The identification of cancerous tissues remains challenging due to the complexity of experimental methods and low identification accuracy rates. Therefore, this paper proposes a rapid identification method. We introduce a new theoretical transmission...
Scene categorization is the dominant proxy for visual understanding, yet humans can perform a large number of visual tasks within any scene. Consequently, we know little about how different tasks change how a scene is processed, represented, and its ...
OBJECTIVES: Dental caries remains a significant global health concern. Recognising the diagnostic potential of cone-beam computed tomography (CBCT) in caries assessment, this study aimed to develop an artificial intelligence (AI)-driven tool for accu...
N-7 methylguanosine (m7G) is an important RNA modification that plays a key role in regulating gene expression and cellular physiological functions. Medical research has shown that m7G is closely associated with the development of a variety of diseas...
In this study, we evaluate the performance of four deep learning models, EfficientNetB0, ResNet50, DenseNet121, and InceptionV3, for the classification of citrus diseases from images. Extensive experiments were conducted on a dataset of 759 images di...
The exploration of deep learning techniques for predicting various biological characteristics of endometrial cancer (EC) is of significant importance. The objective of this study was to develop an optimized radiomics scheme combining multiparametric ...
OBJECTIVE: This study evaluates the performance of various classifiers and pre-trained models for dental implant state classification using preprocessed radiography images with masks.
BMC medical informatics and decision making
Apr 11, 2025
BACKGROUND: Thyroid nodules are frequent in clinical settings, and their diagnosis in adults is growing, with some persons experiencing symptoms. Ultrasound-guided thermal ablation can shrink nodules and alleviate discomfort. Because the degree and r...
To address the public health issue of renal failure and the global shortage of nephrologists, an AI-based system has been developed to automatically identify kidney diseases. Recent advancements in machine learning, deep learning (DL), and artificial...
Early detection of lung nodules is crucial for the prevention and treatment of lung cancer. However, current methods face challenges such as missing small nodules, variations in nodule size, and high false positive rates. To address these challenges,...
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