BACKGROUND: BRAF mutation is the most common genetic change in papillary thyroid carcinoma (PTC). Nevertheless, the association between BRAF mutation status and abundance and the biological behavior of PTC is unclear. Thus, this study investigated wh...
BACKGROUND: Understanding the BRAF alterations preoperatively could remarkably assist in predicting tumor behavior, which leads to a more precise prognostication and management strategy. Recent advances in artificial intelligence (AI) have resulted i...
International journal of computer assisted radiology and surgery
Feb 15, 2025
OBJECTIVE: BRAF is the most common mutation found in thyroid cancer and is particularly associated with papillary thyroid carcinoma (PTC). Currently, genetic mutation detection relies on invasive procedures. This study aimed to extract radiomic featu...
BACKGROUND: Informative biomarkers play a vital role in guiding clinical decisions regarding management of cancers. We have previously demonstrated the potential of a deep convolutional neural network (CNN) for predicting cancer driver gene mutations...
AJNR. American journal of neuroradiology
Jun 7, 2024
BACKGROUND AND PURPOSE: Molecular biomarker identification increasingly influences the treatment planning of pediatric low-grade neuroepithelial tumors (PLGNTs). We aimed to develop and validate a radiomics-based ADC signature predictive of the molec...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 12, 2024
BACKGROUND: The KRAS, NRAS, and BRAF genotypes are critical for selecting targeted therapies for patients with metastatic colorectal cancer (mCRC). Here, we aimed to develop a deep learning model that utilizes pathologic whole-slide images (WSIs) to ...
The histopathological classification of melanocytic tumours with spitzoid features remains a challenging task. We confront the complexities involved in the histological classification of these tumours by proposing machine learning (ML) algorithms tha...
Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, genetic subtypes, and mutations associated with CRC is crucial for precision medicine. However, traditional measurement techniques such as gene sequen...
Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other biomarkers with high performance and whether DL predictions genera...
objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with aggressive biologic behavior. Predicting promoter mutation is thus necessary for the prognostic strati...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.