Predicting cancer outcomes with radiomics and artificial intelligence in radiology
The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …
application of AI-based cancer imaging analysis to address other, more complex, clinical …
[HTML][HTML] Therapeutic implications of tumor microenvironment in lung cancer: focus on immune checkpoint blockade
C Genova, C Dellepiane, P Carrega… - Frontiers in …, 2022 - frontiersin.org
In the last decade, the treatment of non-small cell lung cancer (NSCLC) has been
revolutionized by the introduction of immune checkpoint inhibitors (ICI) directed against …
revolutionized by the introduction of immune checkpoint inhibitors (ICI) directed against …
Caution on kidney dysfunctions of COVID-19 patients
Z Li, M Wu, J Yao, J Guo, X Liao, S Song, J Li, G Duan… - MedRxiv, 2020 - medrxiv.org
Background To date, large amounts of epidemiological and case study data have been
available for the Coronavirus Disease 2019 (COVID-19), which suggested that the mortality …
available for the Coronavirus Disease 2019 (COVID-19), which suggested that the mortality …
Delta radiomics: A systematic review
V Nardone, A Reginelli, R Grassi, L Boldrini… - La radiologia …, 2021 - Springer
Background Radiomics can provide quantitative features from medical imaging that can be
correlated with various biological features and clinical endpoints. Delta radiomics, on the …
correlated with various biological features and clinical endpoints. Delta radiomics, on the …
[HTML][HTML] Digital pathology and computational image analysis in nephropathology
The emergence of digital pathology—an image-based environment for the acquisition,
management and interpretation of pathology information supported by computational …
management and interpretation of pathology information supported by computational …
[HTML][HTML] Deep learning with radiomics for disease diagnosis and treatment: challenges and potential
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
Predicting microvascular invasion in hepatocellular carcinoma using CT-based radiomics model
Background Prediction of microvascular invasion (MVI) may help determine treatment
strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach …
strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach …
[HTML][HTML] Technological advances in cancer immunity: from immunogenomics to single-cell analysis and artificial intelligence
Y Xu, GH Su, D Ma, Y Xiao, ZM Shao… - Signal Transduction and …, 2021 - nature.com
Immunotherapies play critical roles in cancer treatment. However, given that only a few
patients respond to immune checkpoint blockades and other immunotherapeutic strategies …
patients respond to immune checkpoint blockades and other immunotherapeutic strategies …
[HTML][HTML] Extracellular vesicle PD-L1 dynamics predict durable response to immune-checkpoint inhibitors and survival in patients with non-small cell lung cancer
Abstract Background Immune-checkpoint inhibitors (ICIs) changed the therapeutic
landscape of patients with lung cancer. However, only a subset of them derived clinical …
landscape of patients with lung cancer. However, only a subset of them derived clinical …
[HTML][HTML] Predicting response to immunotherapy in advanced non-small-cell lung cancer using tumor mutational burden radiomic biomarker
Background Tumor mutational burden (TMB) is a significant predictor of immune checkpoint
inhibitors (ICIs) efficacy. This study investigated the correlation between deep learning …
inhibitors (ICIs) efficacy. This study investigated the correlation between deep learning …