AIMC Topic: Cross-Sectional Studies

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Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review.

Journal of digital imaging
Since 2000, there have been more than 8000 publications on radiology artificial intelligence (AI). AI breakthroughs allow complex tasks to be automated and even performed beyond human capabilities. However, the lack of details on the methods and algo...

Human examination and artificial intelligence in cephalometric landmark detection-is AI ready to take over?

Dento maxillo facial radiology
OBJECTIVES: To compare the precision of two cephalometric landmark identification methods, namely a computer-assisted human examination software and an artificial intelligence program, based on South African data.

Identifying, Measuring, and Ranking Social Determinants of Health for Health Promotion Interventions Targeting Informal Settlement Residents.

Journal of preventive medicine and public health = Yebang Uihakhoe chi
OBJECTIVES: Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health p...

Comparison of computed tomography and dual-energy X-ray absorptiometry in the evaluation of body composition in patients with obesity.

Frontiers in endocrinology
OBJECTIVE: a) To evaluate the accuracy of the pre-existing equations (based on cm2 provided by CT images), to estimate in kilograms (Kg) the body composition (BC) in patients with obesity (PwO), by comparison with Dual-energy X-ray absorptiometry (DX...

The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.

Acta ophthalmologica
PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS.

Assessing facial weakness in myasthenia gravis with facial recognition software and deep learning.

Annals of clinical and translational neurology
OBJECTIVE: Myasthenia gravis (MG) is an autoimmune disease leading to fatigable muscle weakness. Extra-ocular and bulbar muscles are most commonly affected. We aimed to investigate whether facial weakness can be quantified automatically and used for ...

Performance of an automated deep learning algorithm to identify hepatic steatosis within noncontrast computed tomography scans among people with and without HIV.

Pharmacoepidemiology and drug safety
PURPOSE: Hepatic steatosis (fatty liver disease) affects 25% of the world's population, particularly people with HIV (PWH). Pharmacoepidemiologic studies to identify medications associated with steatosis have not been conducted because methods to eva...

Pain, dynamic postural control, mental health and impact of oral health in individuals with temporomandibular disorder: A cross-sectional study.

Journal of bodywork and movement therapies
INTRODUCTION: Some studies claim that functional changes in TMD affect the stomatognathic system (SS) and could contribute to the emergence of pain and changes in postural control.

Deep learning in optical coherence tomography: Where are the gaps?

Clinical & experimental ophthalmology
Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid, high-resolution and cross-sectional morphology of macular area and optic nerve head for diagnosis and managing of different eye diseases. However, in...

Prediction of Anemia From Cerebral Venous Sinus Attenuation on Deep-Learning Reconstructed Brain Computed Tomography Images.

Journal of computer assisted tomography
OBJECTIVE: The aim of the study is to evaluate whether the prediction of anemia is possible using quantitative analyses of unenhanced cranial computed tomography (CT) with deep learning reconstruction (DLR) compared with conventional methods.