic features. In microscopy imaging, however, it remains…
Lâm sàng & Y tế
Deliberate Evolution: Agentic Reasoning for Sample-Efficient Symbolic Regression with LLMs
Xinyu Pang, Zhanke Zhou, Xuan Li, Fangrui Lv +4
Symbolic regression (SR) discovers compact mathematical expressions from data, yet recent LLM-based evolutionary methods remain sample-inefficient because they rely mainly on…
Lâm sàng & Y tế
Discontinuous Galerkin Neural Operator for Pathology Defocus Deblurring
Shaoqing Duan, Haofei Song, Xintian Mao, Qingli Li +1
Defocus deblurring in pathological microscopy remains challenging due to the spatially varying and locally discontinuous nature of optical blur induced by a position-dependent…
Lâm sàng & Y tế
Disease-Centric Vision-Language Pretraining with Hybrid Visual Encoding for 3D Computed Tomography
Bowen Shi, Weiwei Cao, Ruifeng Yuan, Wanxing Chang +4
Vision–language pre-training (VLP) holds great promise for general-purpose medical AI by leveraging radiology reports as rich textual supervision, yet existing methods struggle…
Lâm sàng & Y tế
DIYHealth Suite: Dataset, Model, and Benchmark for Health Management at Home
Changshuo Liu, Wu Junran, Zhongle Xie, Wenqiao Zhang +4
Generative AI is reshaping healthcare, yet most existing advances rely on hospital-grade devices, which limits their accessibility and potential for health management outside…
Chẩn đoán hình ảnh Lâm sàng & Y tế
DPsurv: Dual-Prototype Evidential Fusion for Uncertainty-Aware and Interpretable Whole Slide Image Survival Prediction
Yucheng Xing, Ling Huang, Jingying Ma, Ruping Hong +4
Whole-slide images (WSIs) are widely used for cancer survival analysis because of their comprehensive histopathological information at both cellular and tissue levels, enabling…
Lâm sàng & Y tế
DSENet: A Novel Dual-Stream Enhancement Network for Multi-Scale Non-Stationary Time Series Forecasting
Yuhan Wang, Yuanyuan Zou, Jie Cheng, Bin Dai +1
Accurately capturing local variations in long series has always been one of the most challenging problems in time-series forecasting especially in medical signals, where local…
Lâm sàng & Y tế
Dynamic Decision Learning: Test-Time Evolution for Abnormality Grounding in Rare Diseases
Jun Li, Mingxuan Liu, Jiazhen Pan, Che Liu +3
Clinical abnormality grounding for rare diseases is often hindered by data scarcity, rendering supervised fine-tuning infeasible and single-pass inference highly unstable. Thus,…
Lâm sàng & Y tế
ECG-R1: Protocol-Guided and Modality-Agnostic MLLM for Reliable ECG Interpretation
Jiarui Jin, Haoyu Wang, Xingliang Wu, Xiaocheng Fang +4
Electrocardiography (ECG) serves as an indispensable diagnostic tool in clinical practice, yet existing multimodal large language models (MLLMs) remain unreliable for ECG…
Lâm sàng & Y tế Thần kinh & Não bộ
EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation and Diagnostic Analyses of EEG Foundation Models
Wei Xiong, Jiangtong Li, Jie Li, Kun Zhu +1
Electroencephalography foundation models (EEG-FMs) have advanced brain signal analysis, but the lack of standardized evaluation benchmarks impedes model comparison and scientific…
Lâm sàng & Y tế Đơn bào Hệ gen
Effects of Structural Reward Shaping on Biophysical Properties in RL-Trained Plasmid Generators
McClain Thiel, Angus G. Cunningham, Chris P Barnes
We compare the efficacy and distributional effects of supervised fine-tuning (SFT) and reinforcement learning (RL) post-training for PlasmidGPT, a foundation model for…
Lâm sàng & Y tế
Evidential Reasoning Advances Interpretable Real-World Disease Screening
Chenyu Lian, Hong-Yu Zhou, Jing Qin
Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical images suffer from limited…
Lâm sàng & Y tế
Expert-guided Clinical Text Augmentation via Query-Based Model Collaboration
