PURPOSE: To investigate the value of deep learning (DL) in T2-weighted imaging (T2) of the bladder regarding acquisition time (TA), image quality, and diagnostic confidence compared to standard T2-weighted turbo-spin-echo (TSE) imaging (T2).
PURPOSE: To develop and validate a deep learning-based feature ensemble model using multiparametric magnetic resonance imaging (MRI) for predicting tumor budding (TB) grading in patients with rectal cancer (RC).
Artificial intelligence (AI) may have the potential to improve existing diagnostic challenges in endometriosis imaging. To better direct future research, this descriptive review summarizes the general landscape of AI applications in endometriosis ima...
Multiple instance learning (MIL) has been successfully applied for whole slide images (WSIs) analysis in computational pathology, enabling a wide range of prediction tasks from tumor subtyping to inferring genetic mutations and multi-omics biomarkers...
RATIONALE AND OBJECTIVES: To construct and validate an interpretable machine learning (ML) radiomics model derived from multiparametric magnetic resonance imaging (MRI) images to differentiate between luminal and non-luminal breast cancer (BC) subtyp...
The most widespread kind of cancer, affecting millions of lives is skin cancer. When the condition of illness worsens, the chance of survival is reduced, and thus detection of skin cancer is extremely difficult. Hence, this paper introduces a new mod...
Medical & biological engineering & computing
Mar 31, 2025
Retinal artery occlusion (RAO) is a sight-threatening condition that requires prompt diagnosis to prevent irreversible vision loss. This study presents an innovative AI-driven approach for RAO detection from fundus images, marking the first applicati...
Skin cancer is a deadly disease and has the highest rising rates globally. It arises from aberrant skin cells, which are often caused by prolonged exposure to ultraviolet rays from sunlight or artificial tanning devices. Dermatologists rely on visual...
The international journal of cardiovascular imaging
Mar 31, 2025
Accurate interpretation of echocardiography measurements is essential for diagnosing cardiovascular diseases and guiding clinical management. The emergence of large language models (LLMs) like ChatGPT presents a novel opportunity to automate the gene...
BMC medical informatics and decision making
Mar 31, 2025
Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imbalance, and computat...
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