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Application of artificial intelligence in lung cancer
Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …
Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques
This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights
While we recognize the prognostic importance of clinicopathological measures and
circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers …
circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers …
[HTML][HTML] Brain tumor characterization using radiogenomics in artificial intelligence framework
Simple Summary Radiogenomics is a relatively new advancement in the understanding of
the biology and behaviour of cancer in response to conventional treatments. One of the most …
the biology and behaviour of cancer in response to conventional treatments. One of the most …
Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application
Y Meng, Y Yang, M Hu, Z Zhang, X Zhou - Seminars in cancer biology, 2023 - Elsevier
Radiomics is the extraction of predefined mathematic features from medical images for
predicting variables of clinical interest. Recent research has demonstrated that radiomics …
predicting variables of clinical interest. Recent research has demonstrated that radiomics …
Radiomics: a primer on high-throughput image phenoty**
Radiomics is a high-throughput approach to image phenoty**. It uses computer
algorithms to extract and analyze a large number of quantitative features from radiological …
algorithms to extract and analyze a large number of quantitative features from radiological …
The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews
Background and purpose In comparison to conventional medical imaging diagnostic
modalities, the aim of this overview article is to analyze the accuracy of the application of …
modalities, the aim of this overview article is to analyze the accuracy of the application of …
Acoustic-based deep learning architectures for lung disease diagnosis: a comprehensive overview
Lung auscultation has long been used as a valuable medical tool to assess respiratory
health and has gotten a lot of attention in recent years, notably following the coronavirus …
health and has gotten a lot of attention in recent years, notably following the coronavirus …
A review on lung disease recognition by acoustic signal analysis with deep learning networks
Recently, assistive explanations for difficulties in the health check area have been made
viable thanks in considerable portion to technologies like deep learning and machine …
viable thanks in considerable portion to technologies like deep learning and machine …
Lung disease recognition methods using audio-based analysis with machine learning
The use of computer-based automated approaches and improvements in lung sound
recording techniques have made lung sound-based diagnostics even better and devoid of …
recording techniques have made lung sound-based diagnostics even better and devoid of …