AIMC Topic: Mass Screening

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Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.

Frontiers in public health
OBJECTIVE: To develop a machine learning (ML)-based admission screening model for hospital-acquired (HA) influenza using routinely available data to support early clinical intervention.

Artificial intelligence utilization in cancer screening program across ASEAN: a scoping review.

BMC cancer
BACKGROUND: Cancer remains a significant health challenge in the ASEAN region, highlighting the need for effective screening programs. However, approaches, target demographics, and intervals vary across ASEAN member states, necessitating a comprehens...

Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Nature communications
Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytology slides from 17,397 women and test it on 10,826 additional cases through a three-stage process. Th...

Acceptability, applicability, and cost-utility of artificial-intelligence-powered low-cost portable fundus camera for diabetic retinopathy screening in primary health care settings.

Diabetes research and clinical practice
AIMS: To evaluate the acceptability, applicability, and cost-utility of AI-powered portable fundus cameras for diabetic retinopathy (DR) screening in Hong Kong, providing a viable alternative screening solution for resource-limited areas.

Responsible CVD screening with a blockchain assisted chatbot powered by explainable AI.

Scientific reports
Cardiovascular disease (CVD) is rising as a significant concern for the healthcare sector around the world. Researchers have applied multiple traditional approaches to making healthcare systems find new solutions for the CVD concern. Artificial Intel...

Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.

Nature medicine
Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and repeated hospital admissions. Routine screening for patients at risk for an OUD to prevent complications is not standard practice in many hospitals, lead...

Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee.

The Lancet. Digital health
Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts ...

Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection.

BMC psychiatry
OBJECTIVE: To develop a stratified screening tool through machine learning approaches for the Center for Epidemiologic Studies Depression Scale (CES-D-20) while maintaining diagnostic accuracy, addressing the efficiency limitations in large-scale app...

Emerging Applications of Digital Technologies for Periodontal Screening, Diagnosis and Prognosis in the Dental Setting.

Journal of clinical periodontology
AIM: To comprehensively review digital technologies (including artificial intelligence, AI) for periodontal screening, diagnosis and prognosis in the dental setting, focusing on accuracy metrics.