RESUMO
Alzheimer's disease (AD) is the most common cause of dementia and accounts for 60-70â¯% of all cases. It affects millions of people worldwide. AD poses a substantial economic burden on societies and healthcare systems. AD is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. As the prevalence of AD continues to increase, understanding its pathogenesis, improving diagnostic methods, and developing effective therapeutics have become paramount. This comprehensive review delves into the intricate mechanisms underlying AD, explores the current state of diagnostic techniques, and examines emerging therapeutic strategies. By revealing the complexities of AD, this review aims to contribute to the growing body of knowledge surrounding this devastating disease.
RESUMO
BACKGROUND AND AIM: Contrast-enhanced harmonic endoscopic ultrasonography (CH-EUS) is useful for the diagnosis of lesions inside and outside the digestive tract. This study evaluated the value of artificial intelligence (AI) in the diagnosis of gastric submucosal tumors by CH-EUS. METHODS: This retrospective study included 53 patients with gastrointestinal stromal tumors (GISTs) and leiomyomas, all of whom underwent CH-EUS between June 2015 and February 2020. A novel technology, SiamMask, was used to track and trim the lesions in CH-EUS videos. CH-EUS was evaluated by AI using deep learning involving a residual neural network and leave-one-out cross-validation. The diagnostic accuracy of AI in discriminating between GISTs and leiomyomas was assessed and compared with that of blind reading by two expert endosonographers. RESULTS: Of the 53 patients, 42 had GISTs and 11 had leiomyomas. Mean tumor size was 26.4 mm. The consistency rate of the segment range of the tumor image extracted by SiamMask and marked by the endosonographer was 96% with a Dice coefficient. The sensitivity, specificity, and accuracy of AI in diagnosing GIST were 90.5%, 90.9%, and 90.6%, respectively, whereas those of blind reading were 90.5%, 81.8%, and 88.7%, respectively (P = 0.683). The κ coefficient between the two reviewers was 0.713. CONCLUSIONS: The diagnostic ability of CH-EUS results evaluated by AI to distinguish between GISTs and leiomyomas was comparable with that of blind reading by expert endosonographers.