Abstract: Cervical cancer is one of the most common causes of mortality among women globally. Development of accurate, interpretable and clinically deployable automated systems for detection of ...
Abstract: Cervical cancer, a prominent contributor to mortality in low-income countries, can often be effectively treated if detected early through the removal of affected tissues. Automating the ...
Deep learning CNN for automated cervical cancer detection using Pap smear images, with Streamlit deployment & Grad‑CAM. This project implements a deep learning Convolutional Neural Network (CNN) for ...
Objective: This study aims to develop and evaluate an artificial intelligence-based model for cervical cancer subtyping using whole-slide images (WSI), incorporating both patch-level and WSI-level ...
The recommendation comes after the first at-home test, a self-swab, received federal approval last year. By Nina Agrawal An agency under the U.S. Department of Health and Human Services endorsed an ...
Melanoma remains one of the hardest skin cancers to diagnose because it often mimics harmless moles or lesions. While most artificial intelligence (AI) tools rely on dermoscopic images alone, they ...
Talk about a breath of fresh air. Researchers have developed a groundbreaking device that may one day make detecting lung cancer as easy as exhaling. “We built a screening tool that could allow ...
Cervical cancer, one of the most common female cancers, can be detected with computed tomography (CT) and magnetic resonance imaging (MRI). Computer-aided diagnosis (CAD) methods based on artificial ...
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