Author:
Yücel Melda,Nigdeli Sinan Melih,Bekdaş Gebrail
Publisher
Springer International Publishing
Reference46 articles.
1. Sawant, A., Bhandari, M., Yadav, R., Yele, R., Bendale, M.S.: Brain cancer detection from mri: a machine learning approach (tensorflow). Brain 5(04), 2089–2094 (2018)
2. Fujisawa, Y., Inoue, S., Nakamura, Y.: The possibility of deep learning-based, computer-aided skin tumor classifiers. Front. Med. 6, 191 (2019)
3. Ayer, T., Alagoz, O., Chhatwal, J., Shavlik, J.W., Kahn, C.E., Jr., Burnside, E.S.: Breast cancer risk estimation with artificial neural networks revisited: discrimination and calibration. Cancer 116(14), 3310–3321 (2010)
4. Sahoo, A.K., Pradhan, C., Das, H.: Performance evaluation of different machine learning methods and deep-learning based convolutional neural network for health decision making. In: Nature Inspired Computing for Data Science, pp. 201–212. Springer, Cham (2020)
5. Grossi, E., Podda, G.M., Pugliano, M., Gabba, S., Verri, A., Carpani, G., Buscema, M., Casazza, G., Cattaneo, M.: Prediction of optimal warfarin maintenance dose using advanced artificial neural networks. Pharmacogenomics 15(1), 29–37 (2014)