With cardiovascular diseases accounting for all other causes of mortality worldwide, an increasing proportion of individuals are being treated for them. To identify the cardiac issue, medical practitioners have to examine electrocardiogram (ECG) data...
Accurate classification of pear varieties is crucial for enhancing agricultural efficiency and ensuring consumer satisfaction. In this study, Bayesian optimized (BO) deep learning is utilized to identify and classify nine types of pears from 43,200 i...
Breast cancer remains a formidable global health challenge, emphasizing the critical importance of accurate and early diagnosis for improved patient outcomes. In recent years, machine learning, particularly deep learning, has shown substantial promis...
Diabetic retinopathy is a leading cause of vision loss, necessitating early, accurate detection. Automated deep learning models show promise but struggle with the complexity of retinal images and limited labeled data. Due to domain differences, tradi...
Robotic surgery has now been widely applied in the treatment of colorectal cancer (CRC), driving significant growth in related research activities. This study aims to reveal the research hotspots, emerging frontiers, and future research trends in the...
Mango is a fruit of great economic importance in India. India is the top mango-producing nation in the world, accounting for over half of global mango output. In order to determine the production capability of the insured orchards, a complete invento...
This study presents a novel deep learning (DL) framework, the Deep Neural Frailty Competing Risks (DNFCR) model, which simultaneously integrates frailty and competing risks (CR) for mortality prediction in heart failure (HF). While existing models li...
Prostate cancer remains a leading cause of mortality, necessitating precise histopathological segmentation for accurate Gleason Grade assessment. However, existing deep learning-based segmentation models lack contextual awareness and explainability, ...
Monitoring mean arterial pressure (MAP) is essential for ensuring safe general anesthesia. Current practices rely either on non-invasive cuff measurements, which suffer from poor temporal resolution, or invasive arterial lines, which provide excellen...
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