0000000000486001

AUTHOR

Christina Glasner

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Multimodal Deep Learning for Prognosis Prediction in Renal Cancer

2021

BackgroundClear-cell renal cell carcinoma (ccRCC) is common and associated with substantial mortality. TNM stage and histopathological grading have been the sole determinants of a patient’s prognosis for decades and there are few prognostic biomarkers used in clinical routine. Management of ccRCC involves multiple disciplines such as urology, radiology, oncology, and pathology and each of these specialties generates highly complex medical data. Here, artificial intelligence (AI) could prove extremely powerful to extract meaningful information to benefit patients.ObjectiveIn the study, we developed and evaluated a multimodal deep learning model (MMDLM) for prognosis prediction in ccRCC.Desig…

OncologyCancer ResearchPrognosis predictionmedicine.medical_specialtyrenal cancerDiseaseRenal cell carcinomaInternal medicinemedicineStage (cooking)Exome sequencingRC254-282Original Researchbusiness.industryDeep learningCancerdeep learningNeoplasms. Tumors. Oncology. Including cancer and carcinogensmedicine.diseaseartificial intelligenceradiologyOncologyCohortpathologyArtificial intelligenceprognosis predictionbusinessFrontiers in Oncology
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