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Clinical Information and Decision Making (2149) Decision Support for Health Professionals (1692) Machine Learning (2306) Artificial Intelligence (2458)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50369, first published .
Scientist in VR headset and hazmat suit in a lab with brain scan on monitor

Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study

Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study

Authors of this article:

Meicheng Yang1 Author Orcid Image ;   Hui Chen2 Author Orcid Image ;   Wenhan Hu2 Author Orcid Image ;   Massimo Mischi3 Author Orcid Image ;   Caifeng Shan4, 5 Author Orcid Image ;   Jianqing Li1, 6 Author Orcid Image ;   Xi Long3 Author Orcid Image ;   Chengyu Liu1 Author Orcid Image
Article Authors Cited by (15) Tweetations (3) Metrics

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  1. Herrera F. Reflections and attentiveness on eXplainable Artificial Intelligence (XAI). The journey ahead from criticisms to human–AI collaboration. Information Fusion 2025;121:103133 View
  2. Wang Y, Kashyap R, Zhang P, Meng Q, Zhang Z. Editorial: Clinical application of artificial intelligence in emergency and critical care medicine, volume V. Frontiers in Medicine 2025;12 View
  3. She X, Zhao X, Yang H, Cui X, Chen R. Development and temporal validation of a nomogram for predicting ICU 28-day mortality in middle-aged and elderly sepsis patients: An eICU database study. PLOS One 2025;20(7):e0328701 View
  4. Riahi A, Yazdani M, Eshraghi R, Houyeh M, Bahrami A, Khoshdooz S, Amini M, Behzadi E, Khalaji A, Moeini Taba S, Hashemian S, Plackett T. Exploring the Potentials of Artificial Intelligence in Sepsis Management in the Intensive Care Unit. Critical Care Research and Practice 2025;2025(1) View
  5. Hao X, Wang Y, Li K, Zhu T, Herasevich V. Applying machine learning for perioperative adverse event prediction: a narrative review toward better clinical efficacy and usability. Anesthesiology and Perioperative Science 2025;3(4) View
  6. Lian X, Liu Y, Liu X, Tao W, Cao B, Fu B, Yang F, Bao Y, Yang K. Artificial intelligence for mortality risk stratification in septic shock: A systematic review and meta-analysis. International Journal of Medical Informatics 2026;207:106197 View
  7. Corvelo Benz N, Miranda L, Chen D, Sattler J, Borgwardt K. Conformal Prediction with Knowledge Graphs for Reliable Antimicrobial Resistance Detection with MALDI-TOF Mass Spectra. Journal of Computational Biology 2026;33(1):19 View
  8. Bai L, Su J. Artificial Intelligence Virtual Organoids (AIVOs). Bioactive Materials 2026;59:45 View
  9. Cheungpasitporn W, Thongprayoon C, Kashani K. Artificial Intelligence in Critical Care Nephrology. Kidney360 2026;7(3):664 View
  10. Maciej Kokoszka , Michalina Chodór , Julia Maria Kuczkowska , Judyta Bordakiewicz , Zuzanna Michalska , Donata Pokorska , Julia Świechowska , Zuzanna Zarzycka , Ingrid Samberger , Magdalena Wiciak . ALGORITHMIC AUTHORITY VS. HUMAN TOUCH: A NARRATIVE REVIEW OF PATIENT TRUST AND CLINICAL AUTONOMY IN AI-ASSISTED DIAGNOSTICS. International Journal of Innovative Technologies in Social Science 2026;3(1(49)) View
  11. Yang M, Shi N, Chen H, Po E, Ng P, Lai P, Wu Y, Fong D. Multimodal Artificial Intelligence for Precision Critical Care: A Scoping Review. Health Data Science 2026;6 View
  12. Parreño S. Uncertainty‑aware sepsis survival prediction using conformal XGBoost on minimal clinical features under Sepsis‑3 criteria. Computer Methods and Programs in Biomedicine 2026;283:109429 View
  13. Barriga-Gallegos F, Ríos-Vásquez G, de la Fuente-Mella H, Ulloa Catalán K, Febré Vergara N. Enhancing clinical reliability in pressure injury prediction: A conformal prediction approach with machine learning models. DIGITAL HEALTH 2026;12 View

Books/Policy Documents

  1. Corvelo Benz N, Miranda L, Chen D, Sattler J, Borgwardt K. Research in Computational Molecular Biology. View
  2. Zhao S, Zhang Z, Liu Y, Nguyen K, Wang Y, Luo Z, Li G. The Importance of Being Learnable. View