BACKGROUND: Current ultrasound-based screening for endometrial cancer (EC) primarily relies on endometrial thickness (ET) and morphological evaluation, which suffer from low specificity and high interobserver variability. This study aimed to develop ...
Evaluating cumulus-oocyte complex (COC) morphology is commonly used to assess oocyte quality. However, clear guidelines on interpreting COC morphology data are lacking as this evaluation method is subjective. In the present study, individual in vitro...
Breast cancer is the second leading cause of cancer-related deaths among women, following lung cancer, as of 2024. Conventional cancer diagnosis relies on the manual examination of biopsied tissues by pathologists, a time-consuming process that may v...
Oral cancer is a hazardous disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop the deep convolutional neural networks (CNN)-based multiclass classification and object detection models for distingui...
Deep learning techniques, particularly Convolutional Neural Networks (CNNs), have been widely recognized as effective tools for facial expression recognition applications. The accuracy of facial expression recognition application requires further enh...
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...
The developing elderly population undergoes a high level of eyesight and mental impairment, which frequently results in a defeat of independence. That kind of person should do vital daily tasks like heating and cooking, with methods and devices inten...
In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. Conversely, Mamba, a novel network framework, effectively captures long-range feature dependencies and e...
The Forced Swim Test (FST) is a widely used preclinical model for assessing antidepressant efficacy, studying stress response, and evaluating depressive-like behaviours in rodents. Over the last 10 years, more than 5500 scientific articles reporting ...
Fine-grained visual classification is fundamental for medical image applications because it detects minor lesions. Diabetic retinopathy (DR) is a preventable cause of blindness, which requires exact and timely diagnosis to prevent vision damage. The ...
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