Latest AI and machine learning research in hospitalists for healthcare professionals.
This paper aimed to detect the latent clusters of patients with opioid use disorder and to identify the risk factors affecting drug misuse using unsupervised machine learning. The cluster with the highest proportion of successful treatment outcomes was characterized by the highest percentage of employment rate at admission and discharge, the highest percentage of patients who also recovered from a...
The rainfall-runoff process is one of the most complex hydrological phenomena. Estimating runoff in the basin is one of the main conditions for planning and optimal use of rainfall. Using machine learning models in various sciences to investigate phenomena for which statistical information is available is a helpful tool. This study investigates and compares the abilities of HEC-HMS and TOPMODEL as...
The role of segmentectomy for lung cancer is expected to increase owing to the results of Japan Clinical Oncology Group (JCOG) 0802. Moreover, the maj...
As the experience with robot-assisted partial nephrectomy (RAPN) grows, the indications have expanded to incorporate previously operated ipsilateral ...
As the coronavirus disease 2019 (COVID-19) global pandemic continues, there is increased value in performing same-day discharge (SDD) protocols to mi...
Initial 37 cases of robot-assisted cardiac surgery were reviewed. The early outcomes were favorable with low transfusion rate and no mortality, but so...
Robotic-based rehabilitation administered by means of serious games certainly represents the frontier of rehabilitation treatments, offering a high de...
OBJECTIVES: Robot-assisted coronary artery bypass grafting (CABG) has been developed as a less invasive alternative for conventional CABG to enhance p...
A significant portion of data in Electronic Health Records is only available as unstructured text, such as surgical or finding reports, clinical notes...
This study aims to investigate the prediction of hospital readmission of alcohol use disorder patients within 28 days of discharge and compare the per...
An 87-year-old female was admitted for endoscopic retrograde cholangiopancreatography (ERCP) due to obstructive jaundice. On admission, total bilirubi...
In a tokamak, disruption is defined as losing control over a confined plasma resulting in sudden extinction of the plasma current. Machine learning of...
Automated information extraction might be able to assist with the collection of stroke key performance indicators (KPI). The feasibility of using natu...
Health care systems around the world do not have sufficient medical services to immediately offer elective (e.g., scheduled or non-emergency) services...
Clinical data are increasingly being mined to derive new medical knowledge with a goal of enabling greater diagnostic precision, better-personalized t...
BACKGROUND: Cost and quality are important, complex, and intertwined surgical outcomes. Evidence suggests that major cost drivers include operating ro...
INTRODUCTION: Patient outcome prediction models are underused in clinical practice because of lack of integration with real-time patient data. The ele...
Vitamin D plays a protective role against COVID-19. Patients with deficiency of vitamin D are more prone to severe SARS-CoV-2 infections. It is known ...
The increasing availability of electronic health records and administrative data and the adoption of computer-based technologies in healthcare have si...
AIMS: This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day di...