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ORCIDArtificial Intelligence in Medicine, Volume 98
Volume 98, July 2019
- Bing-Zhong Jing, Tao Zhang
, Zixian Wang, Ying Jin, Kuiyuan Liu, Wenze Qiu, Liangru Ke, Ying Sun, Caisheng He, Dan Hou, Linquan Tang, Xing Lv, Chao-Feng Li:
A deep survival analysis method based on ranking. 1-9 - Muhammad Naveed Iqbal Qureshi, Jooyoung Oh, Boreom Lee:
3D-CNN based discrimination of schizophrenia using resting-state fMRI. 10-17 - Tung Tran, Ramakanth Kavuluru:
Distant supervision for treatment relation extraction by leveraging MeSH subheadings. 18-26 - Alessio Alexiadis:
Deep multiphysics: Coupling discrete multiphysics with machine learning to attain self-learning in-silico models replicating human physiology. 27-34 - Jianying Lin, Hui Chen, Shan Li, Yushuang Liu, Xuan Li, Bin Yu:
Accurate prediction of potential druggable proteins based on genetic algorithm and Bagging-SVM ensemble classifier. 35-47 - Oeslle Lucena, Roberto Souza, Letícia Rittner, Richard Frayne, Roberto de Alencar Lotufo:
Convolutional neural networks for skull-stripping in brain MR imaging using silver standard masks. 48-58 - Rudresh Deepak Shirwaikar, Dinesh Acharya U., Krishna Moorthi Makkithaya, Surulivelrajan M, Shikhar Srivastava, Leslie Edward S. Lewis U:
Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction. 59-76 - Haik Kalantarian, Khaled Jedoui, Peter Washington, Qandeel Tariq, Kaiti Dunlap, Jessey N. Schwartz, Dennis P. Wall:
Labeling images with facial emotion and the potential for pediatric healthcare. 77-86 - Alessio Bottrighi, Luca Piovesan, Paolo Terenziani:
Supporting the distributed execution of clinical guidelines by multiple agents. 87-108
- Ashenafi Zebene Woldaregay, Eirik Årsand, Ståle Walderhaug, David J. Albers, Lena Mamykina, Taxiarchis Botsis, Gunnar Hartvigsen:
Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. 109-134
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