Papers with Code 아카이브

Mortality Prediction

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하위 태스크: 1
평가표: 2
보존된 평가 기록: 16

<span style="color:grey; opacity: 0.6">( Image credit: Early hospital mortality prediction using vital signals )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/mlds-lab/interp-net

공식 코드

Interpolation-Prediction Networks for Irregularly Sampled Time Series

https://github.com/mnaylor5/quantifying-explainability

공식 코드

Quantifying Explainability in NLP and Analyzing Algorithms for Performance-Explainability Tradeoff

https://github.com/mohammad-gh009/large-language-models-vs-classical-machine-learning

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Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data

https://github.com/mostafaalishahi/eICU_Benchmark

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Benchmarking machine learning models on multi-centre eICU critical care dataset

https://github.com/mostafaalishahi/eICU_Benchmark_updated

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Benchmarking machine learning models on multi-centre eICU critical care dataset

https://github.com/mriosb08/dkl-temporal-shift

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Deep Kernel Learning for Mortality Prediction in the Face of Temporal Shift

https://github.com/muhangtian/gfr-experiments

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Fast and Interpretable Mortality Risk Scores for Critical Care Patients

https://github.com/musaelab/mspb

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MSPB: a longitudinal multi-sensor dataset with phenotypic trait measurements from honey bees

https://github.com/nliulab/FedScore

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FedScore: A privacy-preserving framework for federated scoring system development

https://github.com/ny1031/tm-hgnn

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Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learning

https://github.com/nyuad-cai/medfuse

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MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images

https://github.com/psudslab/FEDMEKI

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FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection

https://github.com/randlbem/early_icu_mortality_prediction_with_deep_fl

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Early prediction of the risk of ICU mortality with Deep Federated Learning

https://github.com/ratschlab/HIRID-ICU-Benchmark

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HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data

https://github.com/rpidial/chexfound

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Chest X-ray Foundation Model with Global and Local Representations Integration

https://github.com/scxsunchenxi/ccts

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Continuous Diagnosis and Prognosis by Controlling the Update Process of Deep Neural Networks

https://github.com/sdamirsa/tehran_covid_cohort

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Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data

https://github.com/sindhura97/STraTS

공식 코드

Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series

https://github.com/stanfordmlgroup/cdr-mimic

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Countdown Regression: Sharp and Calibrated Survival Predictions

https://github.com/starmpcc/remed

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General-Purpose Retrieval-Enhanced Medical Prediction Model Using Near-Infinite History

https://github.com/stefanhgm/ehrshot-benchmark

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Large Language Models are Powerful Electronic Health Record Encoders

https://github.com/swiergarst/association_analysis

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MRI-based and metabolomics-based age scores act synergetically for mortality prediction shown by multi-cohort federated learning

https://github.com/tanlab/mimic-iii-clinical-drug-representations

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Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions

https://github.com/tdgfrost/td-icu-mortality

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Robust Real-Time Mortality Prediction in the Intensive Care Unit using Temporal Difference Learning

https://github.com/theonesp/multimodal_mortality_covid

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Developing and validating multi-modal models for mortality prediction in COVID-19 patients: a multi-center retrospective study

https://github.com/wangtongada/MARS

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Interpretable Patient Mortality Prediction with Multi-value Rule Sets

https://github.com/xiaoleihuang/useremb_explainable

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Enriching Unsupervised User Embedding via Medical Concepts

https://github.com/yerevann/mimic3-benchmarks

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Multitask learning and benchmarking with clinical time series data

https://github.com/yhzhu99/covid-ehr-benchmarks

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A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care

https://github.com/yhzhu99/pyehr

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A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care

https://github.com/yhzhu99/pyehr-playground

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A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care

https://github.com/yxs/MedLens

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MedLens: Improve Mortality Prediction Via Medical Signs Selecting and Regression

https://github.com/zavareh89/MITST

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Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-Series

https://github.com/zheng321/deep-reinforcement-learning-for-cost-effective-medical-diagnosis

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Deep Reinforcement Learning for Cost-Effective Medical Diagnosis

https://github.com/zidixiu/VIE

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Variational Disentanglement for Rare Event Modeling

https://github.com/zzzace2000/autodiagnosis

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Dynamic Measurement Scheduling for Event Forecasting using Deep RL

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