Dongkyu Cho, Miao Zhang, Gregory D Lyng, Rumi Chunara
Data augmentation is a widely used strategy to improve model robustness and generalization by enriching training datasets with synthetic examples. While large language models…
Lâm sàng & Y tế
Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
Pengfei Hu, Chang Lu, Feifan Liu, Yue Ning
Deep learning models for clinical event prediction on electronic health records (EHR) often suffer performance degradation when deployed under different data distributions. While…
Chẩn đoán hình ảnh Lâm sàng & Y tế
FACT: Fuzzy Alignment with Comorbidity Topology for Reliable Multi-Label Medical Image Diagnosis
Yingyu Chen, Yongqiang Huang, Yang Qin, Ziyuan Yang +3
In clinical practice, patients often present with multiple co-occurring diseases, yet most existing Multi-Label-Diagnosis (MLD) methods treat diagnosis as a rigid discriminative…
Lâm sàng & Y tế
FlowCloud: Learning Continuous Spatiotemporal Dynamics from Unpaired Sparse Point Cloud Snapshots
Yinbo Liu, Keyang Ye, Wenshan Sun, Handi Gao +1
Reconstructing unified continuous dynamics from sparse, non-contiguous, and unpaired point cloud snapshots remains a fundamental challenge in spatiotemporal analysis for computer…
Lâm sàng & Y tế
From Conflict to Consensus: Boosting Medical Reasoning via Multi-Round Agentic RAG
Wenhao Wu, Zhentao Tang, Yafu Li, Shixiong Kai +4
Large Language Models (LLMs) exhibit high reasoning capacity in medical question-answering, but their tendency to produce hallucinations and outdated knowledge poses critical…
Lâm sàng & Y tế
From Knowledge to Inference: Formalizing Specialized Public Health Reasoning on GlobalHealthAtlas
Zhaokun Yan, Shan Xu, Wuzheng Dong, Zhaohan Liu +4
Public health reasoning requires population level inference grounded in scientific evidence, expert consensus, and safety constraints. However, it remains underexplored as a…
Lâm sàng & Y tế
From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction
Mingcheng Zhu, Zhiyao Luo, Yu Liu, Tingting Zhu
By processing electronic health records (EHRs) as natural language sequences, large language models (LLMs) have shown potential in clinical prediction tasks such as mortality…
Lâm sàng & Y tế
FunCQNet: A Functional Censored Quantile Neural Network for Predicting Long-Term Post-Transplant Kidney Survival
Jiaqi Men, Hua Liu, Yiming Tang, Jinhong You +2
Accurate survival prediction in kidney transplantation is critical yet challenging due to the complex interplay between functional biomarkers and patient characteristics under…
Lâm sàng & Y tế
GLEAN: Guideline-Grounded Evidence Accumulation for High-Stakes Agent Verification
Yichi Zhang, Nabeel Seedat, Yinpeng Dong, Peng Cui +2
As LLM-powered agents have been used for high-stakes decision-making, such as clinical diagnosis, it becomes critical to develop reliable verification of their decisions to…
Lâm sàng & Y tế Đơn bào
HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference
Zelin Zang, WenZhe Li, Yongjie Xu, Chang Yu +4
In single-cell research, tracing and analyzing high-throughput single-cell differentiation trajectories is crucial for understanding biological processes. Key to this is the…
Lâm sàng & Y tế
HEARTS: Benchmarking LLM Reasoning on Health Time Series
Sirui Li, Shuhan Xiao, Mihir Joshi, Ahmed Metwally +3
The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing benchmarks cover only a small set of…
Lâm sàng & Y tế
How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting
Yiqi Su, Ray Lee, Jiaming Cui, Naren Ramakrishnan
Epidemiological forecasting from surveillance data is a hard problem and hybridizing mechanistic compartmental models with neural models is a natural direction. The mechanistic…
Lâm sàng & Y tế
How Should Transformers Encode Numeric Values in Electronic Health Records?
