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In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040.

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[Approach to Scabies in Children: An Update].

Acta Med Port

January 2025

Serviço de Dermatologia. Unidade Local de Saúde Santo António. Porto. Portugal.

Scabies is a common dermatological infection that globally affects more than 200 million people. It is caused by the parasite Sarcoptes scabiei var. hominis and its transmission primarily occurs through direct contact.

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Background: Thyroid nodules classified cytologically as low-risk indeterminate lesions (TIR3A) on fine-needle aspiration biopsy (FNAB) present a clinical challenge due to their uncertain malignancy risk. This single-center study aimed to evaluate the natural history of TIR3A nodules.

Materials And Methods: FNABs performed between July 2017 and December 2019 were retrospectively retrieved and patients with TIR3A nodules were evaluated at baseline and throughout a follow-up based on ultrasound (US) parameters and clinical data.

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Pediatric neuro-oncology patients have one of the highest mortality rates among all children with cancer. Our study examines the potential relationship between palliative care consultation and intensity of in-hospital care and determines if racial and ethnic differences are associated with palliative care consultations during their terminal admission. Retrospective observational study using the Pediatric Health Information System (PHIS) database with data from U.

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Transformers for Neuroimage Segmentation: Scoping Review.

J Med Internet Res

January 2025

Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.

Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.

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