Hospital-Based Medicine

Application of Artificial Intelligence in rehabilitation science: A scientometric investigation Utilizing Citespace.

This study presents a scientometric analysis of the intersection between rehabilitation science and artificial intelligence (AI) technologies, using data from the Web of Science (WOS) database from 2002 to 2022. The analysis employed a comprehensive search query with key AI-related terms, focusing on a wide range of publications in rehabilitation science. Utilizing the Citespace tool, the study vi...

Risk assessment and prediction of nosocomial infections based on surveillance data using machine learning methods.

BACKGROUND: Nosocomial infections with heavy disease burden are becoming a major threat to the health care system around the world. Through long-term, systematic, continuous data collection and analysis, Nosocomial infection surveillance (NIS) systems are constructed in each hospital; while these data are only used as real-time surveillance but fail to realize the prediction and early warning func...

Early Postoperative Prediction of Complications and Readmission After Colorectal Cancer Surgery Using an Artificial Neural Network.

BACKGROUND: Early predictors of postoperative complications can risk-stratify patients undergoing colorectal cancer surgery. However, conventional reg...

DeepSAP: A Novel Brain Image-Based Deep Learning Model for Predicting Stroke-Associated Pneumonia From Spontaneous Intracerebral Hemorrhage.

RATIONALE AND OBJECTIVE: Stroke-associated pneumonia (SAP) often appears as a complication following intracerebral hemorrhage (ICH), leading to poor p...

Prediction of in-hospital Mortality of Intensive Care Unit Patients with Acute Pancreatitis Based on an Explainable Machine Learning Algorithm.

BACKGROUND AND AIM: Acute pancreatitis (AP) is potentially fatal. Therefore, early identification of patients at a high mortality risk and timely inte...

Quantification of litter in cities using a smartphone application and citizen science in conjunction with deep learning-based image processing.

Cities are a major source of litter pollution. Determination of the abundance and composition of plastic litter in cities is imperative for effective ...

Machine learning risk stratification for high-risk infant follow-up of term and late preterm infants.

BACKGROUND: Term and late preterm infants are not routinely referred to high-risk infant follow-up programs at neonatal intensive care unit (NICU) dis...

An artificial intelligence-designed predictive calculator of conversion from minimally invasive to open colectomy in colon cancer.

Minimally invasive surgery is safe and effective in colorectal cancer. Conversion to open surgery may be associated with adverse effects on treatment ...

Artificial intelligence and personalized diagnostics in periodontology: A narrative review.

Periodontal diseases pose a significant global health burden, requiring early detection and personalized treatment approaches. Traditional diagnostic ...

Shaping dynamical neural computations using spatiotemporal constraints.

Dynamics play a critical role in computation. The principled evolution of states over time enables both biological and artificial networks to represen...

Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers.

This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional liv...

Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).

Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have pre...

Artificial intelligence and its implications for data privacy.

Contemporary, multidisciplinary research sheds light on data privacy implications of artificial intelligence (AI). This review adopts an AI ecosystem ...

Development of a new prognostic model to predict pneumonia outcome using artificial intelligence-based chest radiograph results.

This study aimed to develop a new simple and effective prognostic model using artificial intelligence (AI)-based chest radiograph (CXR) results to pre...

Using machine learning or deep learning models in a hospital setting to detect inappropriate prescriptions: a systematic review.

OBJECTIVES: The emergence of artificial intelligence (AI) is catching the interest of hospital pharmacists. A massive collection of health data is now...

The role of artificial intelligence and data science in nanoparticles development: a review.

Artificial intelligence has revolutionized many sectors with unparalleled predictive capabilities supported by machine learning (ML). So far, this too...

Virtual Clinical Trials: Implications of Computer Simulations and Artificial Intelligence for Musculoskeletal Research.

In silico clinical trials, particularly when augmented with artificial intelligence methods, represent an innovative approach with much to offer, part...

Development and validation of machine learning models to predict perioperative transfusion risk for hip fractures in the elderly.

BACKGROUND: Patients with hip fractures frequently need to receive perioperative transfusions of concentrated red blood cells due to preoperative anem...

A hybrid SWAT-ANN model approach for analysis of climate change impacts on sediment yield in an Eastern Himalayan sub-watershed of Brahmaputra.

The current study focuses on analyzing the impacts of climate change and land use/land cover (LULC) changes on sediment yield in the Puthimari basin, ...

Machine learning for the prediction of in-hospital mortality in patients with spontaneous intracerebral hemorrhage in intensive care unit.

This study aimed to develop a machine learning (ML)-based tool for early and accurate prediction of in-hospital mortality risk in patients with sponta...