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

4.9.2025

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

Flere episoder fra "JALM Talk Podcast"

Blood Utilization and Waste Following Implementation of Thromboelastography

ADLM Guidance Document on Coagulation Testing in Patients Using Direct Oral Anticoagulants

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