AIMC Topic: Rural Population
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A machine learning approach to understanding the road and traffic environments of crashes involving driver distraction and inattention (DDI) on rural multilane highways.
Journal of safety research
Nov 14, 2024
INTRODUCTION: Driver distraction and inattention (DDI) are major causes of road crashes, especially on rural highways. However, not all instances of distracted or inattentive driving lead to crashes. Previous studies indicate that DDI-related driving...
The Promise of Remote Patient Monitoring.
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Nov 13, 2024
The promise of remote patient monitoring (RPM) lies in its ability to revolutionize health care delivery by enabling continuous, real-time tracking of patient health outside traditional clinical settings. The COVID-19 pandemic accelerated the adoptio...
Spatial patterns of rural opioid-related hospital emergency department visits: A machine learning analysis.
Health & place
Oct 13, 2024
As opioid-related overdose emergency department visits continue to rise in the United States, there is a need to understand the location and magnitude of the crisis, especially in at-risk rural areas. We analyzed sets of ZIP code level electronic hea...
The Use of Remote Presence Robotic Tele-Presentation in Rural and Remote Canada: A Systematic Review.
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Oct 7, 2024
One potential solution to limited health care in rural and remote regions is remote presence robotic tele-presentation to allow health care providers to care for patients in their home community via a robotic interface. We synthesized evidence regar...
Diagnostic Performance of the Offline Medios Artificial Intelligence for Glaucoma Detection in a Rural Tele-Ophthalmology Setting.
Ophthalmology. Glaucoma
Sep 12, 2024
PURPOSE: This study assesses the diagnostic efficacy of offline Medios Artificial Intelligence (AI) glaucoma software in a primary eye care setting, using nonmydriatic fundus images from Remidio's Fundus-on-Phone (FOP NM-10). Artificial intelligence ...
Mobil Monitoring Doppler Ultrasound (MoMDUS) study: protocol for a prospective, observational study investigating the use of artificial intelligence and low-cost Doppler ultrasound for the automated quantification of hypertension, pre-eclampsia and fetal growth restriction in rural Guatemala.
BMJ open
Sep 10, 2024
INTRODUCTION: Undetected high-risk conditions in pregnancy are a leading cause of perinatal mortality in low-income and middle-income countries. A key contributor to adverse perinatal outcomes in these settings is limited access to high-quality scree...
Recruitment in Appalachian, Rural and Older Adult Populations in an Artificial Intelligence World: Study Using Human-Mediated Follow-Up.
JMIR formative research
Aug 22, 2024
BACKGROUND: Participant recruitment in rural and hard-to-reach (HTR) populations can present unique challenges. These challenges are further exacerbated by the need for low-cost recruiting, which often leads to use of web-based recruitment methods (e...
Real-world evaluation of RetCAD deep-learning system for the detection of referable diabetic retinopathy and age-related macular degeneration.
Clinical & experimental optometry
Aug 12, 2024
CLINICAL RELEVANCE: The challenges of establishing retinal screening programs in rural settings may be mitigated by the emergence of deep-learning systems for early disease detection.
Use of artificial intelligence-guided echocardiography to detect cardiac dysfunction and heart valve disease in rural and remote areas: Rationale and design of the AGILE-echo trial.
American heart journal
Aug 10, 2024
BACKGROUND: Transthoracic echocardiography (TTE) is essential in the diagnosis of cardiovascular diseases (CVD), including but not limited to heart failure (HF) and heart valve disease (HVD). However, its dependence on expert acquisition means that i...
A lightweight intelligent laryngeal cancer detection system for rural areas.
American journal of otolaryngology
Aug 8, 2024
OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of lary...
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