OBJECTIVE: Modic changes (MCs) are the most prevalent classification system for describing intravertebral MRI signal intensity changes. However, interpreting these intricate MRI images is a complex and time-consuming process. This study investigates ...
OBJECTIVES: To develop and externally validate multiphase CT-based deep learning (DL) models for differentiating adrenal metastases from benign lesions.
BACKGROUND: Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammo...
BACKGROUND: The surgical resection of rectal carcinoma is associated with a high risk of permanent stoma rate. Primary anastomosis rate is suggested to be higher in robot-assisted and transanal total mesorectal excision, but permanent stoma rate is u...
South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde
Nov 6, 2023
BACKGROUND: Progressive interventions have recently improved programmatic outcomes in drug-resistant tuberculosis (DR-TB) care in South Africa (SA). Amidst these, a shorter regimen was introduced in 2017 with weak evidence, and has shown mixed result...
BMC medical informatics and decision making
Nov 6, 2023
OBJECTIVE: Using two three-dimensional U-Net architectures for myocardium structure extraction and a distance transformation algorithm specifically for the left circumflex artery, we have designed a fully automated algorithm for coronary artery label...
BACKGROUND: Risk of biochemical recurrence (BCR) in localised prostate cancer can be stratified using the 5-tier Cambridge Prognostic Group (CPG) or 3-tier European Association of Urology (EAU) model. Active surveillance is the current recommendation...
RATIONALE AND OBJECTIVES: To develop a fully automated deep-learning (DL) model using digital radiography (DR) with relatively high accuracy for predicting the efficacy of non-vascularized fibular grafting (NVFG) and identifying suitable patients for...
BACKGROUND: We aimed to construct and validate a deep learning (DL) radiomics nomogram using baseline and restage enhanced computed tomography (CT) images and clinical characteristics to predict the response of metastatic lymph nodes to neoadjuvant c...
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