Latest AI and machine learning research in breast cancer for healthcare professionals.
Summarize functional outcomes after transoral robotic surgery (TORS) ± adjuvant therapy for oropharyngeal cancer (OPC). A systematic review was conducted. The MEDLINE database was searched (MeSH terms: TORS, pharyngeal neoplasms, oropharyngeal neoplasms). Peer-reviewed human subject papers published through December 2013 were included. Exclusion criteria were as follows: (1) case report design (n ...
Virtual staining aims to computationally generate target-stained histopathological images while reducing the cost and time associated with conventional staining procedures. However, existing methods rely predominantly on strictly paired and accurately registered training data, which are difficult and expensive to obtain in routine practice. To reduce this dependence, we propose a stable semi-super...
In large data sets discovery is often limited to pre-conceived hypotheses and data fishing. Here we tested whether systematic exploration of AI genera...
Chimeric antigen receptor (CAR) cell therapy has achieved transformative clinical success through targeting of CD19 in refractory B cell malignancies,...
PurposeThe 11 Integrative Cluster (IntClust) genomic subtypes of breast cancer have both prognostic and predictive value but require integrated DNA co...
Objective: Accurate volumetric analysis of the brain and cerebrospinal fluid (CSF) is essential for monitoring hydrocephalus, a significant pediatric ...
Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with a median overall survival of 15 months. Longitudinal, multi-modal imagin...
Background. Residual cancer burden (RCB) after neoadjuvant chemotherapy (NAC) offers finer prognostic stratification than binary pathologic complete r...
Motivation: Disease mechanisms emerge from the coordinated activity of multiple biological pathways, rather than from individual pathways acting in is...
Multimodal Large Language Models (MLLMs) can generate pathological descriptions from histological images, but gigapixel Whole Slide Images (WSIs) exce...
Breast lesion detection in mammography remains a challenging task due to variations in image quality, lesion appearance, and population demographics a...
Breast cancer (BC) is the second most common noncutaneous cancer and the second leading cause of cancer-related death in women. BC is classified into ...
Four-dimensional cone beam CT (4D CBCT) is important for image-guided radiation therapy of thoracic cancers, but its use is limited by long scan times...
Pathology foundation models (PFMs) provide strong tissue representations and have become central to digital pathology. However, deployment in disease-...
Background. Pediatric musculoskeletal trauma represents up to 18% of pediatric ED visits, yet diagnosis still depends on ionizing radiography. Cumulat...
Multimodal learning is a robust approach to improve predictive performance in applications such as medical prognosis. However, the clinical applicabil...
Minimally invasive endovascular procedures offer reduced surgical trauma, shorter recovery times, and improved outcomes, but rely on 2D fluoroscopic X...
Brain tumor progression exhibits spatially heterogeneous growth, patient-specific treatment response, and complex interactions with surrounding anatom...
Next-generation sequencing technologies, including RNA-sequencing, provide genome-wide measurements of gene expression and enable broad explorations o...
Weakly supervised whole-slide image (WSI) classification is widely used in computational pathology because slide-level labels are easier to obtain tha...