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ORCIDJournal of Biomedical Informatics, Volume 90
Volume 90, February 2019
- Robert Moskovitch
, Yuval Shahar, Fei Wang, George Hripcsak:
Temporal biomedical data analytics. - Maurits Kaptein:
Personalization in biomedical-informatics: Methodological considerations and recommendations.
- Maxim Topaz, Ludmila Murga, Katherine M. Gaddis, Margaret V. McDonald, Ofrit Bar-Bachar, Yoav Goldberg, Kathryn H. Bowles:
Mining fall-related information in clinical notes: Comparison of rule-based and novel word embedding-based machine learning approaches. - Neil R. Smalheiser, Aaron M. Cohen, Gary Bonifield:
Unsupervised low-dimensional vector representations for words, phrases and text that are transparent, scalable, and produce similarity metrics that are not redundant with neural embeddings. - Safa Fathiamini, Amber M. Johnson, Jia Zeng, Vijaykumar Holla, Nora S. Sanchez, Funda Meric-Bernstam, Elmer V. Bernstam, Trevor Cohen:
Rapamycin-mTOR+BRAF=? Using relational similarity to find therapeutically relevant drug-gene relationships in unstructured text. - Maryam Zolnoori, Kin Wah Fung, Timothy B. Patrick, Paul A. Fontelo, Hadi Kharrazi, Anthony Faiola, Yi Shuan Shirley Wu, Christina E. Eldredge, Jake Luo, Mike Conway, Jiaxi Zhu, Soo Kyung Park, Kelly Xu, Hamideh Moayyed, Somaieh Goudarzvand:
A systematic approach for developing a corpus of patient reported adverse drug events: A case study for SSRI and SNRI medications. - Brecht Claerhout, Dipak Kalra, Christina Mueller, Gurparkash Singh, Nadir Ammour, Laura Meloni, Juuso Blomster, Mark Hopley, George Kafatos, Almenia Garvey, Peter Kuhn, Martine Lewi, Bart Vannieuwenhuyse, Benoît Marchal, Ketan Patel, Christoph Schindler, Mats Sundgren:
Federated electronic health records research technology to support clinical trial protocol optimization: Evidence from EHR4CR and the InSite platform.
- Sara Fotouhi, Shahrokh Asadi, Michael W. Kattan:
A comprehensive data level analysis for cancer diagnosis on imbalanced data. - Zear Ibrahim, Arthur G. Money:
Computer mediated reality technologies: A conceptual framework and survey of the state of the art in healthcare intervention systems.
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