Background: Discrepancies in medical data sets can perpetuate bias, especially when training deep learning models, potentially leading to biased outcomes in clinical applications. Understanding these biases is crucial for the development of equitable healthcare technologies. This study employs generative deep learning technology to explore and understand radiographic differences based on race among patients undergoing total hip arthroplasty.
View Article and Find Full Text PDFTumors resembling tenosynovial giant cell tumor (TGCT) but additionally forming chondroid matrix are rare and most often involve the temporomandibular joint (TMJ). We studied 21 tumors consisting of synoviocytes (large, eosinophilic mononuclear cells containing hemosiderin) and chondroid matrix to better understand these unusual neoplasms. The tumors occurred in 10 males and 11 females, in the age group of 31 to 80 years (median, 50 years) and involved the TMJ region (16), extremities (4), and spine (1).
View Article and Find Full Text PDFAims: Venous tumour thrombus (VTT) is a rare finding in osteosarcoma. Despite the high rate of VTT in osteosarcoma of the pelvis, there are very few descriptions of VTT associated with extrapelvic primary osteosarcoma. We therefore sought to describe the prevalence and presenting features of VTT in osteosarcoma of both the pelvis and the limbs.
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