Maria Elkjær Montgomery, Christian Igel, Mikkel Fruelund Odgaard, Martin Sillesen +1
How do we encode numeric values in transformer-based sequence processing, particularly in electronic health record (EHR) data? We systematically compare discrete, continuous, and…
Lâm sàng & Y tế
HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis
Shuo Tang, Jiadong Zhang, Gengxian Zhou, Qizhao Jin +4
While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable challenge. This gap exists…
Lâm sàng & Y tế Miễn dịch
iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
Yang Song, Yixuan Zhang, Lingfa Meng, Tongyuan Hu +4
Parameter-efficient adaptation has made LLMs practical for domain prediction, but standard LoRA still relies on a static low-rank update and does not expose the latent…
Lâm sàng & Y tế
InfiMed-ORBIT: Aligning LLMs on Open-Ended Complex Tasks via Rubric-Based Incremental Training
Pengkai Wang, Pengwei Liu, Qi Zuo, Zhijie Sang +2
Reinforcement learning (RL) has powered many recent breakthroughs in large language models (LLMs), especially for tasks where rewards can be computed automatically, such as code…
Lâm sàng & Y tế
Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
Evgeny Saveliev, Samuel Holt, Nabeel Seedat, David L. Bentley +2
Large Language Models (LLMs) offer a promising avenue for scientific discovery, yet their application to symbolic regression is often constrained by inefficient search strategies…
Lâm sàng & Y tế Hệ gen
Interpretability Driven Evolutionary Approach for the Design of Biological Sequences
Akash Pandey, Wei Chen, Sinan Keten
Designing biological sequences such as proteins and DNA for desired properties is challenging due to vast search spaces and limited wet lab evaluation budgets. Current…
Lâm sàng & Y tế
Learning Fingerprints for Medical Time Series with Redundancy-Constrained Information Maximization
Huayu Li, ZhengXiao He, Xiwen Chen, Jingjing Wang +3
Learning meaningful representations from medical time series (MedTS), such as ECG or EEG signals, is a critical challenge. These signals are often high-dimensional,…
Lâm sàng & Y tế
Learning Treatment Allocations with Risk Control Under Partial Identifiability
Sofia Ek, Dave Zachariah
Learning beneficial treatment allocations for a patient population is an important problem in precision medicine. For such allocations, a certain proportion of treated patients…
Lâm sàng & Y tế
LLM-Guided Diagnostic Evidence Alignment for Medical Vision–Language Pretraining under Limited Pairing
Huimin Yan, Liang Bai, Xian Yang, Long Chen
Most existing CLIP-style medical vision--language pretraining methods rely on global or local alignment with substantial paired data. However, global alignment is easily dominated…
Lâm sàng & Y tế
M-IDoL: Information Decomposition for Modality-Specific and Diverse Representation Learning in Medical Foundation Model
Yihang Liu, Longzhen Yang, Jiaxiong Yang, Ying Wen +2
Medical foundation models (MFMs) aim to learn universal representations from multimodal medical images that can generalize effectively to diverse downstream clinical tasks.…
Lâm sàng & Y tế
Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning
Ziquan Wei, Tingting Dan, Guorong Wu
Despite the central role of sensor-derived measurements such as imaging traits and plasma biomarkers in biomedical research and clinical practice, existing generative models for…
Lâm sàng & Y tế
Med-Scout: Curing MLLMs' Geometric Blindness in Medical Perception via Geometry-Aware RL Post-Training
Anglin Liu, Ruichao Chen, Yi Lu, Hongxia Xu +1
Despite recent Multimodal Large Language Models (MLLMs)' linguistic prowess in medical diagnosis, we find even state-of-the-art MLLMs suffer from a critical perceptual deficit:…
Lâm sàng & Y tế
MEDA: Medical-Oriented Activation Editing for Hallucination Mitigation in Medical Large Vision-Language Model
Tianbo Wang, Yuqing Ma, Lingyan Meng, Zhange Zhang +4
Medical Large Vision-Language Models (Med-LVLMs) suffer from severe hallucinations, posing critical safety risks in clinical deployment. Editing LVLM activations has shown promise…
