AIMC Topic: Outpatients
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Large-Scale Study on AI's Impact on Identifying Chest Radiographs with No Actionable Disease in Outpatient Imaging.
Academic radiology
Jul 12, 2024
RATIONALE AND OBJECTIVES: Given the high volume of chest radiographs, radiologists frequently encounter heavy workloads. In outpatient imaging, a substantial portion of chest radiographs show no actionable findings. Automatically identifying these ca...
Dissatisfaction-considered waiting time prediction for outpatients with interpretable machine learning.
Health care management science
Jun 1, 2024
Long waiting time in outpatient departments is a crucial factor in patient dissatisfaction. We aim to analytically interpret the waiting times predicted by machine learning models and provide patients with an explanation of the expected waiting time....
Assessing the utility of artificial intelligence throughout the triage outpatients: a prospective randomized controlled clinical study.
Frontiers in public health
May 30, 2024
Currently, there are still many patients who require outpatient triage assistance. ChatGPT, a natural language processing tool powered by artificial intelligence technology, is increasingly utilized in medicine. To facilitate and expedite patients' n...
Improved Glycemic Control through Robot-Assisted Remote Interview for Outpatients with Type 2 Diabetes: A Pilot Study.
Medicina (Kaunas, Lithuania)
Feb 15, 2024
: Our research group developed a robot-assisted diabetes self-management monitoring system to support Certified Diabetes Care and Education Specialists (CDCESs) in tracking the health status of patients with type 2 diabetes (T2D). This study aimed to...
Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques.
BMC medical informatics and decision making
Feb 8, 2024
BACKGROUND: The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet mental health needs. Ac...
Editorial Comment: Are Body Composition Metrics Applicable to Clinical Practice?
AJR. American journal of roentgenology
Sep 14, 2022
Utility of Normalized Body Composition Areas, Derived From Outpatient Abdominal CT Using a Fully Automated Deep Learning Method, for Predicting Subsequent Cardiovascular Events.
AJR. American journal of roentgenology
Aug 31, 2022
CT-based body composition (BC) measurements have historically been too resource intensive to analyze for widespread use and have lacked robust comparison with traditional weight metrics for predicting cardiovascular risk. The aim of this study was ...
Results of robotic TAPP and conventional laparoscopic TAPP in an outpatient setting: a cohort study in Switzerland.
Langenbeck's archives of surgery
May 24, 2022
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 ...
Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches.
PloS one
Jan 21, 2022
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...
Outpatient Inpatient Robot-Assisted Radical Prostatectomy: An Evidence-Based Analysis of Comparative Outcomes.
Journal of endourology
Jan 5, 2022
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...
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