AIMC Topic: Lung Neoplasms
Clear Filters Showing 201 to 210 of 1666 articles
Advancing lung cancer diagnosis: Combining 3D auto-encoders and attention mechanisms for CT scan analysis.
Journal of X-ray science and technology
Jan 28, 2025
ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, se...
Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis.
Computers in biology and medicine
Jan 27, 2025
An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three l...
Artificial intelligence for diagnosis and predictive biomarkers in Non-Small cell lung cancer Patients: New promises but also new hurdles for the pathologist.
Lung cancer (Amsterdam, Netherlands)
Jan 27, 2025
The rapid development of artificial intelligence (AI) based tools in pathology laboratories has brought forward unlimited opportunities for pathologists. Promising AI applications used for accomplishing diagnostic, prognostic and predictive tasks are...
Impact of Deep Learning 3D CT Super-Resolution on AI-Based Pulmonary Nodule Characterization.
Tomography (Ann Arbor, Mich.)
Jan 27, 2025
BACKGROUND/OBJECTIVES: Correct pulmonary nodule volumetry and categorization is paramount for accurate diagnosis in lung cancer screening programs. CT scanners with slice thicknesses of multiple millimetres are still common worldwide, and slice thick...
Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.
Journal of medical Internet research
Jan 27, 2025
BACKGROUND: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accura...
Feature-targeted deep learning framework for pulmonary tumorous Cone-beam CT (CBCT) enhancement with multi-task customized perceptual loss and feature-guided CycleGAN.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 26, 2025
Thoracic Cone-beam computed tomography (CBCT) is routinely collected during image-guided radiation therapy (IGRT) to provide updated patient anatomy information for lung cancer treatments. However, CBCT images often suffer from streaking artifacts an...
Brachytherapy Seed Placement by Robotic Bronchoscopy with Cone Beam Computed Tomography Guidance for Peripheral Lung Cancer: A Human Cadaveric Feasibility Pilot.
International journal of radiation oncology, biology, physics
Jan 25, 2025
PURPOSE: This study evaluates the feasibility of using robotic-assisted bronchoscopy with cone beam computed tomography (RB-CBCT) platform to perform low-dose-rate brachytherapy (LDR-BT) implants in a mechanically ventilated human cadaveric model. Po...
NAVT-net neuron attention visual taylor network for lung cancer detection using CT images.
Computational biology and chemistry
Jan 25, 2025
Lung Cancer is regarded as a common fatal disease affecting humans throughout the entire world. Early diagnosis is vital to save the patient's life and Computed Tomography (CT) scans are referred to as the major imaging modes but, the manual examinat...
Multiomic machine learning on lactylation for molecular typing and prognosis of lung adenocarcinoma.
Scientific reports
Jan 24, 2025
To integrate machine learning and multiomic data on lactylation-related genes (LRGs) for molecular typing and prognosis prediction in lung adenocarcinoma (LUAD). LRG mRNA and long non-coding RNA transcriptomes, epigenetic methylation data, and somati...
Delta-Radiomics Using Machine Learning Classifiers With Auxiliary Data Sets to Predict Disease Progression During Magnetic Resonance-Guided Radiotherapy in Adrenal Metastases.
JCO clinical cancer informatics
Jan 24, 2025
PURPOSE: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evalu...
Stay Ahead of Medical AI
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 32021
- Neural Networks, Computer 30231
- Algorithms 27405
- Deep Learning 26912
- Artificial Intelligence 24844
- Robotics 13389
- Image Processing, Computer-Assisted 9738
- Retrospective Studies 9346
- Magnetic Resonance Imaging 6347
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4866
- Support Vector Machine 4771
- Computational Biology 4333
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6800
- Sensors (Basel, Switzerland) 4794
- PloS one 4210
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- 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 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1066
- Nature communications 1047
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 874
- Journal of medical Internet research 864
- Briefings in bioinformatics 853