Article

Expert-integrated automated machine learning uncovers hemodynamic predictors in spinal cord injury

2021-09-28

Abstract excerpt

Automated machine learning (AutoML) is positioned to democratize artificial intelligence (AI) by reducing the amount of human input and ML expertise needed to create prediction models. However, successful translation of ML in biomedicine requires moving beyond optimizing only for prediction accuracy and towards discovering reproducible clinical and biological inferences. Here, we present a model-agnostic framework...

Topics

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

Identifiers and source

Literature Corpus work: f4728ddb-5d12-5bae-8caf-e5c3e549e45a
DOI: 10.1101/2021.09.27.461544

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Expert-integrated automated machine learning uncovers hemodynamic predictors in spinal cord injuryDOI 10.1101/2021.09.27.461544Read

EHR-ML: A generalisable pipeline for reproducible clinical outcomes using electronic health recordsSemantic proximity Read

Combination AI-Machine Learning to Diagnose Pulmonary Hypertension: A Real-World Evidence Cohort StudySemantic proximity Read

Operationalizing Trustworthy AI: A Scalable Framework for Granular Error Analysis and Bias Mitigation in Healthcare ModelsSemantic proximity Read

Generalisability of AI-based scoring systems in the ICU: a systematic review and meta-analysisSemantic proximity Read

Leveraging Expert Knowledge and Causal Structure Learning to Build Parsimonious Models of Acute Brain Dysfunction in the Pediatric Intensive Care Unit (PICU)Semantic proximity Read

Clinician-Informed Feature Engineering Improves Machine Learning Assignment of Molecular Endotypes in the Intensive Care UnitSemantic proximity Read

Explainable Artificial Intelligence in Precision Medicine: Methods, Applications, and ChallengesSemantic proximity Read

Trustworthy personalized treatment selection: causal effect-trees and calibration in perioperative medicineSemantic proximity Read

Automated Real-time Assessment of Intracranial Hemorrhage Detection AI Using an Ensembled Monitoring Model (EMM)Semantic proximity Read

Machine learning in cardiovascular medicine: are we there yet?Semantic proximity Read

Application of concise machine learning to construct accurate and interpretable EHR computable phenotypesSemantic proximity Read

A Reproducible Clinical Decision-Support Suite on MIMIC-IVSemantic proximity Read