Infection Control

Exploring Hospital Overcrowding with an Explainable Time-to-Event Machine Learning Approach.

Emergency department (ED) overcrowding is a complex problem that is intricately linked with the oper...

Predicting Patient No-Shows: Situated Machine Learning with Imperfect Data.

Patients who do not show up for scheduled appointments are a considerable cost and concern in health...

Assessment of Knowledge, Practice, Perception, and Expectations of Artificial Intelligence in Medical Care among Staff of a Tertiary Hospital.

BACKGROUND: Artificial intelligence (AI) is the simulation of human intelligence processes by machin...

[Translated article] Introducing artificial intelligence to hospital pharmacy departments.

Artificial intelligence is a broad concept that includes the study of the ability of computers to pe...

Approaching artificial intelligence to Hospital Pharmacy.

Artificial intelligence (AI) is a broad concept that includes the study of the ability of computers ...

[Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning].

OBJECTIVE: To predict the risk of in-hospital death in patients with chronic heart failure (CHF) com...

Artificial-intelligence-based neurological outcome prediction during out-of-hospital cardiac arrest.

[Computer-vision-based artificial intelligence for detection and recognition of instruments and organs during radical laparoscopic gastrectomy for gastric cancer: a multicenter study].

To investigate the feasibility and accuracy of computer vision-based artificial intelligence techno...

Deep learning application to automated classification of recommendations made by hospital pharmacists during medication prescription review.

PURPOSE: Recommendations to improve therapeutics are proposals made by pharmacists during the prescr...

A prediction model for reactivation of Langerhans cell histiocytosis based on machine-learning algorithms.

Langerhans cell histiocytosis (LCH) is a rare inflammatory myeloid neoplasm characterized by the clo...

Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures.

PURPOSE: Adverse effects of chemotherapy often require hospital admissions or treatment management. ...

Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.

The health product circuit corresponds to the chain of steps that a medicine goes through in hospita...

Implementation of a Clinical, Patient-Level Dashboard at a Mental Health Hospital: Lessons Learned from Two Pilot Clinics.

The Centre for Addiction and Mental Health has implemented mechanisms to standardize routine data co...

[Evaluation of brain age changes in patients with liver cirrhosis and hepatic encephalopathy with deep learning models based on structural magnetic resonance imaging].

To investigate the brain aging in patients with cirrhosis and hepatic encephalopathy(HE), construct...

Toward Relieving Clinician Burden by Automatically Generating Progress Notes using Interim Hospital Data.

CHARTPNG, 7089 1616 80.53 19.61 76.9%

Maturity degree assessment of hospital ward system using integrated fuzzy AHP-TOPSIS model.

BACKGROUND: The hospital ward system is the core service unit of a hospital and an important aspect ...

Robot-Assisted Repair of Ureteroenteric Strictures After Cystectomy with Urinary Diversion: Technique Description and Outcomes from the European Robotic Urology Section Scientific Working Group.

Robot-assisted repair of benign ureteroenteric anastomotic strictures (UAS) provides an alternative...

Improving Cardiology-Rehospitalization Prediction Through the Synergy of Process Mining and Deep Learning: An Innovative Approach.

Nowadays, hospitals are facing the need for an accurate prediction of rehospitalizations. Rehospital...

Understanding and Use of Artificial Intelligence Among Doctors in a University Hospital in Morocco.

INTRODUCTION: Research and development in artificial intelligence (AI) has increased dramatically ov...

Design and implementation of a smart Internet of Things chest pain center based on deep learning.

The data input process for most chest pain centers is not intelligent, requiring a lot of staff to m...

[Development of auxiliary early predicting model for human brucellosis using machine learning algorithm].

Using machine learning algorithms to construct an early prediction model of brucellosis to improve t...