Abstract DNA functional group classification across species plays a crucial role in understanding genetic diversity, evolutionary relationships and biological function. The increasing availability of genomic data has led to the use of machine learning and deep learning methods fo…
The precision and early detection of subtypes of acute lymphoblastic leukaemia (ALL) in peripheral blood smear images are crucial for efficient clinical practice. Traditional deep learning methods tend to be challenging in terms of model interpretation and are often reliant on la…
Assessment of the Ulcerative Colitis Endoscopic Index of Severity (UCEIS) is limited by subjectivity and interobserver variability. We developed UC-MTLNet, a multi-task deep learning model to predict UCEIS descriptors, total score, endoscopic remission, and severity strata. This…
Abstract The fusion multi-sensory system with optimized deep learning and machine learning algorithms appeared to synergize difficult paradigms in precision agriculture and boost recognition of various plant species. In this study, an electronic nose (E-nose) system with eight MO…
Abstract The evaluation of automotive sound quality is of considerable significance for improving driving comfort. However, existing methodologies suffer from notable limitations, including inconsistencies in subjective evaluations and weak correlations between objective metrics…
On social media platforms, users share their thoughts and opinions through comments in multiple languages, including English and Amharic, resulting in vast amounts of data. Accurately interpreting and understanding these comments has important practical implications, with potenti…