AIMC Topic: Tomography, X-Ray Computed
Clear Filters Showing 301 to 310 of 4962 articles
Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy.
Journal for immunotherapy of cancer
Mar 15, 2025
BACKGROUND: Accurate prediction of pathologic complete response (pCR) following neoadjuvant immunotherapy combined with chemotherapy (nICT) is crucial for tailoring patient care in esophageal squamous cell carcinoma (ESCC). This study aimed to develo...
Establishing a Deep Learning Model That Integrates Pretreatment and Midtreatment Computed Tomography to Predict Treatment Response in Non-Small Cell Lung Cancer.
International journal of radiation oncology, biology, physics
Mar 13, 2025
PURPOSE: Patients with identical stages or similar tumor volumes can vary significantly in their responses to radiation therapy (RT) due to individual characteristics, making personalized RT for non-small cell lung cancer (NSCLC) challenging. This st...
CQENet: A segmentation model for nasopharyngeal carcinoma based on confidence quantitative evaluation.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 13, 2025
Accurate segmentation of the tumor regions of nasopharyngeal carcinoma (NPC) is of significant importance for radiotherapy of NPC. However, the precision of existing automatic segmentation methods for NPC remains inadequate, primarily manifested in t...
Patellar tilt calculation utilizing artificial intelligence on CT knee imaging.
The Knee
Mar 13, 2025
BACKGROUND: In the diagnosis of patellar instability, three-dimensional (3D) imaging enables measurement of a wide range of metrics. However, measuring these metrics can be time-consuming and prone to error due to conducting 2D measurements on 3D obj...
Segment Like A Doctor: Learning reliable clinical thinking and experience for pancreas and pancreatic cancer segmentation.
Medical image analysis
Mar 13, 2025
Pancreatic cancer is a lethal invasive tumor with one of the worst prognosis. Accurate and reliable segmentation for pancreas and pancreatic cancer on computerized tomography (CT) images is vital in clinical diagnosis and treatment. Although certain ...
Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods.
Tomography (Ann Arbor, Mich.)
Mar 13, 2025
RATIONALE: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response of NAC for patients with LABC before initiating treatment would be valuable to customize therapies and ensure t...
Integration of intratumoral and peritumoral CT radiomic features with machine learning algorithms for predicting induction therapy response in locally advanced non-small cell lung cancer.
BMC cancer
Mar 13, 2025
OBJECTIVES: To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical facto...
Liver margin segmentation in abdominal CT images using U-Net and Detectron2: annotated dataset for deep learning models.
Scientific reports
Mar 13, 2025
The segmentation of liver margins in computed tomography (CT) images presents significant challenges due to the complex anatomical variability of the liver, with critical implications for medical diagnostics and treatment planning. In this study, we ...
Multi-dimensional interpretable deep learning-radiomics based on intra-tumoral and spatial habitat for preoperative prediction of thymic epithelial tumours risk categorisation.
Acta oncologica (Stockholm, Sweden)
Mar 13, 2025
BACKGROUND AND PURPOSE: This study aims to develop and compare combined models based on enhanced CT-based radiomics, multi-dimensional deep learning, clinical-conventional imaging and spatial habitat analysis to achieve accurate prediction of thymoma...
Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms.
European journal of medical research
Mar 13, 2025
OBJECTIVES: This study aimed to develop a model for predicting peripheral lymph node metastasis (LNM) in thyroid cancer patients by combining enhanced CT radiomic features with machine learning algorithms. It increased the clinical utility and interp...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32523
- Neural Networks, Computer 30491
- Algorithms 27737
- Deep Learning 27290
- Artificial Intelligence 25212
- Robotics 13430
- Image Processing, Computer-Assisted 9887
- Retrospective Studies 9532
- Magnetic Resonance Imaging 6482
- Reproducibility of Results 5745
- Tomography, X-Ray Computed 4959
- Support Vector Machine 4812
- Computational Biology 4396
- Brain 4188
- Computer Simulation 3963
Recent Journals
- Scientific reports 7012
- Sensors (Basel, Switzerland) 4794
- PloS one 4303
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2040
- Computational intelligence and neuroscience 1931
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1395
- IEEE journal of biomedical and health informatics 1195
- Journal of chemical information and modeling 1087
- Nature communications 1071
- Computer methods and programs in biomedicine 895
- Bioinformatics (Oxford, England) 879
- Journal of medical Internet research 878
- IEEE transactions on neural networks and learning systems 859