Artificial intelligence-based prediction of clinical outcome in immunotherapy and targeted therapy of lung cancer
X Yin, H Liao, H Yun, N Lin, S Li, Y Xiang… - Seminars in cancer biology, 2022 - Elsevier
Lung cancer accounts for the main proportion of malignancy-related deaths and most
patients are diagnosed at an advanced stage. Immunotherapy and targeted therapy have …
patients are diagnosed at an advanced stage. Immunotherapy and targeted therapy have …
[HTML][HTML] [18F] FDG-PET/CT radiomics and artificial intelligence in lung cancer: technical aspects and potential clinical applications
R Manafi-Farid, E Askari, I Shiri, C Pirich… - Seminars in nuclear …, 2022 - Elsevier
Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …
Radiomics and gene expression profile to characterise the disease and predict outcome in patients with lung cancer
M Kirienko, M Sollini, M Corbetta, E Voulaz… - European journal of …, 2021 - Springer
Objective The objectives of our study were to assess the association of radiomic and
genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC) …
genomic data with histology and patient outcome in non-small cell lung cancer (NSCLC) …
Homology-based image processing for automatic classification of histopathological images of lung tissue
M Nishio, M Nishio, N Jimbo, K Nakane - Cancers, 2021 - mdpi.com
Simple Summary The purpose of this study was to develop a computer-aided diagnosis
(CAD) system for automatic classification of histopathological images of lung tissues …
(CAD) system for automatic classification of histopathological images of lung tissues …
Predicting EGFR mutation status in non–small cell lung cancer using artificial intelligence: a systematic review and meta-analysis
Rationale and Objectives Recent advancements in artificial intelligence (AI) render a
substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction …
substantial promise for epidermal growth factor receptor (EGFR) mutation status prediction …
Clinical application of AI-based PET images in oncological patients
J Dai, H Wang, Y Xu, X Chen, R Tian - Seminars in Cancer Biology, 2023 - Elsevier
Based on the advantages of revealing the functional status and molecular expression of
tumor cells, positron emission tomography (PET) imaging has been performed in numerous …
tumor cells, positron emission tomography (PET) imaging has been performed in numerous …
[HTML][HTML] Predicting EGFR mutation subtypes in lung adenocarcinoma using 18F-FDG PET/CT radiomic features
Background Identification of epidermal growth factor receptor (EGFR) mutation types is
crucial before tyrosine kinase inhibitors (TKIs) treatment. Radiomics is a new strategy to …
crucial before tyrosine kinase inhibitors (TKIs) treatment. Radiomics is a new strategy to …
Use of radiomics based on 18F-FDG PET/CT and machine learning methods to aid clinical decision-making in the classification of solitary pulmonary lesions: an …
Y Zhou, X Ma, T Zhang, J Wang, T Zhang… - European journal of …, 2021 - Springer
Purpose This study was designed and performed to assess the ability of 18 F-
fluorodeoxyglucose (FDG) positron emission tomography (PET) and computed tomography …
fluorodeoxyglucose (FDG) positron emission tomography (PET) and computed tomography …
Imaging-based prediction of molecular therapy targets in NSCLC by radiogenomics and AI approaches: a systematic review
The objective of this systematic review was to analyze the current state of the art of imaging-
derived biomarkers predictive of genetic alterations and immunotherapy targets in lung …
derived biomarkers predictive of genetic alterations and immunotherapy targets in lung …
Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …
routines provide unquestionable benefits in connecting human medical expertise with …