Cover Image

Clinically Interpretable Mortality Prediction for ICU Patients with Diabetes and Atrial Fibrillation: A Machine Learning Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sun, Li, Chen, Shuheng, Si, Yong, Fan, Junyi, Pishgar, Maryam, Pishgar, Elham, Alaei, Kamiar, Placencia, Greg
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Interpretable Machine Learning Model for Early Prediction of 30-Day Mortality in ICU Patients With Coexisting Hypertension and Atrial Fibrillation: A Retrospective Cohort Study
by: Chen, Shuheng, et al.
Published: (2025)

Machine Learning-Based Prediction of ICU Mortality in Sepsis-Associated Acute Kidney Injury Patients Using MIMIC-IV Database with Validation from eICU Database
by: Chen, Shuheng, et al.
Published: (2025)

Predicting ICU Readmission in Acute Pancreatitis Patients Using a Machine Learning-Based Model with Enhanced Clinical Interpretability
by: Chen, Shuheng, et al.
Published: (2025)

Early Mortality Prediction in ICU Patients with Hypertensive Kidney Disease Using Interpretable Machine Learning
by: Si, Yong, et al.
Published: (2025)

Predicting Short-Term Mortality in Elderly ICU Patients with Diabetes and Heart Failure: A Distributional Inference Framework
by: Fan, Junyi, et al.
Published: (2025)

Machine Learning-Based Prediction of Mortality in Geriatric Traumatic Brain Injury Patients
by: Si, Yong, et al.
Published: (2025)

Development of Interactive Nomograms for Predicting Short-Term Survival in ICU Patients with Aplastic Anemia
by: Fan, Junyi, et al.
Published: (2025)

Predicting Postoperative Stroke in Elderly SICU Patients: An Interpretable Machine Learning Model Using MIMIC Data
by: Li, Tinghuan, et al.
Published: (2025)

Machine Learning-Based Model for Postoperative Stroke Prediction in Coronary Artery Disease
by: Pan, Haonan, et al.
Published: (2025)

Prediction of Significant Creatinine Elevation in First ICU Stays with Vancomycin Use: A retrospective study through Catboost
by: Fan, Junyi, et al.
Published: (2025)

Machine Learning-Based Prediction of ICU Readmissions in Intracerebral Hemorrhage Patients: Insights from the MIMIC Databases
by: Chen, Shuheng, et al.
Published: (2025)

Interpretable Machine Learning Model for Early Prediction of Acute Kidney Injury in Critically Ill Patients with Cirrhosis: A Retrospective Study
by: Sun, Li, et al.
Published: (2025)

A Novel Multi-Task Teacher-Student Architecture with Self-Supervised Pretraining for 48-Hour Vasoactive-Inotropic Trend Analysis in Sepsis Mortality Prediction
by: Jin, Houji, et al.
Published: (2025)

Data-Driven Machine Learning Approaches for Predicting In-Hospital Sepsis Mortality
by: Shumilov, Arseniy, et al.
Published: (2024)

Aligning Language Models with Clinical Expertise: DPO for Heart Failure Nursing Documentation in Critical Care
by: Fan, Junyi, et al.
Published: (2025)

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database
by: Roknaldin, Aleyeh, et al.
Published: (2024)

Advanced Predictive Modeling for Enhanced Mortality Prediction in ICU Stroke Patients Using Clinical Data
by: Abdollahi, Armin, et al.
Published: (2024)

Optimizing Mortality Prediction for ICU Heart Failure Patients: Leveraging XGBoost and Advanced Machine Learning with the MIMIC-III Database
by: Ashrafi, Negin, et al.
Published: (2024)

Effect of a Process Mining based Pre-processing Step in Prediction of the Critical Health Outcomes
by: Ashrafi, Negin, et al.
Published: (2024)

Enhanced Prediction of Ventilator-Associated Pneumonia in Patients with Traumatic Brain Injury Using Advanced Machine Learning Techniques
by: Ashrafi, Negin, et al.
Published: (2024)

Which Voices Move Markets? Speaker Identity and the Cross-Section of Post-Earnings Returns
by: Sidhu, Karmanpartap Singh, et al.
Published: (2026)

Dynamic Token Selection for Aerial-Ground Person Re-Identification
by: Wang, Yuhai, et al.
Published: (2024)

Optimizing Urban Mobility Through Complex Network Analysis and Big Data from Smart Cards
by: Sun, Li, et al.
Published: (2025)

Translating Machine Learning Interpretability into Clinical Insights for ICU Mortality Prediction
by: Liao, Ling, et al.
Published: (2025)

The Value of Glycemic Gap for Predicting Mortality in ICU in Patients With and Without Diabetes
by: Ran Lou, et al.
Published: (2025)

A Nomogram for Predicting In‐Hospital Mortality in Critically Ill Patients With Myocardial Infarction and Atrial Fibrillation
by: Weixi Tan, et al.
Published: (2025)

Think as a Doctor: An Interpretable AI Approach for ICU Mortality Prediction
by: Li, Qingwen, et al.
Published: (2025)

Neural Erosion: Emulating Controlled Neurodegeneration and Aging in AI Systems
by: Alexos, Antonios, et al.
Published: (2024)

Clinical Characteristics and Outcomes of Catheter Ablation in Young Patients With Atrial Fibrillation
by: Xuewen Wang, et al.
Published: (2025)

Transthoracic Echocardiography Combined With the Clinical History Can Predict Left Atrial Thrombus in Patients With Nonvalvular Atrial Fibrillation
by: Jing Wang, et al.
Published: (2025)

A Predictive Nomogram of In‐Hospital Mortality After 48 h for Atrial Fibrillation Patients in the Coronary Care Unit
by: Wenhui Wang, et al.
Published: (2024)

Atrial Fibrillation in Clinical Practice
by: Adrián Baranchuk
Published: (2017)

Atrial Fibrillation Detection Using Machine Learning
by: Singh, Ankit, et al.
Published: (2026)

Predicting ICU Readmission in Patients With Cerebral Infarction: A Machine Learning Approach Using Neurophysiological and Clinical Data
by: Hang Su, et al.
Published: (2025)

Hemodynamic Consequences and Clinical Outcomes With Intravenous Lidocaine Infusion in Patients With Atrial Fibrillation
by: Andrea N. Keithler, et al.
Published: (2026)

Pre‐Operative Reduced Atrial Compliance Is Predictive of Post‐Operative Atrial Fibrillation in Patients Undergoing Esophagectomy
by: Michal Schäfer, et al.
Published: (2025)

Multi-Model Ensemble Approach for Accurate Bi-Atrial Segmentation in LGE-MRI of Atrial Fibrillation Patients
by: Beveridge, Lucas, et al.
Published: (2024)

LLM Encoder vs. Decoder: Robust Detection of Chinese AI-Generated Text with LoRA
by: Jin, Houji, et al.
Published: (2025)

Asundexian Versus Apixaban in Patients With Atrial Fibrillation
by: Zara Saeed, et al.
Published: (2026)

Morphology and Function Assessment of Left Atrial Appendage in Patients With Atrial Fibrillation
by: Ruizhong Liu, et al.
Published: (2024)