Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.
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DOI: 10.1002/mp.15903
Abstract: PURPOSE To develop a novel multimodal data fusion model by incorporating computed tomography (CT) images and clinical variables based on deep learning for predicting the invasiveness risk of stage I lung adenocarcinoma that manifests as… read more here.
Keywords: fusion; fusion model; clinical variables; multimodal data ... See more keywords
Predicting colorectal cancer tumor mutational burden from histopathological images and clinical information using multi-modal deep learning
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DOI: 10.1093/bioinformatics/btac641
Abstract: MOTIVATION Tumor mutational burden (TMB) is an indicator of the efficacy and prognosis of immune checkpoint therapy in colorectal cancer (CRC). Cancer patients with high TMB (TMB_H) values tend to benefit from immunotherapy, whereas those… read more here.
Keywords: multi modal; images clinical; deep learning; histopathological images ... See more keywords