AIMC Topic: Lung Neoplasms
Clear Filters Showing 1381 to 1390 of 1639 articles
Evaluating robustly standardized explainable anomaly detection of implausible variables in cancer data.
Journal of the American Medical Informatics Association : JAMIA
Apr 1, 2025
OBJECTIVES: Explanations help to understand why anomaly detection algorithms identify data as anomalous. This study evaluates whether robustly standardized explanation scores correctly identify the implausible variables that make cancer data anomalou...
Model development and validation for predicting small-cell lung cancer bone metastasis utilizing diverse machine learning algorithms based on the SEER database.
Medicine
Mar 21, 2025
The aim of this study was to devise a machine learning algorithm with superior performance in predicting bone metastasis (BM) in small cell lung cancer (SCLC) and create a straightforward web-based predictor based on the developed algorithm. Data com...
[Application Practice of AI Empowering Post-discharge Specialized Disease Management in Postoperative Rehabilitation of the Lung Cancer Patients Undergoing Surgery].
Zhongguo fei ai za zhi = Chinese journal of lung cancer
Mar 20, 2025
BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surg...
Accuracy of artificial intelligence-based simulation for assessing lung vessels and volume using unenhanced computed tomography.
European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
Mar 4, 2025
OBJECTIVES: The advantages of preoperative three-dimensional (3D) image simulations, which require enhanced computed tomography (ECT), for anatomical lung resection are well documented. However, the necessity for contrast agent presents a significant...
Easy ensemble classifier-group and intersectional fairness and threshold (EEC-GIFT): a fairness-aware machine learning framework for lung cancer screening eligibility using real-world data.
JNCI cancer spectrum
Mar 3, 2025
BACKGROUND: We use real-world data to develop a lung cancer screening (LCS) eligibility mechanism that is both accurate and free from racial bias.
Identifying Lipid Metabolism-Related Therapeutic Targets and Diagnostic Markers for Lung Adenocarcinoma by Mendelian Randomization and Machine Learning Analysis.
Thoracic cancer
Mar 1, 2025
BACKGROUND: Lipid metabolic disorders are emerging as a recognized influencing factors of lung adenocarcinoma (LUAD). This study aims to investigate the influence of lipid metabolism-related genes (LMRGs) on the diagnosis and treatment of LUAD and to...
Performance of Lung Cancer Prediction Models for Screening-detected, Incidental, and Biopsied Pulmonary Nodules.
Radiology. Artificial intelligence
Mar 1, 2025
Purpose To evaluate the performance of eight lung cancer prediction models on patient cohorts with screening-detected, incidentally detected, and bronchoscopically biopsied pulmonary nodules. Materials and Methods This study retrospectively evaluated...
[Exploration of the Predictive Value of Peripheral Blood-related Indicators for EGFR 
Mutations and Prognosis in Non-small Cell Lung Cancer Using Machine Learning].
Zhongguo fei ai za zhi = Chinese journal of lung cancer
Feb 20, 2025
BACKGROUND: Epidermal growth factor receptor (EGFR) sensitive mutation is one of the effective targets of targeted therapy for non-small cell lung cancer (NSCLC). However, due to the difficulty of obtaining some primary tissues and the economic facto...
Uncertainty CNNs: A path to enhanced medical image classification performance.
Mathematical biosciences and engineering : MBE
Feb 20, 2025
The automated detection of tumors using medical imaging data has garnered significant attention over the past decade due to the critical need for early and accurate diagnoses. This interest is fueled by advancements in computationally efficient model...
[Application of artificial intelligence in combination with CT radiomics in chronic obstructive pulmonary disease].
Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Feb 12, 2025
As CT imaging is increasingly used for the evaluation of lung nodules and the diagnosis and screening of lung cancer in smokers, we have more opportunities to use CT images to identify patients with early-stage chronic obstructive pulmonary disease(C...
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 31451
- Neural Networks, Computer 29895
- Algorithms 27046
- Deep Learning 26582
- Artificial Intelligence 24503
- Robotics 13347
- Image Processing, Computer-Assisted 9611
- Retrospective Studies 9187
- Magnetic Resonance Imaging 6228
- Reproducibility of Results 5621
- Tomography, X-Ray Computed 4804
- Support Vector Machine 4721
- Computational Biology 4285
- Brain 4066
- Computer Simulation 3901
Recent Journals
- Scientific reports 6417
- Sensors (Basel, Switzerland) 4794
- PloS one 4121
- Neural networks : the official journal of the International Neural Network Society 2930
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1870
- 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 1278
- IEEE journal of biomedical and health informatics 1155
- Journal of chemical information and modeling 1031
- Nature communications 993
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 867
- Briefings in bioinformatics 853
- IEEE transactions on neural networks and learning systems 840