Lâm sàng & Y tế
MedCoG: Maximizing LLM Inference Density in Medical Reasoning via Meta-Cognitive Regulation
Yu Zhao, Hao Guan, Yongcheng Jing, Ying Zhang +1
Large Language Models (LLMs) have shown strong potential in complex medical reasoning yet face diminishing gains under inference scaling laws. While existing studies augment LLMs…
Lâm sàng & Y tế
MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio
Harshit Rajgarhia, Shuubham Ojha, Asif Shaik, Akhil Pothanapalli +3
Medical audio data is difficult to collect due to privacy regulations and high annotation costs arising from domain expertise. Thus, existing benchmarks tend to underrepresent…
Lâm sàng & Y tế
MedREK: Retrieval-Based Editing for Medical LLMs with Key-Aware Prompts
Shujun Xia, Haokun Lin, Yichen Wu, Yinan Zhou +4
Large Language Models (LLMs) hold great promise for healthcare applications, but fast-changing medical knowledge can quickly make their outputs outdated or inaccurate, limiting…
Lâm sàng & Y tế
MedScope: Incentivizing "Think with Videos" for Clinical Reasoning via Coarse-to-Fine Tool Calling
Wenjie Li, Yujie Zhang, Haoran Sun, Xingqi He +4
Long-form clinical videos are central to visual evidence-based decision-making, with growing importance for applications such as surgical robotics and related settings. However,…
Lâm sàng & Y tế
MedSIGHT: Towards Grounded Visual Comprehension in Medical Large Vision-Language Models
Aofei Chang, Le Huang, Alex James Boyd, Parminder Bhatia +3
Medical large vision-language models (Med-LVLMs) have recently achieved remarkable progress in vision–language comprehension and medical image segmentation. However, existing…
Lâm sàng & Y tế
Modeling Attributional Style at Scale: A Dataset and Analysis for Psychological Attribution Assessment and Reframing
Qiang Zhou, Hanzhen Zhu, Pan Wang, Rui Tu +4
According to the reformulated Learned Helplessness theory, repeated exposure to uncontrollable negative events can foster a depressogenic attributional style—increasing…
Lâm sàng & Y tế
Modeling Long-Tail Relations in the Operating Room via In-Context Multimodal Learning
Boqiang Xu, Wei Zhang, Ding Ma, Jian Liang +2
Operating room (OR) scene graph generation (SGG) enables holistic modeling of OR domains by encoding interactions among medical staff, tools, and equipment as triplet-based…
Lâm sàng & Y tế
MoRGen: Mixture-of-Resolutions Generative Forecasting for Irregularly Sampled Medical Time-Series Data
Nassim Oufattole, Matthew B.A. McDermott, Collin Stultz
Autoregressive generative models for irregularly sampled clinical time-series data are increasingly used for zero-shot risk forecasting. Prior work typically adopts a single…
Lâm sàng & Y tế
Near-Optimal Dynamic Matching via Coarsening with Application to Heart Transplantation
Itai Zilberstein, Ioannis Anagnostides, Zachary W. Sollie, Arman Kilic +1
Online matching has been a mainstay in domains such as Internet advertising and organ allocation, but practical algorithms often lack strong theoretical guarantees. We take an…
Lâm sàng & Y tế
No Data? No Problem: Robust Vision-Tabular Learning with Missing Values
Marta Hasny, Laura Alexandra Daza, Keno Bressem, Maxime Di Folco +1
Large-scale medical biobanks provide imaging data complemented by extensive tabular information, such as clinical measurements or demographics. However, this abundance of tabular…
Lâm sàng & Y tế
Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification
Shaohao Rui, Kaitao Chen, Weijie Ma, Xiaosong Wang
Extended Chain-of-Thought (CoT) reasoning has significantly bolstered the capabilities of medical large language models (LLMs). However, current models exhibit static…
Chẩn đoán hình ảnh Lâm sàng & Y tế
ORBIT: A Prognostic World Model for Ocular Reasoning Based on Imagined Trajectories
Jiangtao Yan, Yanlin Qu, Yansheng Qiu, Shujian Gao +4
The longitudinal management of blinding fundus diseases constitutes a Partially Observable Markov Decision Process (POMDP) necessitating a critical precision-risk trade-off…
