[HTML][HTML] Gastrointestinal abnormality detection and classification using empirical wavelet transform and deep convolutional neural network from endoscopic images
With an intention to assist gastroenterologists, this work proposes an intelligent method to
classify alimentary canal diseases such as Barrett's, Esophagitis, Hemorrhoids, Polyps, and …
classify alimentary canal diseases such as Barrett's, Esophagitis, Hemorrhoids, Polyps, and …
Efficiency of transfer learning for abnormality detection using colonoscopy images: a critical analysis
S Mohapatra, GK Pati… - 2022 IEEE Fourth …, 2022 - ieeexplore.ieee.org
Colonoscopy is a procedure which helps the gastroenterologists to examine the lower
gastrointestinal (GI) region for any abnormal condition. Diagnosis of diseases in the lower GI …
gastrointestinal (GI) region for any abnormal condition. Diagnosis of diseases in the lower GI …
[HTML][HTML] Spatial-attention ConvMixer architecture for classification and detection of gastrointestinal diseases using the Kvasir dataset
AA Demirbaş, H Üzen, H Fırat - Health Information Science and Systems, 2024 - Springer
Gastrointestinal (GI) disorders, encompassing conditions like cancer and Crohn's disease,
pose a significant threat to public health. Endoscopic examinations have become crucial for …
pose a significant threat to public health. Endoscopic examinations have become crucial for …
Severity Grading of Ulcerative Colitis Using Endoscopy Images: An Ensembled Deep Learning and Transfer Learning Approach
Ulcerative colitis (UC) is a persistent condition necessitating prompt treatment to avert
potential complications. Detecting UC severity aids treatment decisions. The Mayo …
potential complications. Detecting UC severity aids treatment decisions. The Mayo …
Ensemble deep learning approach with attention mechanism for COVID-19 detection and prediction
Abstract New coronavirus (COVID-19), which first appeared in Wuhan City and is now
rapidly disseminating worldwide, may be predicted, diagnosed, and treated with the help of …
rapidly disseminating worldwide, may be predicted, diagnosed, and treated with the help of …
A Hybrid-Based Ensemble Learning Model and DNN for Automated Diagnosis of Brain Tumor from MRI Images
B Jehangir, SR Nayak - … Technology: Proceedings of Second IEPCCT 2021, 2021 - Springer
A brain tumor is a life-threatening condition that can disrupt the human body's normal
functioning. Manual detection of the type of tumor may be time-consuming and sometimes …
functioning. Manual detection of the type of tumor may be time-consuming and sometimes …
A Review of the Detection of Pulmonary Embolism from Computed Tomography Images Using Deep Learning Methods
MP Das, V Rohini - Ambient Intelligence in Health Care: Proceedings of …, 2022 - Springer
Medical imaging has been evolving at a steady pace generating enormous amounts of
health data, and the use of deep learning (DL) has helped a great deal in processing the …
health data, and the use of deep learning (DL) has helped a great deal in processing the …
Skeletal Bone Age Determination Using Deep Learning
CD Karthik, C Shrada, A Krishnamurthy - Ambient Intelligence in Health …, 2022 - Springer
In today's clinical diagnosis of dental patients, skeletal maturity assessment is a unique bio-
marker. The bone age assessment (BAA) method is use to identify endocrinological as well …
marker. The bone age assessment (BAA) method is use to identify endocrinological as well …
Classification of Skin Lesions Using Deep Convolutional Neural Network
The melanoma is a type of skin cancer which develops from melanocytes, responsible to
provide the skin color. The severity of melanoma cancer is defined on the basis of different …
provide the skin color. The severity of melanoma cancer is defined on the basis of different …