AIMC Topic: Cross-Sectional Studies

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Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.

Indian journal of ophthalmology
PURPOSE: An observational study to assess the sensitivity and specificity of the Medios smartphone-based offline deep learning artificial intelligence (AI) software to detect diabetic retinopathy (DR) compared with the image diagnosis of ophthalmolog...

Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

JAMA ophthalmology
IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary among patients, structure-function studies and quality-of-life assessments are impeded by the lack of appropriate characterization of end-stage VF loss.

Utility of MemTrax and Machine Learning Modeling in Classification of Mild Cognitive Impairment.

Journal of Alzheimer's disease : JAD
BACKGROUND: The widespread incidence and prevalence of Alzheimer's disease and mild cognitive impairment (MCI) has prompted an urgent call for research to validate early detection cognitive screening and assessment.

Effects of robot-assisted gait training alongside conventional therapy on the development of walking in children with cerebral palsy.

Journal of pediatric rehabilitation medicine
PURPOSE: To investigate the effects of robot-assisted gait training (RAGT) alongside conventional therapy on the standing and walking abilities of children with cerebral palsy (CP).

Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Computed tomographic (CT) is a fundamental imaging modality to generate cross-sectional views of internal anatomy in a living subject or interrogate material composition of an object, and it has been routinely used in clinical applications and nondes...

Vitamin D deficiency among children aged 10-18 years in Sri Lanka.

The Ceylon medical journal
BACKGROUND: Vitamin D deficiency (VDD) and insufficiency (VDI) are public health problems in many countries, and limited data is available on the prevalence of VDD/VDI in Sri Lanka.

Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

Metabolic syndrome and related disorders
We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibr...

Sarcopenia feature selection and risk prediction using machine learning: A cross-sectional study.

Medicine
The purpose of this study was to verify the usefulness of machine learning (ML) for selection of risk factors and development of predictive models for patients with sarcopenia.We collected medical records from Korean postmenopausal women based on Kor...