AIMC Topic: Lung Neoplasms
Clear Filters Showing 471 to 480 of 1668 articles
Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.
European radiology experimental
May 20, 2024
BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR).
Prognostic model incorporating immune checkpoint genes to predict the immunotherapy efficacy for lung adenocarcinoma: a cohort study integrating machine learning algorithms.
Immunologic research
May 16, 2024
This study aimed to develop and validate a nomogram based on immune checkpoint genes (ICGs) for predicting prognosis and immune checkpoint blockade (ICB) efficacy in lung adenocarcinoma (LUAD) patients. A total of 385 LUAD patients from the TCGA data...
Attention pyramid pooling network for artificial diagnosis on pulmonary nodules.
PloS one
May 16, 2024
The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. Howev...
Development of a machine learning model for predicting pneumothorax risk in coaxial core needle biopsy (≤3 cm).
European journal of radiology
May 15, 2024
PURPOSE: The aim is to devise a machine learning algorithm exploiting preoperative clinical data to forecast the hazard of pneumothorax post-coaxial needle lung biopsy (CCNB), thereby informing clinical decision-making and enhancing perioperative car...
Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy response.
Respiratory research
May 14, 2024
BACKGROUND: Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures.
Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer.
Academic radiology
May 12, 2024
RATIONALE AND OBJECTIVES: To build a risk stratification by incorporating PET/CT-based deep learning features and whole-body metabolic tumor volume (MTV), which was to make predictions about overall survival (OS) and progression-free survival (PFS) f...
Accuracy of machine learning in preoperative identification of genetic mutation status in lung cancer: A systematic review and meta-analysis.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
May 10, 2024
BACKGROUND AND PURPOSE: We performed this systematic review and meta-analysis to investigate the performance of ML in detecting genetic mutation status in NSCLC patients.
Cross-site validation of lung cancer diagnosis by electronic nose with deep learning: a multicenter prospective study.
Respiratory research
May 10, 2024
BACKGROUND: Although electronic nose (eNose) has been intensively investigated for diagnosing lung cancer, cross-site validation remains a major obstacle to be overcome and no studies have yet been performed.
Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.
Cancer imaging : the official publication of the International Cancer Imaging Society
May 9, 2024
BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduc...
Graphene and metal-organic framework hybrids for high-performance sensors for lung cancer biomarker detection supported by machine learning augmentation.
Nanoscale
May 9, 2024
Conventional diagnostic methods for lung cancer, based on breath analysis using gas chromatography and mass spectrometry, have limitations for fast screening due to their limited availability, operational complexity, and high cost. As potential repla...
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 32065
- Neural Networks, Computer 30249
- Algorithms 27433
- Deep Learning 26935
- Artificial Intelligence 24866
- Robotics 13394
- Image Processing, Computer-Assisted 9746
- Retrospective Studies 9358
- Magnetic Resonance Imaging 6353
- Reproducibility of Results 5671
- Tomography, X-Ray Computed 4869
- Support Vector Machine 4774
- Computational Biology 4337
- Brain 4132
- Computer Simulation 3936
Recent Journals
- Scientific reports 6855
- Sensors (Basel, Switzerland) 4794
- PloS one 4219
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1920
- 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 1178
- Journal of chemical information and modeling 1070
- Nature communications 1054
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 877
- Journal of medical Internet research 867
- IEEE transactions on neural networks and learning systems 854