AIMC Topic: Mass Screening

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Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study.

Diabetes research and clinical practice
AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy (DR) screening in Japan. This evaluation compared the simultaneous introduction of AI in nationwide health checkups, namely "specific health check-up...

Operational Advantages of Novel Strategies Supported by Portability and Artificial Intelligence for Breast Cancer Screening in Low-Resource Rural Areas: Opportunities to Address Health Inequities and Vulnerability.

Medicina (Kaunas, Lithuania)
Early detection of breast cancer plays a crucial role in reducing the number of cases diagnosed at advanced stages, thereby lowering the high healthcare costs required to achieve disease-free survival and helping to prevent avoidable premature deaths...

The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population-Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis.

JMIR research protocols
BACKGROUND: HIV testing is the cornerstone of HIV prevention and a pivotal step in realizing the Joint United Nations Program on HIV/AIDS (UNAIDS) goal of ending AIDS by 2030. Despite the availability of relevant survey data, there exists a research ...

Evaluation of an AI-Based Voice Biomarker Tool to Detect Signals Consistent With Moderate to Severe Depression.

Annals of family medicine
PURPOSE: Mental health screening is recommended by the US Preventive Services Task Force for all patients in areas where treatment options are available. Still, it is estimated that only 4% of primary care patients are screened for depression. The go...

Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems.

Circulation. Genomic and precision medicine
BACKGROUND: While universal screening for Lipoprotein(a) [Lp(a)] is increasingly recommended, <0.5% of patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a) (ARISE), a ...

Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study.

Experimental biology and medicine (Maywood, N.J.)
Screening tests for disease have their performance measured through sensitivity and specificity, which inform how well the test can discriminate between those with and without the condition. Typically, high values for sensitivity and specificity are ...

Nationwide real-world implementation of AI for cancer detection in population-based mammography screening.

Nature medicine
Artificial intelligence (AI) in mammography screening has shown promise in retrospective evaluations, but few prospective studies exist. PRAIM is an observational, multicenter, real-world, noninferiority, implementation study comparing the performanc...

High performance COVID-19 screening using machine learning.

La Tunisie medicale
Since the World Health Organization declared the Coronavirus Disease 2019 (COVID-19) pandemic as an international concern of public health emergency in the early 2020, several strategies have been initiated in many countries to prevent healthcare ser...

Machine learning-assisted construction of COPD self-evaluation questionnaire (COPD-EQ): a national multicentre study in China.

Journal of global health
BACKGROUND: Approximately 70% of chronic obstructive pulmonary disease (COPD) is underdiagnosed worldwide. We aimed to develop and validate a COPD self-evaluation questionnaire (COPD-EQ) that is better suited for COPD screening in China.