AIMC Topic: Mass Screening
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Analyzing Geospatial and Socioeconomic Disparities in Breast Cancer Screening Among Populations in the United States: Machine Learning Approach.
JMIR cancer
Jan 16, 2025
BACKGROUND: Breast cancer screening plays a pivotal role in early detection and subsequent effective management of the disease, impacting patient outcomes and survival rates.
Socioeconomic Factors
Mass Screening
Early Detection of Cancer
Mammography
Aged
Breast Neoplasms
Middle Aged
United States
Socioeconomic Disparities in Health
Healthcare Disparities
Spatial Analysis
Social Determinants of Health
Behavioral Risk Factor Surveillance System
Humans
Machine Learning
Female
Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study.
Experimental biology and medicine (Maywood, N.J.)
Jan 8, 2025
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
Jan 7, 2025
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
Jan 5, 2025
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
Jan 3, 2025
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.
Stress Monitoring in Pandemic Screening: Insights from GSR Sensor and Machine Learning Analysis.
Biosensors
Jan 2, 2025
This study investigates the impact of patient stress on COVID-19 screening. An attempt was made to measure the level of anxiety of individuals undertaking rapid tests for SARS-CoV-2. To this end, a galvanic skin response (GSR) sensor that was connect...
Patient and practitioner perceptions around use of artificial intelligence within the English NHS diabetic eye screening programme.
Diabetes research and clinical practice
Dec 19, 2024
AIMS: Automated retinal image analysis using Artificial Intelligence (AI) can detect diabetic retinopathy as accurately as human graders, but it is not yet licensed in the NHS Diabetic Eye Screening Programme (DESP) in England. This study aims to ass...
Diagnostic Accuracy of Artificial Intelligence-Based Chest X-Ray reading for screening of Tuberculosis.
Journal of Nepal Health Research Council
Dec 19, 2024
BACKGROUND: Tuberculosis remains a public health challenge in Nepal and ranks as the seventh leading cause of death in the country. The END Tuberculosis strategy stresses - the screening for symptoms alone may not suffice; additional screening tools ...
Efficient Screening in Obstructive Sleep Apnea Using Sequential Machine Learning Models, Questionnaires, and Pulse Oximetry Signals: Mixed Methods Study.
Journal of medical Internet research
Dec 19, 2024
BACKGROUND: Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by frequent pauses or shallow breathing during sleep. Polysomnography, the gold standard for OSA assessment, is time consuming and labor intensive, thus limiting di...
Screening for Depression and Anxiety Using a Nonverbal Working Memory Task in a Sample of Older Brazilians: Observational Study of Preliminary Artificial Intelligence Model Transferability.
JMIR formative research
Dec 12, 2024
BACKGROUND: Anxiety and depression represent prevalent yet frequently undetected mental health concerns within the older population. The challenge of identifying these conditions presents an opportunity for artificial intelligence (AI)-driven, remote...
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