A Recent Survey of the Advancements in Deep Learning Techniques for Monkeypox Disease Detection
SH Khan, R Iqbal, S Naz - arXiv preprint arXiv:2311.10754, 2023 - arxiv.org
Monkeypox is a zoonotic infectious disease induced by the Monkeypox virus, part of the
poxviridae orthopoxvirus group initially discovered in Africa and gained global attention in …
poxviridae orthopoxvirus group initially discovered in Africa and gained global attention in …
[HTML][HTML] Efficient pneumonia detection using Vision Transformers on chest X-rays
Pneumonia is a widespread and acute respiratory infection that impacts people of all ages.
Early detection and treatment of pneumonia are essential for avoiding complications and …
Early detection and treatment of pneumonia are essential for avoiding complications and …
[HTML][HTML] Enhanced gastric cancer classification and quantification interpretable framework using digital histopathology images
Recent developments have highlighted the critical role that computer-aided diagnosis (CAD)
systems play in analyzing whole-slide digital histopathology images for detecting gastric …
systems play in analyzing whole-slide digital histopathology images for detecting gastric …
[HTML][HTML] COVID-19 infection analysis framework using novel boosted CNNs and radiological images
COVID-19, a novel pathogen that emerged in late 2019, has the potential to cause
pneumonia with unique variants upon infection. Hence, the development of efficient …
pneumonia with unique variants upon infection. Hence, the development of efficient …
[HTML][HTML] MITER: Medical Image–TExt joint adaptive pretRaining with multi-level contrastive learning
Recently multimodal medical pretraining models play a significant role in automatic medical
image and text analysis that has wide social and economical impact in healthcare. Despite …
image and text analysis that has wide social and economical impact in healthcare. Despite …
Brain tumor MRI classification using a novel deep residual and regional CNN
Brain tumor classification is essential for clinical diagnosis and treatment planning. Deep
learning models have shown great promise in this task, but they are often challenged by the …
learning models have shown great promise in this task, but they are often challenged by the …
The role of llms in sustainable smart cities: Applications, challenges, and future directions
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living
standards, facilitating the rapid expansion of urban areas while efficiently managing …
standards, facilitating the rapid expansion of urban areas while efficiently managing …
[HTML][HTML] DBU-Net: Dual branch U-Net for tumor segmentation in breast ultrasound images
Breast ultrasound medical images often have low imaging quality along with unclear target
boundaries. These issues make it challenging for physicians to accurately identify and …
boundaries. These issues make it challenging for physicians to accurately identify and …
[HTML][HTML] Improving prediction of cervical cancer using KNN imputer and multi-model ensemble learning
T Aljrees - Plos one, 2024 - journals.plos.org
Cervical cancer is a leading cause of women's mortality, emphasizing the need for early
diagnosis and effective treatment. In line with the imperative of early intervention, the …
diagnosis and effective treatment. In line with the imperative of early intervention, the …
[HTML][HTML] Utilization of deep convolutional neural networks for accurate chest X-ray diagnosis and disease detection
Chest radiography is a widely used diagnostic imaging procedure in medical practice, which
involves prompt reporting of future imaging tests and diagnosis of diseases in the images. In …
involves prompt reporting of future imaging tests and diagnosis of diseases in the images. In …