SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction

04/09/2025

JALM Talk Podcast

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10:45

Podcast interviews with authors of articles published in The Journal of Applied Laboratory Medicine, a publication of the Association for Diagnostics and Laboratory Medicine.

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SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction

JALM Talk Podcast

D'autres épisodes de "JALM Talk Podcast"

Handling Hemolytic Blood Samples from High-Risk Clinical Areas: A Call to Action

SBC-SHAP: Increasing the Accessibility and Interpretability of Machine Learning Algorithms for Sepsis Prediction

MedPromptExtract (Medical Data Extraction Tool): Anonymization and High-Fidelity Automated Data Extraction Using Natural Language Processing and Prompt Engineering

Rapid Whole-Genome Sequencing as a First-Line Test Is Likely to Significantly Reduce the Cost of Acute Care in a Private Payer System

The 2024 PhD Board-Certified Clinical Chemist Compensation Survey

Fetal Fraction Methodologies and Their Clinical Use: Results of a College of American Pathologists Exercise

Is the 99th Percentile Cutoff Still Relevant? A Single-Center Assessment of Different Thresholds for Diagnosing Antiphospholipid Syndrome

Price Variability of Eight Common Laboratory Tests across All Licensed Tennessee Hospitals

Comparison of 2 Sets of Immunoassays Used in Modified 2-Tiered Testing Algorithms for the Diagnosis of Lyme Disease

High-Sensitivity Cardiac Troponin Assays: From Implementation to Resource Utilization and Cost Effectiveness