Explainable deep learning methods in medical image classification: A survey
The remarkable success of deep learning has prompted interest in its application to medical
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …
Deep learning based image processing for robot assisted surgery: a systematic literature survey
The recent advancements in the surging field of Deep Learning (DL) have revolutionized
every sphere of life, and the healthcare domain is no exception. The enormous success of …
every sphere of life, and the healthcare domain is no exception. The enormous success of …
Background selection schema on deep learning-based classification of dermatological disease
J Zhou, Z Wu, Z Jiang, K Huang, K Guo… - Computers in Biology and …, 2022 - Elsevier
Skin diseases are one of the most common ailments affecting humans. Artificial intelligence
based on deep learning can significantly improve the efficiency of identifying skin disorders …
based on deep learning can significantly improve the efficiency of identifying skin disorders …
RCS-YOLO: A fast and high-accuracy object detector for brain tumor detection
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks
have become one of the most efficient algorithms for object detection. However, the …
have become one of the most efficient algorithms for object detection. However, the …
Out-of-distribution generalized dynamic graph neural network for human albumin prediction
Human albumin is essential for indicating the body's overall health. Accurately predicting
plasma albumin levels and determining appropriate doses are urgent clinical challenges …
plasma albumin levels and determining appropriate doses are urgent clinical challenges …
A novel approach in bio-medical image segmentation for analyzing brain cancer images with U-NET semantic segmentation and TPLD models using SVM
SNJ Eali, D Bhattacharyya, TR Nakka… - Traitement Du …, 2022 - search.proquest.com
Many medical applications need to be able to separate and find brain tumor's using CT scan
images. There have been a lot of recent studies that used distinguish between benign and …
images. There have been a lot of recent studies that used distinguish between benign and …
A hierarchical self‐attention‐guided deep learning framework to predict breast cancer response to chemotherapy using pre‑treatment tumor biopsies
Background Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC)
has demonstrated a strong correlation to improved survival in breast cancer (BC) patients …
has demonstrated a strong correlation to improved survival in breast cancer (BC) patients …
Medical image segmentation using levit-unet++: A case study on gi tract data
Gastro-Intestinal Tract cancer is considered a fatal malignant condition of the organs in the
GI tract. Due to its fatality, there is an urgent need for medical image segmentation …
GI tract. Due to its fatality, there is an urgent need for medical image segmentation …
Explainable deep learning methods in medical imaging diagnosis: a survey
The remarkable success of deep learning has prompted interest in its application to medical
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …
Classification of companion animals' ocular diseases: Domain adversarial learning for imbalanced data
MG Nam, SY Dong - IEEE Access, 2023 - ieeexplore.ieee.org
In contrast to the widespread implementation of computer-aided diagnosis of human
diseases, the limited availability of veterinary image datasets has hindered its application in …
diseases, the limited availability of veterinary image datasets has hindered its application in …