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ORCIDArtificial Intelligence in Medicine, Volume 99
Volume 99, August 2019
- Xiaowei Li, Xin Zhang, Jing Zhu, Wandeng Mao, Shuting Sun, Zihan Wang, Chen Xia, Bin Hu:
Depression recognition using machine learning methods with different feature generation strategies. - Nassim Versbraegen, Aziz Fouché
, Charlotte Nachtegael, Sofia Papadimitriou, Andrea M. Gazzo, Guillaume Smits, Tom Lenaerts:
Using game theory and decision decomposition to effectively discern and characterise bi-locus diseases. - Malihe Javidi, Ahad Harati, Hamidreza Pourreza:
Retinal image assessment using bi-level adaptive morphological component analysis. - Yi-Peng Liu, Zhanqing Li, Cong Xu, Jing Li, Ronghua Liang:
Referable diabetic retinopathy identification from eye fundus images with weighted path for convolutional neural network. - Tahira Nazir, Aun Irtaza, Zain Shabbir, Ali Javed, Usman Akram, Muhammad Tariq Mahmood:
Diabetic retinopathy detection through novel tetragonal local octa patterns and extreme learning machines. - Nicolas Houy, François Le Grand:
Personalized oncology with artificial intelligence: The case of temozolomide. - Anders Reenberg Andersen, Wim Vancroonenburg, Greet Vanden Berghe:
Strategic room type allocation for nursing wards through Markov chain modeling. - A. M. Mutawa, Mariam A. Alzuwawi:
Multilayered rule-based expert system for diagnosing uveitis.
- Norah M. Asiri, Muhammad Hussain, Fadwa Al Adel, Nazih Alzaidi:
Deep learning based computer-aided diagnosis systems for diabetic retinopathy: A survey. - Andy M. Y. Tai, Alcides Albuquerque, Nicole E. Carmona, Mehala Subramanieapillai, Danielle S. Cha, Margarita Sheko, Yena Lee, Rodrigo Mansur, Roger S. McIntyre:
Machine learning and big data: Implications for disease modeling and therapeutic discovery in psychiatry.
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