[HTML][HTML] BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions

FM Calisto, C Santiago, N Nunes… - Artificial Intelligence in …, 2022 - Elsevier
In this paper, we developed BreastScreening-AI within two scenarios for the classification of
multimodal beast images:(1) Clinician-Only; and (2) Clinician-AI. The novelty relies on the …

A hybrid workflow of residual convolutional transformer encoder for breast cancer classification using digital X-ray mammograms

RM Al-Tam, AM Al-Hejri, SM Narangale, NA Samee… - Biomedicines, 2022 - mdpi.com
Breast cancer, which attacks the glandular epithelium of the breast, is the second most
common kind of cancer in women after lung cancer, and it affects a significant number of …

Brain tumor segmentation based on the dual-path network of multi-modal MRI images

L Fang, X Wang - Pattern Recognition, 2022 - Elsevier
Because of the tumor with infiltrative growth, the glioma boundary is usually fused with the
brain tissue, which leads to the failure of accurately segmenting the brain tumor structure …

Selecting the optimal transfer learning model for precise breast cancer diagnosis utilizing pre-trained deep learning models and histopathology images

A Ravikumar, H Sriraman, B Saleena, B Prakash - Health and Technology, 2023 - Springer
Abstract Background Every year, around 1.5 million women worldwide receive a breast
cancer diagnosis, which is why the mortality rate for women is rising. Scientists have …

[HTML][HTML] Breast cancer detection and localizing the mass area using deep learning

MM Rahman, MZB Jahangir, A Rahman… - Big Data and Cognitive …, 2024 - mdpi.com
Breast cancer presents a substantial health obstacle since it is the most widespread invasive
cancer and the second most common cause of death in women. Prompt identification is …

ETECADx: Ensemble self-attention transformer encoder for breast cancer diagnosis using full-field digital X-ray breast images

AM Al-Hejri, RM Al-Tam, M Fazea, AH Sable, S Lee… - Diagnostics, 2022 - mdpi.com
Early detection of breast cancer is an essential procedure to reduce the mortality rate among
women. In this paper, a new AI-based computer-aided diagnosis (CAD) framework called …

Multimodal breast cancer hybrid explainable computer-aided diagnosis using medical mammograms and ultrasound Images

RM Al-Tam, AM Al-Hejri, SS Alshamrani… - Biocybernetics and …, 2024 - Elsevier
Breast cancer is a prevalent global disease where early detection is crucial for effective
treatment and reducing mortality rates. To address this challenge, a novel Computer-Aided …

Convergence of various computer-aided systems for breast tumor diagnosis: a comparative insight

SK Singh, KS Patnaik - Multimedia Tools and Applications, 2024 - Springer
Breast Cancer, with an expected 42,780 deaths in the US alone in 2024, is one of the most
prevalent types of cancer. The death toll due to breast cancer would be very high if it were to …

Breast Cancer Classification with Enhanced Interpretability: DALAResNet50 and DT Grad-CAM

S Liu, GMS Himel, J Wang - IEEE Access, 2024 - ieeexplore.ieee.org
Automatic classification of breast cancer in histopathology images is crucial for accurate
diagnosis and effective treatment planning. Recently, classification methods based on the …

A Multimodal Transfer Learning Approach using PubMedCLIP for Medical Image Classification

HN Dao, T Nguyen, C Mugisha, I Paik - IEEE Access, 2024 - ieeexplore.ieee.org
Medical image data often face the problem of data scarcity and costly annotation processes.
To overcome this, our study introduces a novel transfer learning method for medical image …