D. C. ALİS Et Al. , "Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas," JAPANESE JOURNAL OF RADIOLOGY , vol.38, no.2, pp.135-143, 2020
ALİS, D. C. Et Al. 2020. Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas. JAPANESE JOURNAL OF RADIOLOGY , vol.38, no.2 , 135-143.
ALİS, D. C., Bagcilar, O., Senli, Y. D., Yergin, M., İŞLER, C., Kocer, N., ... Islak, C.(2020). Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas. JAPANESE JOURNAL OF RADIOLOGY , vol.38, no.2, 135-143.
ALİS, DENİZ Et Al. "Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas," JAPANESE JOURNAL OF RADIOLOGY , vol.38, no.2, 135-143, 2020
ALİS, DENİZ C. Et Al. "Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas." JAPANESE JOURNAL OF RADIOLOGY , vol.38, no.2, pp.135-143, 2020
ALİS, D. C. Et Al. (2020) . "Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas." JAPANESE JOURNAL OF RADIOLOGY , vol.38, no.2, pp.135-143.
@article{article, author={DENİZ CAN ALİS Et Al. }, title={Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas}, journal={JAPANESE JOURNAL OF RADIOLOGY}, year=2020, pages={135-143} }