Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
This study aimed to develop a machine learning (ML)-based tool for early and accurate prediction of ...
This research utilized machine learning to analyze experiments conducted in an open channel laborato...
Postoperative ileus (POI) is a common complication after colorectal surgery, leading to increased h...
Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical ...
BACKGROUND: Predicting functional impairment after intracerebral hemorrhage (ICH) provides valuable ...
BACKGROUND: Patients in serious condition due to COVID-19 often require special care in intensive ca...
BACKGROUND: Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to anal...
BACKGROUND: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prost...
To investigate the factors that influence readmissions in patients with acute non-ST elevation myoca...
Despite years of research, we are still not able to reliably predict who might benefit from electroc...
The purposes were to assess the efficacy of AI-generated radiology reports in terms of report summar...
Renal recovery following dialysis-requiring acute kidney injury (AKI-D) is a vital clinical outcome ...
BACKGROUND: This study aimed to develop a higher performance nomogram based on explainable machine l...
Artificial Intelligence (AI) applications in healthcare are evolving rapidly. The integration of AI ...
Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim t...
Detecting patients with a high-risk profile for treatment-resistant schizophrenia (TRS) can be benef...
OBJECTIVE: Post-operative length of hospital stay (LOS) is a valuable measure for monitoring quality...
INTRODUCTION: Neonatal intensive care unit (NICU) admission is a stressful experience for parents. N...
Effective planning and managing medical waste necessitate a crucial focus on both the public and pri...
We present a neural network framework for learning a survival model to predict a time-to-event outco...
AIMS: There is a lack of tools for accurately identifying the risk of readmission for heart failure ...