AIMC Topic: Immune Checkpoint Inhibitors
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Development and validation of a CT-based radiomics machine learning model for differentiating immune-related interstitial pneumonia.
International immunopharmacology
May 27, 2025
INTRODUCTION: Immune checkpoint inhibitor-related interstitial pneumonia (CIP) poses a diagnostic challenge due to its radiographic similarity to other pneumonias. We developed a non-invasive model using CT imaging to differentiate CIP from other pne...
Prediction of prognosis of immune checkpoint inhibitors combined with anti-angiogenic agents for unresectable hepatocellular carcinoma by machine learning-based radiomics.
BMC cancer
May 19, 2025
OBJECTIVES: This study aims to develop and validate a novel radiomics model utilizing magnetic resonance imaging (MRI) to predict progression-free survival (PFS) in patients with unresectable hepatocellular carcinoma (uHCC) who are receiving a combin...
Carcinoma, Hepatocellular
Immune Checkpoint Inhibitors
Nomograms
Angiogenesis Inhibitors
Radiomics
Male
Middle Aged
Liver Neoplasms
Antineoplastic Combined Chemotherapy Protocols
Magnetic Resonance Imaging
Progression-Free Survival
Humans
Machine Learning
Female
Aged
Adult
Prognosis
Retrospective Studies
Identification of predictive subphenotypes for clinical outcomes using real world data and machine learning.
Nature communications
May 12, 2025
Predicting treatment response is an important problem in real-world applications, where the heterogeneity of the treatment response remains a significant challenge in practice. Unsupervised machine learning methods have been proposed to address this ...
Blood-brain barrier crossing biopolymer targeting c-Myc and anti-PD-1 activate primary brain lymphoma immunity: Artificial intelligence analysis.
Journal of controlled release : official journal of the Controlled Release Society
May 10, 2025
Primary Central Nervous System Lymphoma is an aggressive central nervous system neoplasm with poor response to pharmacological treatment, partially due to insufficient drug delivery across blood-brain barrier. In this study, we developed a novel ther...
NetLnc: A Network-Based Computational Framework to Identify Immune Checkpoint-Related lncRNAs for Immunotherapy Response in Melanoma.
International journal of molecular sciences
May 9, 2025
Long non-coding RNAs (lncRNAs) could alter the tumor immune microenvironment and regulate the expression of immune checkpoints (ICPs) by regulating target genes in tumors. However, only a few lncRNAs have precise functions in immunity and potential f...
Clinical characteristics, outcomes, and predictive modeling of patients diagnosed with immune checkpoint inhibitor therapy-related pneumonitis.
Cancer immunology, immunotherapy : CII
May 9, 2025
PURPOSE: The aim of this study is to better characterize the clinical characteristics and outcomes of patients diagnosed with Immune checkpoint Inhibitor (ICI) pneumonitis and propose predictive models.
Assessing the effects of immune checkpoint inhibitors on bone utilizing machine learning-assisted opportunistic quantitative computed tomography.
Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Mar 15, 2025
Immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, yet their impact on bone health remains unclear. This study aimed to perform a retrospective cohort study utilizing routine CT scans from patients with melanoma to perform oppor...
Deep Learning Model for Predicting Immunotherapy Response in Advanced Non-Small Cell Lung Cancer.
JAMA oncology
Feb 1, 2025
IMPORTANCE: Only a small fraction of patients with advanced non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitor (ICI) treatment. For optimal personalized NSCLC care, it is imperative to identify patients who are most likely to b...
Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census.
Frontiers in immunology
Jan 1, 2025
BACKGROUND: Although immune checkpoint inhibitors (ICIs) represent a substantial breakthrough in cancer treatment, it is crucial to acknowledge that their efficacy is limited to a subset of patients. The heterogeneity and stemness of cancer render it...
A transformer-based deep learning survival prediction model and an explainable XGBoost anti-PD-1/PD-L1 outcome prediction model based on the cGAS-STING-centered pathways in hepatocellular carcinoma.
Briefings in bioinformatics
Nov 22, 2024
Recent studies suggest cGAS-STING pathway may play a crucial role in the genesis and development of hepatocellular carcinoma (HCC), closely associated with classical pathways and tumor immunity. We aimed to develop models predicting survival and anti...
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