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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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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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Background: Mental health concerns have become increasingly prevalent; however, care remains inaccessible to many. While digital mental health interventions offer a promising solution, self-help and even coached apps have not fully addressed the challenge. There is now a growing interest in hybrid, or blended, care approaches that use apps as tools to augment, rather than to entirely guide, care.

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Short-term starvation boosts anti-PD-L1 therapy by reshaping tumor-associated macrophages in hepatocellular carcinoma.

Hepatology

January 2025

Hepatic Surgery Centre, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, People's Republic of China.

Background And Aims: Immune checkpoint inhibitors (ICIs) have revolutionized systemic hepatocellular carcinoma (HCC) treatment. Nevertheless, numerous patients are refractory to ICIs therapy. It is currently unknown whether diet therapies such as short-term starvation (STS) combined with ICIs can be used to treat HCC.

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Purpose: The study aimed to identify and assess the methodological quality of essential clinical guidelines for the management of laryngitis and pharyngitis.

Methods: A systematic search of clinical guidelines for the management of laryngitis and pharyngitis was performed in three databases. Methodological quality was assessed according to AGREE II, in which each item in its domains was scored by four independent evaluators.

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