Using Machine Learning to predict survival in patients with brain metastases after Gamma Knife radiosurgery

Vazhenin, G.; Banov, S.; Golanov, A.; Ryabov, P.; Kostjuchenko, V.; Dalechina, A.

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Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 20 декабря 2019 г.

Авторы: Vazhenin G., Banov S., Golanov A., Ryabov P., Kostjuchenko V., Dalechina A.
Журнал: Journal of Physics: Conference Series
Том: 1205
Год издания: 2019
Издательство: IOP Publishing
Местоположение издательства: [Bristol, UK], England
Первая страница: 1
Последняя страница: 6
DOI: 10.1088/1742-6596/1205/1/012058
Аннотация: In this work machine learning approach was used to predict the patients overall survival after Gamma Knife radiosurgery. We constructed the regression and multiclass classification models to predict the time interval from the onset of the oncological disease to the unfavourable outcome and the patient's survival class. The models were built on data of 916 patients with 26 different primary features. The train set included patients with known clinical outcomes (445 patients). The median deviation in determining of the time from the onset of cancer to the date of death was 1.4 months. According to the regression model the most significant feature was the largest volume of the lesion by the date of the first radiosurgery. The most important feature was identified as the time interval from the date of birth to the onset of the oncological disease. The mean accuracy, according to the confusion matrix was 0,76. The accuracy of the study can be improved by the increasing of the patients number and completeness of the patient data.
Добавил в систему: Костюченко Валерий Валерьевич

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