Accurate segmentation of gastric cavities from ultrasound images remains a challenging task due to the presence of ultrasound shadow and varying anatomical structures. To address these challenges, we collected a Gastric Ultrasound Image (GUSI) datase...
Alpha-thalassemia is a widespread genetic disorder, and accurately distinguishing between alpha-plus (α⁺) and alpha-zero (α⁰) types is critical for effective screening and management. This study developed and evaluated machine learning models to clas...
The emergence of large foundation models (FMs) in histopathology, trained on extensive image datasets using high-performance graphics processing unit (GPU) clusters, has demonstrated significant potential in advancing computational pathology. FMs hav...
Precise segmentation of brain tumors is essential for efficient diagnosis and therapy planning. While current automated methods frequently fail to capture complicated tumor shapes, traditional manual methods are laborious, subjective, and unpredictab...
Respiratory ailments constitute various pathological conditions affecting the respiratory system, including the airways, pulmonary tissues, and associated structures. When these conditions are left untreated or inadequately managed, they can result i...
Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic performance. Educational evaluation is an important part of the teaching process, and the traditional ev...
In this study, we introduce a machine learning optimized graphene-based biosensor tailored for the early and accurate detection of breast cancer, aiming to elevate diagnostic reliability and clinical efficacy. The device employs a multilayer Ag-SiO₂-...
Visually impaired people generally face many troubles in their everyday lives, and technical involvement might help them perform these tasks. Object detection is a significant aspect of computer vision (CV) and machine learning (ML), which plays a su...
Endometriosis (EMs) and recurrent miscarriage (RM) represent major reproductive health challenges. This study investigates the involvement of endothelial-mesenchymal transition (EndMT) in these conditions through integrative bioinformatics analysis, ...
In recent years, Hand Gesture Recognition (HGR) devices have been designed to recognize gestures in real time using machine-learning classifiers (MLCs). However, the performance of these classifiers heavily relies on the tuning of their hyperparamete...
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