Synovial Sarcoma of the Thyroid Gland

Primary synovial sarcoma of the thyroid is an extremely rare condition which has only been reported twice in the literature. We herein report a case of highly aggressive and rapidly lethal primary synovial sarcoma of the thyroid. A 72-year-old woman presented with extensive local invasion, rapid progression, and early distant metastasis secondary to primary thyroid synovial sarcoma. The tumor exhibited an atypical histologic and immunohistochemical staining pattern. Detection of SYT/SSX fusion transcript confirmed the diagnosis of synovial sarcoma. Due to the aggressive nature of primary synovial sarcoma of the thyroid gland, early diagnosis and comprehensive treatment including wide resection and postoperative chemoradiation is required

Predictive Solution for Radiation Toxicity Based on Big Data

Radiotherapy is a treatment method using radiation for cancer treatment based on a patient treatment planning for each radiotherapy machine. At this time, the dose, volume, device setting information, complication, tumor control probability, etc. are considered as a single-patient treatment for each fraction during radiotherapy process. Thus, these filed-up big data for a long time and numerous patients’ cases are inevitably suitable to produce optimal treatment and minimize the radiation toxicity and complication. Thus, we are going to handle up prostate, lung, head, and neck cancer cases using machine learning algorithm in radiation oncology. And, the promising algorithms as the support vector machine, decision tree, and neural network, etc. will be introduced in machine learning. In conclusion, we explain a predictive solution of radiation toxicity based on the big data as treatment planning decision support system

Prediction of Cancer Patient Outcomes Based on Artificial Intelligence

Knowledge-based outcome predictions are common before radiotherapy. Because there are various treatment techniques, numerous factors must be considered in predicting cancer patient outcomes. As expectations surrounding personalized radiotherapy using complex data have increased, studies on outcome predictions using artificial intelligence have also increased. Representative artificial intelligence techniques used to predict the outcomes of cancer patients in the field of radiation oncology include collecting and processing big data, text mining of clinical literature, and machine learning for implementing prediction models. Here, methods of data preparation and model construction to predict rates of survival and toxicity using artificial intelligence are described

Diversity and distribution of the genus Scrophularia L. (Scrophulariaceae) in Uzbekistan

This article presents a new checklist of Scrophularia in Uzbekistan. The synopsis includes 21 species; one of them is national endemic, and seven species were newly recorded for Uzbekistan as a result of field collecting missions, studies, and examination of Tashkent (TASH), St.-Petersburg (LE), Almaty (AA), and Moscow (MW) herbarium collections. The geographical distribution of Scrophularia in Uzbekistan was mapped and analyzed. The identification key, a table of comparative diagnostic characters, nomenclatural types, and ecological data are provided. (C) 2019 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA), Publishing Services by Elsevier.Peer reviewe