Article

GPT-4o and the Quest for Machine Learning Interpretability in ICU Mortality Prediction

2024-08-06

Abstract excerpt

<title>Abstract</title> <p><bold>Background </bold> Clinical utilization of machine learning is hampered by the lack of interpretability inherent in most non-linear black box modeling approaches, reducing trust among clinicians and regulators. Advanced large language models, such as GPT-4o, offer a potential framework for integrating medical knowledge into these models, potentially enhancing their interpretabilit...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: fa4c8763-fc2a-5de1-a4d4-f68f0c2e001e
DOI: 10.21203/rs.3.rs-4816139/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

GPT-4o and the Quest for Machine Learning Interpretability in ICU Mortality PredictionDOI 10.21203/rs.3.rs-4816139/v1Read

Calibrated and Interpretable Machine Learning for ICU Mortality Prediction Using First 24-Hour Clinical DataSemantic proximity Read

Machine Learning Identifies ICU Outcome Predictors in a Multicenter COVID-19 Cohort.Semantic proximity Read

Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infectionSemantic proximity Read

Large-Language-Model Mortality Risk Stratification in the Intensive Care Unit: A Benchmark Against APACHE IISemantic proximity Read

A Hybrid Modeling Framework for Generalizable and Interpretable Predictions of ICU Mortality: Leveraging ICD Codes in a Multi-Hospital Study of Mechanically Ventilated Influenza PatientsSemantic proximity Read

Clinical Risk-Weighted Evaluation of ICU Mortality Prediction Models on MIMIC-IVSemantic proximity Read

Integrating Machine Learning and SHAP for Interpretable Prediction of 28-D ay Mortality in ICU Patients: A Comprehensive Analysis of Initial Physiologic al FeaturesSemantic proximity Read

A Machine Learning-Based Prediction of Hospital Mortality in Mechanically Ventilated ICU PatientsSemantic proximity Read

Development and External Validation of a High-Precision Model for Predicting ICU Admission from Emergency Department TriageSemantic proximity Read

Using Machine Learning and Natural Language Processing in Triage for Prediction of Clinical Disposition in the Emergency DepartmentSemantic proximity Read

Natural Language Processing as a Predictor of Mortality in Intensive Care Unit PatientsSemantic proximity Read

Prediction of 30-Day Mortality for ICU Patients with Sepsis-3Semantic proximity Read