Monkeypox diagnosis with interpretable deep learning
As the world gradually recovers from the impacts of COVID-19, the recent global spread of
Monkeypox disease has raised concerns about another potential pandemic, highlighting the …
Monkeypox disease has raised concerns about another potential pandemic, highlighting the …
An attention-fused architecture for brain tumor diagnosis
A Hekmat, Z Zhang, SUR Khan, I Shad… - … Signal Processing and …, 2025 - Elsevier
To enhance the accuracy of brain tumor diagnosis and treatment, reliance on MRI images is
crucial. However, human error in manual diagnosis remains a concern, underscoring the …
crucial. However, human error in manual diagnosis remains a concern, underscoring the …
Exploiting histopathological imaging for early detection of lung and colon cancer via ensemble deep learning model
Cancer seems to have a vast number of deaths due to its heterogeneity, aggressiveness,
and significant propensity for metastasis. The predominant categories of cancer that may …
and significant propensity for metastasis. The predominant categories of cancer that may …
Transfer learning and local interpretable model agnostic based visual approach in monkeypox disease detection and classification: A deep learning insights
The recent development of Monkeypox disease among various nations poses a global
pandemic threat when the world is still fighting Coronavirus Disease-2019 (COVID-19). At its …
pandemic threat when the world is still fighting Coronavirus Disease-2019 (COVID-19). At its …
An Enhanced Technique of COVID‐19 Detection and Classification Using Deep Convolutional Neural Network from Chest X‐Ray and CT Images
Background. Coronavirus disease (COVID‐19) is an infectious illness that spreads widely
over a short period of time and finally causes a pandemic. Unfortunately, the lack of …
over a short period of time and finally causes a pandemic. Unfortunately, the lack of …
Distinguishing bronchoscopically observed anatomical positions of airway under by convolutional neural network
C Chen, FJF Herth, Y Zuo, H Li… - … in Chronic Disease, 2023 - journals.sagepub.com
Background: Artificial intelligence (AI) technology has been used for finding lesions via
gastrointestinal endoscopy. However, there were few AI-associated studies that discuss …
gastrointestinal endoscopy. However, there were few AI-associated studies that discuss …
Multimodal Deep Convolutional Neural Network Pipeline for AI-Assisted Early Detection of Oral Cancer
Oral Squamous Cell Carcinoma (OSCC) poses a significant health challenge, with early
detection being crucial for effective treatment and improved survival rates. While previous …
detection being crucial for effective treatment and improved survival rates. While previous …
Skin lesion segmentation using deep learning algorithm with ant colony optimization
Background Segmentation of skin lesions remains essential in histological diagnosis and
skin cancer surveillance. Recent advances in deep learning have paved the way for greater …
skin cancer surveillance. Recent advances in deep learning have paved the way for greater …
Machine learning and new insights for breast cancer diagnosis
Y Guo, H Zhang, L Yuan, W Chen… - Journal of …, 2024 - journals.sagepub.com
Breast cancer (BC) is the most prominent form of cancer among females all over the world.
The current methods of BC detection include X-ray mammography, ultrasound, computed …
The current methods of BC detection include X-ray mammography, ultrasound, computed …
A multi‐stage fusion framework to classify breast lesions using deep learning and radiomics features computed from four‐view mammograms
Background Developing computer aided diagnosis (CAD) schemes of mammograms to
classify between malignant and benign breast lesions has attracted a lot of research …
classify between malignant and benign breast lesions has attracted a lot of research …