The artificial intelligence and machine learning in lung cancer immunotherapy

Q Gao, L Yang, M Lu, R Jin, H Ye, T Ma - Journal of Hematology & …, 2023 - Springer
Since the past decades, more lung cancer patients have been experiencing lasting benefits
from immunotherapy. It is imperative to accurately and intelligently select appropriate …

[HTML][HTML] Radiomics: a review of current applications and possibilities in the assessment of tumor microenvironment

C Xue, Q Zhou, H Xi, J Zhou - Diagnostic and Interventional Imaging, 2023 - Elsevier
With the recent success in the application of immunotherapy for treating various advanced
cancers, the tumor microenvironment has rapidly become an important field of research. The …

Non-invasive measurement using deep learning algorithm based on multi-source features fusion to predict PD-L1 expression and survival in NSCLC

C Wang, J Ma, J Shao, S Zhang, J Li, J Yan… - Frontiers in …, 2022 - frontiersin.org
Background Programmed death-ligand 1 (PD-L1) assessment of lung cancer in
immunohistochemical assays was only approved diagnostic biomarker for immunotherapy …

Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges

F Silva, T Pereira, I Neves, J Morgado… - Journal of Personalized …, 2022 - mdpi.com
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …

[HTML][HTML] Wavelet transformation can enhance computed tomography texture features: a multicenter radiomics study for grade assessment of COVID-19 pulmonary …

Z Jiang, J Yin, P Han, N Chen, Q Kang… - … imaging in medicine …, 2022 - ncbi.nlm.nih.gov
Background This study set out to develop a computed tomography (CT)-based wavelet
transforming radiomics approach for grading pulmonary lesions caused by COVID-19 and to …

Musculoskeletal ultrasound image‐based radiomics for the diagnosis of achilles tendinopathy in skiers

L Wang, D Wen, Y Yin, P Zhang, W Wen… - … of Ultrasound in …, 2023 - Wiley Online Library
Objectives Our study aimed to develop and validate an efficient ultrasound image‐based
radiomic model for determining the Achilles tendinopathy in skiers. Methods A total of 88 feet …

Artificial Intelligence-Based Treatment Decisions: A New Era for NSCLC

O Fiste, I Gkiozos, A Charpidou, NK Syrigos - Cancers, 2024 - mdpi.com
Simple Summary Lung cancer therapeutics have dramatically improved in recent years.
Indeed, precision oncology could be exemplified by non-small cell lung cancer (NSCLC) …

MRI-based pre-Radiomics and delta-Radiomics models accurately predict the post-treatment response of rectal adenocarcinoma to neoadjuvant chemoradiotherapy

L Wang, X Wu, R Tian, H Ma, Z Jiang, W Zhao… - Frontiers in …, 2023 - frontiersin.org
Objectives To develop and validate magnetic resonance imaging (MRI)-based pre-
Radiomics and delta-Radiomics models for predicting the treatment response of local …

A whirl of radiomics-based biomarkers in cancer immunotherapy, why is large scale validation still lacking?

M Ligero, B Gielen, V Navarro… - npj Precision …, 2024 - nature.com
The search for understanding immunotherapy response has sparked interest in diverse
areas of oncology, with artificial intelligence (AI) and radiomics emerging as promising tools …

Quantitative radiological features and deep learning for the non-invasive evaluation of programmed death ligand 1 expression levels in gastric cancer patients: A …

W Xie, Z Jiang, X Zhou, X Zhang, M Zhang, R Liu… - Academic …, 2023 - Elsevier
Rationale and objectives Programmed Death-Ligand 1 (PD-L1) is an important biomarker
for patient selection of immunotherapy in gastric cancer (GC). This study aimed to construct …