Iron deficiency (ID) is a well-known cause of anaemia and could lead to adverse clinical and functional impairments. However, ID is under-diagnosed due to non-specific symptoms, difficulties in interpreting ambiguous assessment outcomes and suboptima...
The need to reduce the number of embryos transferred in assisted reproductive care to prevent multiple gestations has led to a stronger emphasis on selecting embryos with the highest morphological quality. Although this evaluation has traditionally b...
Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, and its early detection and accurate grading play a crucial role in clinical intervention. To address the dual limitations of existing methods in multi-scale lesions feature fusion ...
Sign language (SL) is a non-verbal language applied by deaf and hard-of-hearing individuals for daily communication between them. Studies in SL recognition (SLR) have recently become essential developments. The current successes present the base for ...
The lengthy 1 h dynamic positron emission tomography (PET) scans discomfort patients, add motion artifacts, and inflate costs, highlighting the need for tech advancements to reduce scan times. Therefore, we attempted to reconstruct multi-parametric i...
Electrocardiograms (ECGs) contain valuable information in the clinical diagnosis of myocardial infarction (MI). However, its interpretation process is dependent on cardiologists with extensive clinical experience and expertise. The issue not only cau...
The goal of this study is to improve the quality and diversity of text paraphrase generation, a critical task in Natural Language Generation (NLG) that requires producing semantically equivalent sentences with varied structures and expressions. Exist...
The evolution of Large Language Models (LLMs) has significantly advanced artificial intelligence, driving innovation across various applications. Their continued development relies on a deep understanding of their capabilities and limitations. This i...
Time-series momentum (TSMOM) trading strategies manage positions based on the persistence of return trends. Although long short-term memory (LSTM) deep neural architectures can enhance TSMOM, their performance often deteriorates during abrupt market ...
Purpose Prediction of the ectasia screening index, an estimator provided by the Casia2 instrument for identifying keratoconus, from raw optical coherence tomography data using convolutional neural networks. Methods Three convolutional neural networks...
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