Application of artificial intelligence in lung cancer

HY Chiu, HS Chao, YM Chen - Cancers, 2022‏ - mdpi.com
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 …

Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques

A Atmakuru, S Chakraborty, O Faust, M Salvi… - Expert Systems with …, 2024‏ - Elsevier
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 …

Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights

SJ Sujit, M Aminu, TV Karpinets, P Chen… - Nature …, 2024‏ - nature.com
While we recognize the prognostic importance of clinicopathological measures and
circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers …

[HTML][HTML] Brain tumor characterization using radiogenomics in artificial intelligence framework

B Jena, S Saxena, GK Nayak, A Balestrieri, N Gupta… - Cancers, 2022‏ - mdpi.com
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 …

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 …

Radiomics: a primer on high-throughput image phenoty**

KJ Lafata, Y Wang, B Konkel, FF Yin, MR Bashir - Abdominal Radiology, 2022‏ - Springer
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 …

The use of artificial intelligence tools in cancer detection compared to the traditional diagnostic imaging methods: An overview of the systematic reviews

HEC Silva, GNM Santos, AF Leite, CRM Mesquita… - Plos one, 2023‏ - journals.plos.org
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 …

Acoustic-based deep learning architectures for lung disease diagnosis: a comprehensive overview

AH Sfayyih, AH Sabry, SM Jameel, N Sulaiman… - Diagnostics, 2023‏ - mdpi.com
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 …

A review on lung disease recognition by acoustic signal analysis with deep learning networks

AH Sfayyih, N Sulaiman, AH Sabry - Journal of big Data, 2023‏ - Springer
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 …

Lung disease recognition methods using audio-based analysis with machine learning

AH Sabry, OID Bashi, NHN Ali, YM Al Kubaisi - Heliyon, 2024‏ - cell.com
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 …