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http://dx.doi.org/10.1136/gutjnl-2018-317573 | DOI Listing |
Sci Rep
December 2024
Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Canada.
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for classifying oral lesions, focusing on accuracy, interpretability, and reducing dataset bias.
View Article and Find Full Text PDFHealth Inf Sci Syst
December 2025
Department of Electrical Engineering, Iqra National University, Peshawar, 25000 Pakistan.
Leukemia, a life-threatening form of cancer, poses a significant global health challenge affecting individuals of all age groups, including both children and adults. Currently, the diagnostic process relies on manual analysis of microscopic images of blood samples. In recent years, machine learning employing deep learning approaches has emerged as cutting-edge solutions for image classification problems.
View Article and Find Full Text PDFBMC Med Inform Decis Mak
December 2024
Intelligent System Research Group, Faculty of Computer Science Universitas Sriwijaya, Palembang, 30139, Indonesia.
Background: Automatic classification of arrhythmias based on electrocardiography (ECG) data faces several significant challenges, particularly due to the substantial volume of clinical data involved in ECG signal analysis. The volume of clinical data has increased considerably, especially with the emergence of new clinical symptoms and signs in various arrhythmia conditions. These symptoms and signs, which serve as distinguishing features, can number in the tens of thousands.
View Article and Find Full Text PDFWorld J Gastroenterol
December 2024
School of Computer Science Technology, Changchun University, Changchun 130022, Jilin Province, China.
Background: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has been propelled by advancements in medical imaging technology. However, the complexity of the digestive tract structure, and the diversity of lesion types, results in different sites and types of lesions distinctly appearing in the images, posing a challenge for the accurate identification of digestive tract diseases.
Aim: To propose a deep learning-based lesion detection model to automatically identify and accurately label digestive tract lesions, thereby improving the diagnostic efficiency of doctors, and creating significant clinical application value.
Biomed Res Int
December 2024
Department of Biomedical Engineering, Ziauddin University, Faculty of Engineering, Science, Technology and Management (ZUFESTM), Karachi, Pakistan.
Vitiligo is a chronic skin damage disease, triggered by differential melanocyte death. Vitiligo (0.5%-1% of the population) is one of the most severe skin conditions.
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