AIMC Topic: Tomography, X-Ray Computed
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Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer.
BMC cancer
Feb 7, 2025
BACKGROUND: Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after surgery, which is an important cause of death in postoperative patients. Therefore, it is particularly important to find a suitable way to predict the r...
Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses.
Nature communications
Feb 7, 2025
Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. We analyze 132...
TQGDNet: Coronary artery calcium deposit detection on computed tomography.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 6, 2025
Coronary artery disease (CAD) continues to be a leading global cause of cardiovascular related mortality. The scoring of coronary artery calcium (CAC) using computer tomography (CT) images is a diagnostic instrument for evaluating the risk of asympto...
Aligning large language models with radiologists by reinforcement learning from AI feedback for chest CT reports.
European journal of radiology
Feb 6, 2025
BACKGROUND: Large language models (LLMs) often struggle to fully capture the nuanced preferences and clinical judgement of radiologists in medical report summarization even when fine-tuned on massive medical reports. This could lead to the generated ...
Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.
BMC medical imaging
Feb 6, 2025
BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from chronic VCFs is vital for treatment planning, but MRI, the gold standard, is inaccessible for some. Ho...
A comparison of different machine learning classifiers in predicting xerostomia and sticky saliva due to head and neck radiotherapy using a multi-objective, multimodal radiomics model.
Biomedical physics & engineering express
Feb 6, 2025
. Although radiotherapy techniques are a primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity and side effects. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on featu...
Hypernetwork-Based Physics-Driven Personalized Federated Learning for CT Imaging.
IEEE transactions on neural networks and learning systems
Feb 6, 2025
In clinical practice, computed tomography (CT) is an important noninvasive inspection technology to provide patients' anatomical information. However, its potential radiation risk is an unavoidable problem that raises people's concerns. Recently, dee...
Explainable Classification of Benign-Malignant Pulmonary Nodules With Neural Networks and Information Bottleneck.
IEEE transactions on neural networks and learning systems
Feb 6, 2025
Computerized tomography (CT) is a clinically primary technique to differentiate benign-malignant pulmonary nodules for lung cancer diagnosis. Early classification of pulmonary nodules is essential to slow down the degenerative process and reduce mort...
Zygomatic Osteotomy surgery design software based on skull CT scans - Self-supervised algo reduces workload.
Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Feb 5, 2025
BACKGROUND: The morphology of the zygomatic complex significantly influences facial appearance, leading to a focus on zygomatic osteotomy. The current technique, the "L-shaped" zygomatic osteotomy, requires a small incision and preoperative osteotomy...
Development of an artificial intelligence-based application for the diagnosis of sarcopenia: a retrospective cohort study using the health examination dataset.
BMC medical informatics and decision making
Feb 5, 2025
BACKGROUND: Medical imaging techniques for diagnosing sarcopenia have been extensively investigated. Studies have proposed using the T-score and patient information as key diagnostic factors. However, these techniques have either been time-consuming ...
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