Latest AI and machine learning research in hospital-based medicine for healthcare professionals.
OBJECTIVE: It is difficult to predict which mechanically ventilated patients will ultimately require...
BACKGROUND: Under- or late identification of pulmonary embolism (PE)-a thrombosis of 1 or more pulmo...
BACKGROUND: Machine learning (ML) risk prediction models, although much more accurate than tradition...
BACKGROUND: Governments worldwide are facing growing pressure to increase transparency, as citizens ...
Nutrition plays a key role in the comprehensive care of critically ill patients. Determining optimal...
We present a case of a 75-year-old Asian woman with Guillain-Barré syndrome (GBS) who underwent a 1-...
BACKGROUND: Tuberculosis spondylitis (TS), commonly known as Pott's disease, is a severe type of ske...
Hydrological simulation in karstic areas is a hard task due to the intrinsic intricacy of these envi...
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air ...
The industrial revolution of the 19th century marked the onset of an era of machines and robots that...
BACKGROUND: The frequency of hip and knee arthroplasty surgeries has been rising steadily in recent ...
BACKGROUND: Â Despite low mortality for elective procedures in the United States and developed countr...
Discharge planning is integral to patient flow as delays can lead to hospital-wide congestion. Becau...
The purpose of this study was to develop a machine learning model for predicting 30-day readmission ...
INTRODUCTION: Treatment in the intensive care unit (ICU) generates complex data where machine learni...
BACKGROUND: A prediction model that estimates mortality at admission to the intensive care unit (ICU...
We developed an interpretable machine learning algorithm that prospectively predicts the risk of thr...
BACKGROUND: Prolonged hospital stays after pediatric surgeries, such as tonsillectomy and adenoidect...
AIM OF THE STUDY: This study aimed to develop an artificial intelligence (AI) model capable of predi...
To explore the application efficacy and significance of deep learning in anesthesia management for g...
BACKGROUND: The effective management of trauma patients necessitates efficient triaging, timely acti...