Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Fast and accurate organ-at-risk (OAR) and gross tumor volume (GTV) contour propagation methods are needed to improve the efficiency of magnetic resonance (MR) imaging-guided radiotherapy. We trained deformable image registration networks to accurately propagate contours from planning to fraction MR images. Approach: Data from 140 stage 1-2 lung cancer patients treated at a 0.35T MR-Linac were ...
OBJECTIVES: Post-surgical prediction of recurrence or metastasis for primary gastrointestinal stromal tumors (GISTs) remains challenging. We aim to develop individualized clinical follow-up strategies for primary GIST patients, such as shortening follow-up time or extending drug administration based on the clinical deep learning radiomics model (CDLRM).
An external validation of IAIA-BL-a deep-learning based, inherently interpretable breast lesion malignancy prediction model-was performed on two patie...
Proteolysis targeting chimeras (PROTACs) have emerged as a groundbreaking class of anticancer therapeutics. These bifunctional molecules harness the e...
INTRODUCTION: Image preprocessing is crucial for optimizing radiomics feature extraction, however, inconsistencies in the implementation process and a...
BACKGROUND AND OBJECTIVE: Accurate staging of keratoconus (KC) is crucial for timely intervention and improving patient quality of life. Unlike prior ...
BACKGROUND: Differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) is essential for selecting the most effective tr...
UNLABELLED: Growing research evidence indicates a substantial influence of the intra-tumor microbiome on tumor outcome. However, there is currently no...
() is an oral commensal bacterium that can become pathogenic and is associated with periodontitis, adverse pregnancy outcomes, and colorectal cancer ...
Purpose To develop and evaluate an open-source deep learning model for detection and localization of breast cancer on MRI. Materials and Methods In t...
Monoclonal Antibodies and Breast Cancer Research (MABCR) has progressed substantially, particularly in the areas of HER2-positive and triple-negative ...
IMPORTANCE: Although tumor-infiltrating lymphocytes (TILs) have been implicated as prognostic biomarkers across various malignancies, the clinical app...
Contemporary surgical pathology workflows often prioritize slide examination based on case registry order rather than patient risk level. As a result,...
PURPOSE: This study aims to provide a national-level insight into the optimal management of spinal chordoma, a type of rare and complicated malignancy...
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors of the urinary system. Protein acetylation plays a key ...
OBJECTIVE: To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining Transformer and graph attention networks for class...
UNLABELLED: Spinal tumors represent 15% of all central nervous system malignancies, with intramedullary spinal cord tumors (IMSCTs) being rare. Predom...
With the rapid development of modern medical technology,minimally invasive surgical procedures are playing an increasingly important role in the field...
BACKGROUND: The leiomyosarocma (LMS) is the most common soft tissue sarcoma, and its molecular subtypes were identified with therapeutic sensitivity a...
Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-being of patients and develop customized therapeutic ...