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UrduA study published in Gastroenterology finds that radiomics-based machine learning models may detect pancreatic cancer on prediagnostic CT scans substantially earlier than current methods for clinical diagnosis.
Tag: radiomics
Moffitt Researchers Develop Model to Predict Patients with Poor Lung Cancer Outcomes
Moffitt Cancer Center researchers are working to improve the ability to identify patients who are at a higher risk of poor survival through radiomics, an area of science that uses imaging, such as CT scans and MRIs, to uncover tumoral patterns and characteristics that may not be easy to spot by the naked eye. Results of their newest study was published today in Cancer Biomarkers.
Moffitt Researchers Develop Model to Predict Non-Small Cell Lung Cancer Patient Outcomes to Immunotherapy
In a new article published in JNCI Cancer Spectrum, Moffitt Cancer Center researchers describe a prediction model they have created that includes information calculated from computed tomography images that can identify non-small cell lung cancer patients who are not likely to respond to immunotherapy.
Moffitt Researchers Develop Non-invasive Approach to Measure Biomarker Levels, Predict Outcomes in Lung Cancer Patients
In a new article published in the Journal for ImmunoTherapy of Cancer, Moffitt Cancer Center researchers show that PET/CT images can be used to measure levels of the PD-L1 biomarker of non-small cell lung cancer (NSCLC) patients in a non-invasive manner and, in turn, predict a patient’s response to therapy.
Moffitt Researchers Develop Tool to Better Predict Treatment Course for Lung Cancer Patients
In a new article published in Nature Communications, Moffitt Cancer Center researcher demonstrate how a deep learning model using positron emission tomography/computerized tomography radiomics can identify which non-small cell lung cancer patients may be sensitive to tyrosine kinase inhibitor treatment and those who would benefit from immune checkpoint inhibitor therapy.