NCBI PubMed Central
open access
Predicting Mortality in Intensive Care Unit Patients With Allergic Bronchopulmonary Aspergillosis (ABPA) Using an Interpretable Machine Learning Model: A Retrospective Cohort Study.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
Checking your browser - reCAPTCHA Checking your browser before accessing pmc.ncbi.nlm.nih.gov ... Click here if you are not automatically redirected after 5 seconds.
Related documents
- Development and Interpretability Analysis of a Stacking Ensemble Model for Early Prediction of Nutritional Risk in Intensive Care Unit Patients: Retrospective Cohort Study.#258101
- Development and validation of an explainable machine learning model for mortality prediction in ICU patients with lung cancer.#368026
- Leveraging Clinical Data for Early Heart Disease Prediction: A Machine Learning Approach With Interpretability Analysis.#196073
- Cross-silo federated learning for predicting successful mechanical ventilation weaning across 5 intensive care unit databases: retrospective database analysis / Seyedmostafa Sheikhalishahi, Mathias Kaspar, Johanna Schwinn, Matthaeus Morhart, Philipp Simon, Ludwig Christian Hinske#661753
- Development and external validation of an ICU mortality prediction model using routinely collected clinical data.#251046
Record · ID 28249 · SHA-256 ca0f8ef3d8a44bc5
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive