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Outpatients

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Application of PSO-based LSTM Neural Network for Outpatient Volume Prediction.

Journal of healthcare engineering
In order to study the construction method of long- and short-term memory neural network model, which is based on particle swarm optimization algorithm and its application in hospital outpatient management, we have selected historical data of outpatie...

Machine learning prediction of dropping out of outpatients with alcohol use disorders.

PloS one
BACKGROUND: Alcohol use disorder (AUD) is a chronic disease with a higher recurrence rate than that of other mental illnesses. Moreover, it requires continuous outpatient treatment for the patient to maintain abstinence. However, with a low probabili...

Advancing care for acute gastrointestinal bleeding using artificial intelligence.

Journal of gastroenterology and hepatology
The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision making. Machine learning algorithms have shown promise in outperforming existing clinical risk score...

Characterising the nationwide burden and predictors of unkept outpatient appointments in the National Health Service in England: A cohort study using a machine learning approach.

PLoS medicine
BACKGROUND: Unkept outpatient hospital appointments cost the National Health Service £1 billion each year. Given the associated costs and morbidity of unkept appointments, this is an issue requiring urgent attention. We aimed to determine rates of un...

Predicting cognitive impairment in outpatients with epilepsy using machine learning techniques.

Scientific reports
Many studies report predictions for cognitive function but there are few predictions in epileptic patients; therefore, we established a workflow to efficiently predict outcomes of both the Mini-Mental State Examination (MMSE) and Montreal Cognitive A...

Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches.

PloS one
The COVID-19 pandemic has been widely spread and affected millions of people and caused hundreds of deaths worldwide, especially in patients with comorbilities and COVID-19. This manuscript aims to present models to predict, firstly, the number of co...

Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study.

European radiology
OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicenter cohort of chest radiographs and to compare physicians' ability to detect and localize referable thoracic abnormalities with and without AI assistanc...

Outpatient Inpatient Robot-Assisted Radical Prostatectomy: An Evidence-Based Analysis of Comparative Outcomes.

Journal of endourology
To provide a systematic analysis of outcomes comparing outpatient and inpatient robot-assisted radical prostatectomy (RARP) for prostate cancer based on the best available evidence. A comprehensive search of electronic databases (PubMed, Web of Sci...

Results of robotic TAPP and conventional laparoscopic TAPP in an outpatient setting: a cohort study in Switzerland.

Langenbeck's archives of surgery
PURPOSE: Recently, robotic surgery has been increasingly performed in hernia surgery. Although feasibility and safety of robot-assisted inguinal hernia repair in an inpatient setting have been already shown, its role in outpatient hernia surgery has ...