AIMC Topic: Radiation Pneumonitis
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Predictive value of machine learning for radiation pneumonitis and checkpoint inhibitor pneumonitis in lung cancer patients: a systematic review and meta-analysis.
Scientific reports
Jul 1, 2025
Some studies have developed machine learning (ML) models for the prediction of pneumonitis following immunotherapy and radiotherapy for patients with lung cancer (LC). However, the prediction accuracy of these models remains a topic of debate. Thus, ...
Multimodal data deep learning method for predicting symptomatic pneumonitis caused by lung cancer radiotherapy combined with immunotherapy.
Frontiers in immunology
Jan 8, 2025
OBJECTIVES: The pairing of immunotherapy and radiotherapy in the treatment of locally advanced nonsmall cell lung cancer (NSCLC) has shown promise. By combining radiotherapy with immunotherapy, the synergistic effects of these modalities not only bol...
Predicting radiation pneumonitis in lung cancer using machine learning and multimodal features: a systematic review and meta-analysis of diagnostic accuracy.
BMC cancer
Nov 5, 2024
OBJECTIVES: To evaluate the diagnostic accuracy of machine learning models incorporating multimodal features for predicting radiation pneumonitis in lung cancer through a systematic review and meta-analysis.
Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy.
Computer methods and programs in biomedicine
Jun 19, 2024
BACKGROUND AND OBJECTIVE: To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve radiother...
Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning.
The Analyst
May 13, 2024
Radiation-induced lung injury (RILI) is a dose-limiting toxicity for cancer patients receiving thoracic radiotherapy. As such, it is important to characterize metabolic associations with the early and late stages of RILI, namely pneumonitis and pulmo...
Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 4, 2024
BACKGROUND: Pneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) rad...
Enhancing the prediction of symptomatic radiation pneumonitis for locally advanced non-small-cell lung cancer by combining 3D deep learning-derived imaging features with dose-volume metrics: a two-center study.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Mar 18, 2024
OBJECTIVE: This study aims to examine the ability of deep learning (DL)-derived imaging features for the prediction of radiation pneumonitis (RP) in locally advanced non-small-cell lung cancer (LA-NSCLC) patients.
Computed tomography and radiation dose images-based deep-learning model for predicting radiation pneumonitis in lung cancer patients after radiation therapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Feb 25, 2023
PURPOSE: To develop a deep learning model that combines CT and radiation dose (RD) images to predict the occurrence of radiation pneumonitis (RP) in lung cancer patients who received radical (chemo)radiotherapy.
Radiation pneumonitis prediction after stereotactic body radiation therapy based on 3D dose distribution: dosiomics and/or deep learning-based radiomics features.
Radiation oncology (London, England)
Nov 17, 2022
BACKGROUND: This study was designed to establish radiation pneumonitis (RP) prediction models using dosiomics and/or deep learning-based radiomics (DLR) features based on 3D dose distribution.
A deep learning-based dual-omics prediction model for radiation pneumonitis.
Medical physics
Aug 25, 2021
PURPOSE: Radiation pneumonitis (RP) is the main source of toxicity in thoracic radiotherapy. This study proposed a deep learning-based dual-omics model, which aims to improve the RP prediction performance by integrating more data points and exploring...
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