Lâm sàng & Y tế
OSF: On Pre-training and Scaling of Sleep Foundation Models
Zitao Shuai, Zongzhe Xu, David Yang, Wei Wang +1
Polysomnography (PSG) provides the gold standard for sleep assessment but suffers from substantial heterogeneity across recording devices and cohorts. There have been growing…
Lâm sàng & Y tế
PathwayLLM: Explainable Clinical Trajectory Modeling with Structured Pathways for Sepsis Prediction
Zhengqiu Yu, Yueping Ding, Xiangrong Liu
Patient-level sepsis prediction requires models that track clinical deterioration over time and integrate heterogeneous structured evidence from electronic health records. We…
Lâm sàng & Y tế Protein
PPI Candidate Ranking: Large-Scale Evaluation of a Domain Knowledge–Guided Pipeline
Maria Emilia Russo, Federico Di Valerio, Alessia Borghini, Alessio Ragno +1
Computational approaches have become central to Protein–Protein Interaction (PPI) research, complementing experimental techniques that remain costly and incomplete. While modern…
Lâm sàng & Y tế
Process Reward Agents for Steering Knowledge-Intensive Reasoning
Jiwoong Sohn, Tomasz Sternal, Kenneth Styppa, Torsten Hoefler +1
Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or code, evaluating step correctness may require…
Lâm sàng & Y tế
Quantifying the Generalization Gap in Seizure Detection: A Large-Scale Empirical Benchmark via the SzCORE Challenge
Jonathan Dan, Amirhossein Shahbazinia, Christodoulos Kechris, David Atienza
Reliable automatic seizure detection from long-term electroencephalogram recordings (EEG) remains an unsolved challenge, as current models often fail to generalize across patients…
Lâm sàng & Y tế Thần kinh & Não bộ
RECTOR: Masked Region-Channel-Temporal Modeling for Affective and Cognitive Representation Learning
Jinhan Liu, Mahsa Shoaran
Affective and cognitive disorders manifest as distributed, time-varying brain network dynamics across regions, channels, and time, challenging robust representation learning from…
Lâm sàng & Y tế
Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis
Tianwei Lin, Zhongwei Qiu, Jie Cao, Jiang Liu +4
Medical vision-language models (VLMs) have rapidly advanced as general-purpose multimodal assistants, yet their deployment in 3D Computed Tomography (CT) analysis remains…
Lâm sàng & Y tế
Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)
Marius Knorr, Robert Müller, Jan Peter Bremer, Nils Schweingruber
Fast Healthcare Interoperability Resources (FHIR) is the dominant standard for interoperable exchange of healthcare data. In FHIR, electronic health records form a directed graph…
Lâm sàng & Y tế
Residual-Guided Multi-Resolution Refinement of Foundation Models: A Case Study in Drought Forecasting
Wentao Gao, Jiuyong Li, Lin Liu, Thuc Duy Le +3
Regional climate prediction presents unique challenges for time series foundation models, which typically process temporal patterns through single-pass inference. Expert…
Lâm sàng & Y tế
Salus: Strategic Diagnostic Testing for Complex Diagnosis via Multi-Agent Reinforcement Learning
Shuohao Gao, Xuanzhong Chen, Lingxiao Luo, Zilin Ding +3
Diagnosing complex diseases is inherently a sequential and iterative medical investigation process, in which a clinician strategically requests multiple rounds of diagnostic tests…
Lâm sàng & Y tế
SGERA: Stein-Guided ECG-Report Alignment for ECG Representation Learning
Jian Chen, Yipeng Du, Wenhao Yuan, Shuai Wang +4
Electrocardiogram (ECG) representation learning via ECG-report alignment is often hindered by the inherent structural and statistical divergence between signals and natural…
Lâm sàng & Y tế
Small Agent Group is the Future of Digital Health
Yuqiao Meng, Luoxi Tang, Dazheng Zhang, Rafael Brens +4
The rapid adoption of large language models (LLMs) in digital health has been driven by a "scaling-first" philosophy, i.e., the assumption that clinical intelligence increases…
Lâm sàng & Y tế Đơn bào
SPATIA: Multimodal Generation and Prediction of Spatial Cell Phenotypes
