paper-with-me

Mortality Prediction

2개 벤치마크 · 논문 236편 · 이 태스크의 논문 보기 →

Benchmarks

MIMIC-III

결과 39개

Most implemented

Papers

MMTClinic: Multimodal, Multilingual Time Series Question Answering and Reasoning Benchmark for Clinical Domain

2026-09-04 · Sourav Malakar, Harshit Nigam, Akash Ghosh, Sriparna Saha 외 arxiv

Time-series data in clinical settings is crucial for capturing dynamic changes in a patient's health over time, enabling timely diagnosis, personalized treatment, and early detection of critical events. However, the deve…

Mortality PredictionQuestion Answering

Making Clinical Language Models Auditable: Concept-Guided Fine-Tuning for Robust Prediction

2026-08-27 · Jin Mu, Guanhua Chen arxiv

Clinical language models can achieve strong in-hospital accuracy yet fail under deployment shifts because they exploit note-specific artifacts (e.g., templates, separators, boilerplate) that do not reflect patient state.…

Mortality PredictionText Classification

QuanTiMedAI: Quantum-Enhanced Time-Series Model guided by Agentic AI for Cardiac Arrest Mortality Prediction

2026-08-06 · Mutasim Fuad Sarker, Adiba Rahman Namira, Wafa Binte Alam, Md Adnan Arefeen 외 arxiv

Cardiac arrest remains one of the most lethal conditions encountered in intensive care units. Despite the growing availability of electronic health record data, existing mortality prediction studies in this population la…

Mortality Prediction

Learning the Pareto Frontier of Predictive Models under Distribution Shift

2026-08-01 · Yiming Dong, Jiwei Zhao, Yang Young Lu arxiv

Modern machine learning pipelines increasingly rely on reusing pretrained and foundation models across downstream tasks. These pretrained models can differ not only in performance but also in how they can be used: some o…

Mortality PredictionDomain Adaptation

A Personalized Computational Framework for Assessing the Sufficiency of Partially Observed Data in Healthcare AI models

2026-07-10 · Qingchu Jin, Felistas Mazhude, Jamie B. Rabb, Robert S. Kramer 외 arxiv

Achieving early and timely diagnosis and treatment for disease is a major challenge. Recent applications of machine learning (ML) algorithms trained on patient data have shown promise in many different settings for predi…

Mortality Prediction

Fusion is not one-size-fits-all: Cross-Modal Representation Alignment for Time-to-Event Modeling

2026-06-13 · Zhemin Zhang, Weijie Chen, David Le, Amara Tariq 외 arxiv

Accurate time-to-event (TTE) prediction from multimodal clinical data remains challenging due to modality imbalance and distribution shift. We introduce a foundation model-driven framework for cross-modal representation …

Mortality Prediction

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