Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Accurate three-dimensional (3D) nuclear instance segmentation is a prerequisite for quantitative phenotyping in volumetric microscopy, yet remains challenging in densely packed tissues, irregular nuclear morphologies, and across heterogeneous imaging modalities. Here we present NucVerse3D, a deep-learning framework for generalized 3D nuclei instance segmentation that combines a residual attention ...
Contrast-enhanced CT is commonly used in the evaluation of hepatic metastatic lesions. This prospective study aimed to assess the capability of artificial intelligence iterative reconstruction (AIIR) in low-dose CT for detection of hepatic metastases. Thirty-two patients with hepatic metastases were enrolled and underwent dual-phase CT scans in the venous phase. Each patient received a standard-do...
OBJECTIVES: Depth of stromal invasion (DSI) is a key prognostic factor significantly influencing treatment decisions in early-stage cervical cancer (E...
Inflammatory breast cancer (IBC) is a rare yet highly aggressive subtype of breast cancer, characterized by distinct clinical features, rapid progress...
Endometrial cancer (EC) incidence is rising, yet current diagnostics lack precision and scalability. We develop an artificial intelligence (AI)-based ...
PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study eval...
Crotonylation is a lysine acylation modification that links cellular metabolism to epigenetic regulation. Its rigid planar crotonyl group is specifica...
Micropeptides are emerging as a previously hidden layer of the human proteome, redefining the long-standing separation between coding and noncoding ge...
BACKGROUND: Sybil is a deep learning model designed to predict future lung cancer risk based on a single low-dose chest CT (LDCT) scan, facilitating a...
Pancreatic cystic lesions are increasingly detected due to the widespread use of high-resolution cross-sectional imaging, particularly MRI and CT. The...
Small tissue biopsies, including renal core biopsies, bone marrow trephines, gastrointestinal endoscopic samples, prostate needle cores, liver biopsie...
PURPOSE OF REVIEW: Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, producing durable responses across multiple malignancies. Howe...
BACKGROUND: Clinical notes are the most abundant data type within electronic health records; however, their highly unstructured format presents signif...
BACKGROUND: Eligibility criteria are essential to clinical trial design, guiding recruitment, and ensuring patient safety and scientific rigor. Howeve...
Papillary thyroid carcinoma (PTC) is the most prevalent thyroid malignancy and its incidence continues to rise. Although prognosis is generally favora...
INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems a...
The assessment of tumor-infiltrating lymphocyte (TILs), together with gene expression signatures (GES), has the potential to guide personalized breast...
Brain tumor segmentation from multi-modal MRI scans remains challenging due to the heterogeneity of tumors, intensity variations, and different protoc...
Cancer arises from oncogenic clones, yet the dynamic mechanisms driving their stepwise evolution toward malignancy remain incompletely understood. Her...