Zhenglun Kong, Mufan Qiu, John Boesen, xiang lin +4
Understanding how cellular morphology, gene expression, and spatial context jointly shape tissue function is a central challenge in biology. Image-based spatial transcriptomics…
Lâm sàng & Y tế
Spherical Procrustes Alignment for Reliable Medical Audio Diagnosis
Ying Wang, Guoheng Huang, Chan-Tong Lam, Xiaochen Yuan
Reliable medical audio diagnosis requires models that are both accurate and honest about their uncertainty. However, fine-tuned models on small, imbalanced datasets often become…
Lâm sàng & Y tế
SPR-RAFT: Parameter-Efficient Regression-Aware Fine-Tuning for Biomedical LLM Regression
Yuanlin Yang, Chenhui Li, Xuhao Guo, Anqi Zhang +2
Biomedical regression tasks require predicting continuous targets from heterogeneous and unstructured evidence. While Large Language Models (LLMs) provide a robust interface for…
Lâm sàng & Y tế
Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls
Ana Sanchez-Fernandez, Thomas Pinetz, Werner Zellinger, Günter Klambauer
Biomedical imaging data presents enormous potential for deep learning models to predict invaluable properties, such as diseases and drug effects. However, unavoidable alterations…
Lâm sàng & Y tế Thần kinh & Não bộ
Structured Multi-modal Graph Disentanglement for Psychiatric Diagnosis
Hongyu Shi, Kaizhong Zheng, Wensheng Zhai, Shuai Jiang +2
Multi-modal neuroimaging-based psychiatric diagnosis must integrate cross-modal agreement with modality-specific complementarity, yet in real multi-site cohorts these signals are…
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STT-LLM: Structural-Temporal Tokenization for Adapting LLMs to Longitudinal Clinical Profiles
Maxx Richard Rahman, Mostafa Hammouda, Wolfgang Maass
Large Language Models have shown strong generalization across natural language tasks but remain underexplored for longitudinal clinical profiles. In sports anti-doping, biological…
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SynerMedGen: Synergizing Medical Multimodal Understanding with Generation via Task Alignment
Weiren zhao, DONG Yi, Cheng Chen
Unifying multimodal understanding and generation is a compelling frontier that is beginning to emerge in the medical field. However, the limited existing unified medical models…
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Time-Conditioned Foreseeing: An EHR-Specific Foundation Model for Irregular Dynamics and Calendrical Time
Bong Gyun Kang, Junyong Ahn, Hyeongrok Han, Sungroh Yoon
Electronic Health Records (EHRs) possess unique characteristics distinct from natural language, yet existing EHR foundation models often rely on suboptimal NLP-based approaches.…
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Token-Sparse Medical Multimodal Reasoning via Dual-Stream Reinforcement Learning
Kaitao Chen, Weiqian Zhao, Jiamin Wu, Qihao Zheng +4
Vision-language models (VLMs) combining reinforcement learning (RL) ignite remarkable progress in multimodal reasoning, yet still struggle with medical images, which typically…
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Tri-Scale Neural ODEs for Continuous Multi-Omics Disease Modeling
Shohaib Shaffiey, Massimiliano Pierobon
The fields of AI-based disease fingerprinting, drug discovery and repurposing are currently among the emerging frontiers of machine learning applied to medicine. One major…
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UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis
Junzhi Ning, Wei Li, Cheng Tang, Jiashi Lin +4
Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central to medical AI. Most existing…
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Unlocking Cross-Modal Biosignal Synthesis: A Temporally-Aware VAE-Diffusion Model
Chenyang Xu, Dezhen Wang, Hao Wang
Synthesizing authentic phonocardiograms (PCG) from ubiquitous electrocardiograms (ECG) is a critical task for accessible cardiac monitoring. Existing generative models, however,…
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