AIMC Topic: Radiation Tolerance
Clear Filters Showing 1 to 10 of 13 articles
A multi-gene predictive model for the radiation sensitivity of nasopharyngeal carcinoma based on machine learning.
eLife
Jun 18, 2025
Radiotherapy resistance in nasopharyngeal carcinoma (NPC) is a major cause of recurrence and metastasis. Identifying radiotherapy-related biomarkers is crucial for improving patient survival outcomes. This study developed the nasopharyngeal carcinoma...
Immunological biomarkers and gene signatures predictive of radiotherapy resistance in non-small cell lung cancer.
Frontiers in immunology
May 29, 2025
INTRODUCTION: A significant challenge in treating non-small cell lung cancer (NSCLC) is its inherent resistance to radiation therapy, leading to poor patient prognosis. This study aimed to identify key genes influencing radiotherapy resistance in NSC...
Deciphering colorectal cancer radioresistance and immune microrenvironment: unraveling the role of EIF5A through single-cell RNA sequencing and machine learning.
Frontiers in immunology
Sep 3, 2024
BACKGROUND: Radiotherapy (RT) is a critical component of treatment for locally advanced rectal cancer (LARC), though patient response varies significantly. The variability in treatment outcomes is partly due to the resistance conferred by cancer stem...
Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction.
Journal of photochemistry and photobiology. B, Biology
Jun 27, 2024
Nasopharyngeal cancer (NPC) is a malignant tumor with high prevalence in Southeast Asia and highly invasive and metastatic characteristics. Radiotherapy is the primary strategy for NPC treatment, however there is still lack of effect method for predi...
dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.
NAR cancer
Feb 24, 2024
Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer patients benefiting from RT during their treatment course. The intrinsic radiosensitivity or acquired radioresistance of tumor cells would affect the r...
Prediction of radiosensitivity and radiocurability using a novel supervised artificial neural network.
BMC cancer
Dec 1, 2022
BACKGROUND: Radiotherapy has been widely used to treat various cancers, but its efficacy depends on the individual involved. Traditional gene-based machine-learning models have been widely used to predict radiosensitivity. However, there is still a l...
Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.
JNCI cancer spectrum
May 17, 2021
In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entire...
Relative Biological Effectiveness
Radiobiology
Research Support as Topic
Neutron Capture Therapy
Neoplasms
Big Data
Radiation Oncology
Humans
Artificial Intelligence
Clinical Trials as Topic
Research
Radiotherapy
Patient-Centered Care
Hyperthermia, Induced
Radiopharmaceuticals
Radiation Tolerance
Photochemotherapy
Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance.
Nature communications
May 11, 2021
Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challenge. Personalized prediction of tumor radiosensitivity is not currently implemented clinically due to insufficient accuracy of existing machine learnin...
Improving the therapeutic ratio of radiotherapy against radioresistant cancers: Leveraging on novel artificial intelligence-based approaches for drug combination discovery.
Cancer letters
Apr 29, 2021
Despite numerous advances in cancer radiotherapy, tumor radioresistance remain one of the major challenges limiting treatment efficacy of radiotherapy. Conventional strategies to overcome radioresistance involve understanding the underpinning molecul...
Deep learning-assisted literature mining for in vitro radiosensitivity data.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Aug 17, 2019
BACKGROUND AND PURPOSE: Integrated analysis of existing radiosensitivity data obtained by the gold-standard clonogenic assay has the potential to improve our understanding of cancer cell radioresistance. However, extraction of radiosensitivity data f...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823