AIMC Topic: Cross-Sectional Studies
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Establish and validate the reliability of predictive models in bone mineral density by deep learning as examination tool for women.
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
Sep 20, 2023
UNLABELLED: While FRAX with BMD could be more precise in estimating the fracture risk, DL-based models were validated to slightly reduce the number of under- and over-treated patients when no BMD measurements were available. The validated models coul...
The use of deep learning state-of-the-art architectures for oral epithelial dysplasia grading: A comparative appraisal.
Journal of oral pathology & medicine : official publication of the International Association of Oral Pathologists and the American Academy of Oral Pathology
Sep 15, 2023
BACKGROUND: Dysplasia grading systems for oral epithelial dysplasia are a source of disagreement among pathologists. Therefore, machine learning approaches are being developed to mitigate this issue.
Impact of retraining a deep learning algorithm for improving guideline-compliant aortic diameter measurements on non-gated chest CT.
European journal of radiology
Sep 12, 2023
PURPOSE/OBJECTIVE: Reliable detection of thoracic aortic dilatation (TAD) is mandatory in clinical routine. For ECG-gated CT angiography, automated deep learning (DL) algorithms are established for diameter measurements according to current guideline...
Development of a machine learning multiclass screening tool for periodontal health status based on non-clinical parameters and salivary biomarkers.
Journal of clinical periodontology
Sep 11, 2023
AIM: To develop a multiclass non-clinical screening tool for periodontal disease and assess its accuracy for differentiating periodontal health, gingivitis and different stages of periodontitis.
Validation of a Novel Perceptual Body Image Assessment Method Using Mobile Digital Imaging Analysis: A Cross-Sectional Multicenter Evaluation in a Multiethnic Sample.
Behavior therapy
Sep 9, 2023
Given that mobile digital imaging analyses (DIA) are equipped to automate body composition and subsequently alter one's appearance at a given objective body fat percent (BF%), the purpose of this study was to validate the use of this tool for assessm...
Artificial intelligence in medicine: A comprehensive survey of medical doctor's perspectives in Portugal.
PloS one
Sep 7, 2023
Artificial Intelligence (AI) is increasingly influential across various sectors, including healthcare, with the potential to revolutionize clinical practice. However, risks associated with AI adoption in medicine have also been identified. Despite th...
Early prediction of body composition parameters on metabolically unhealthy in the Chinese population via advanced machine learning.
Frontiers in endocrinology
Aug 29, 2023
BACKGROUND: Metabolic syndrome (Mets) is considered a global epidemic of the 21st century, predisposing to cardiometabolic diseases. This study aims to describe and compare the body composition profiles between metabolic healthy (MH) and metabolic un...
Re-investigation of functional gastrointestinal disorders utilizing a machine learning approach.
BMC medical informatics and decision making
Aug 26, 2023
BACKGROUND: Functional gastrointestinal disorders (FGIDs), as a group of syndromes with no identified structural or pathophysiological biomarkers, are currently classified by Rome criteria based on gastrointestinal symptoms (GI). However, the high ov...
Applicability of machine learning technique in the screening of patients with mild traumatic brain injury.
PloS one
Aug 24, 2023
Even though the demand of head computed tomography (CT) in patients with mild traumatic brain injury (TBI) has progressively increased worldwide, only a small number of individuals have intracranial lesions that require neurosurgical intervention. As...
Norwegian radiologists' expectations of artificial intelligence in mammographic screening - A cross-sectional survey.
European journal of radiology
Aug 23, 2023
PURPOSE: To explore Norwegian breast radiologists' expectations of adding artificial intelligence (AI) in the interpretation procedure of screening mammograms.
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