AI Medical Compendium Topic

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Mass Screening

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Guidance for using artificial intelligence for title and abstract screening while conducting knowledge syntheses.

BMC medical research methodology
BACKGROUND: Systematic reviews are the cornerstone of evidence-based medicine. However, systematic reviews are time consuming and there is growing demand to produce evidence more quickly, while maintaining robust methods. In recent years, artificial ...

Opportunistic Osteoporosis Screening Using Chest Radiographs With Deep Learning: Development and External Validation With a Cohort Dataset.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Osteoporosis is a common, but silent disease until it is complicated by fractures that are associated with morbidity and mortality. Over the past few years, although deep learning-based disease diagnosis on chest radiographs has yielded promising res...

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies.

Scientific reports
To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT ima...

A stratified analysis of a deep learning algorithm in the diagnosis of diabetic retinopathy in a real-world study.

Journal of diabetes
BACKGROUND: The aim of our research was to prospectively explore the clinical value of a deep learning algorithm (DLA) to detect referable diabetic retinopathy (DR) in different subgroups stratified by types of diabetes, blood pressure, sex, BMI, age...

Optimizing hepatitis B virus screening in the United States using a simple demographics-based model.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Chronic hepatitis B (CHB) affects >290 million persons globally, and only 10% have been diagnosed, presenting a severe gap that must be addressed. We developed logistic regression (LR) and machine learning (ML; random forest) mod...

Machine learning models for screening carotid atherosclerosis in asymptomatic adults.

Scientific reports
Carotid atherosclerosis (CAS) is a risk factor for cardiovascular and cerebrovascular events, but duplex ultrasonography isn't recommended in routine screening for asymptomatic populations according to medical guidelines. We aim to develop machine le...

A collaborative robotic solution to partly automate SARS-CoV-2 serological tests in small facilities.

SLAS technology
The outbreak of COVID-19 has introduced a significant stress on the healthcare systems of many countries. The availability of quick and reliable screening methodologies can be regarded as the keystone approach to mitigate the spread of the infection ...

BH-index: A predictive system based on serum biomarkers and ensemble learning for early colorectal cancer diagnosis in mass screening.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer is one of the most common malignancies among the general population. Artificial Intelligence methodologies based on serum parameters are in continuous development to obtain less expensive tools for highly s...

Machine learning-assisted screening for cognitive impairment in the emergency department.

Journal of the American Geriatrics Society
BACKGROUND/OBJECTIVES: Despite a high prevalence and association with poor outcomes, screening to identify cognitive impairment (CI) in the emergency department (ED) is uncommon. Identification of high-risk subsets of older adults is a critical chall...