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Automated Classification of Osteosarcoma and Benign Tumors using RNA-seq and Plain X-ray

Osteosarcoma is a prominent bone cancer that typically affects adolescents or people in late adulthood. Early recognition of this disease relies on imaging technologies such as x-ray radiography to detect tumor size and location. This paper aims to differentiate osteosarcoma from benign tumors by analyzing both imaging and RNA-seq data through a combination of image processing and machine learning. In experimental results, the proposed method achieved an Area Under the Receiver Operator Characteristic Curve (AUC) of 0.7272 in three-fold cross-validation, and an AUC of 0.9015 using leave-one-out cross-validation.