AI Medical Compendium Topic:
Cross-Sectional Studies

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Disentangled representation for sequential treatment effect estimation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Treatment effect estimation, as a fundamental problem in causal inference, focuses on estimating the outcome difference between different treatments. However, in clinical observational data, some patient covariates (such as ...

Deep learning alignment of bidirectional raster scanning in high speed photoacoustic microscopy.

Scientific reports
Simultaneous point-by-point raster scanning of optical and acoustic beams has been widely adapted to high-speed photoacoustic microscopy (PAM) using a water-immersible microelectromechanical system or galvanometer scanner. However, when using high-sp...

Role of Artificial Intelligence and Machine Learning in the prediction of the pain: A scoping systematic review.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Artificial Intelligence in healthcare is growing quickly in diagnostics and treatment management. Despite the quantity and variety of studies its role in clinical care is not clear. To identify the evidence gaps and characteristics of the Artificial ...

Deep Learning-Based Noise Reduction Improves Optical Coherence Tomography Angiography Imaging of Radial Peripapillary Capillaries in Advanced Glaucoma.

Current eye research
PURPOSE: We applied deep learning-based noise reduction (NR) to optical coherence tomography-angiography (OCTA) images of the radial peripapillary capillaries (RPCs) in eyes with glaucoma and investigated the usefulness of this method as an objective...

Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: A cross-sectional study.

Journal of affective disorders
BACKGROUND: Machine learning (ML) algorithms based on various clinicodemographic, psychometric, and biographic factors have been used to predict depression, suicidal ideation, and suicide attempt in adolescents, but there is still a need for more acc...

Comments on "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India".

Monaldi archives for chest disease = Archivio Monaldi per le malattie del torace
Dear Editor, we read the publication by Rustagi et al. "Identifying psychological antecedents and predictors of vaccine hesitancy through machine learning: A cross sectional study among chronic disease patients of deprived urban neighbourhood, India"...

Deep learning-based quantitative estimation of lymphedema-induced fibrosis using three-dimensional computed tomography images.

Scientific reports
In lymphedema, proinflammatory cytokine-mediated progressive cascades always occur, leading to macroscopic fibrosis. However, no methods are practically available for measuring lymphedema-induced fibrosis before its deterioration. Technically, CT can...

Accuracy and clinical relevance of an automated, algorithm-based analysis of facial signs from selfie images of women in the United States of various ages, ancestries and phototypes: A cross-sectional observational study.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Real-life validation is necessary to ensure our artificial intelligence (AI) skin diagnostic tool is inclusive across a diverse and representative US population of various ages, ancestries and skin phototypes.

Identifying Glucose Metabolism Status in Nondiabetic Japanese Adults Using Machine Learning Model with Simple Questionnaire.

Computational and mathematical methods in medicine
We aimed to identify the glucose metabolism statuses of nondiabetic Japanese adults using a machine learning model with a questionnaire. In this cross-sectional study, Japanese adults (aged 20-64 years) from Tokyo and surrounding areas were recruited...