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2020 – today
- 2024
[j7]Xiao Zhou, Akshara Rao Balachandra
, Michael F. Romano, Sang Peter Chin, Rhoda Au, Vijaya B. Kolachalama:
Adversarial Learning for MRI Reconstruction and Classification of Cognitively Impaired Individuals. IEEE Access 12: 83169-83182 (2024)- [j6]Meysam Ahangaran, Hanzhi Zhu, Ruihui Li, Lingkai Yin, Joseph Jang, Arnav P. Chaudhry, Lindsay A. Farrer, Rhoda Au, Vijaya B. Kolachalama:
DREAMER: a computational framework to evaluate readiness of datasets for machine learning. BMC Medical Informatics Decis. Mak. 24(1): 152 (2024) - [i4]Zexu Li, Suraj P. Prabhu, Zachary T. Popp, Shubhi S. Jain, Vijetha Balakundi, Ting Fang Alvin Ang, Rhoda Au, Jinying Chen:
A Natural Language Processing Approach to Support Biomedical Data Harmonization: Leveraging Large Language Models. CoRR abs/2411.02730 (2024) - 2023
- [c6]Jiaoyun Yang, Richu Jiang, Huitong Ding, Rhoda Au, Jinying Chen, Clara Li, Ning An:
Designing and Evaluating MahjongBrain: A Digital Cognitive Assessment Tool Through Gamification. HCI (49) 2023: 264-278 - 2022
- [c5]Nauman Dawalatabad, Yuan Gong, Sameer Khurana, Rhoda Au, James R. Glass:
Detecting Dementia from Long Neuropsychological Interviews. EMNLP (Findings) 2022: 5270-5283 - [c4]Ning An, Enze Hu, Yanrui Guo, Jiaoyun Yang, Rhoda Au, Huitong Ding:
Digital Mahjong System: Towards Precise Cognitive Assessment with IoT Technologies. HCI (46) 2022: 229-241 - 2021
- [j5]William Souillard-Mandar, Dana L. Penney, Braydon Schaible, Alvaro Pascual-Leone, Rhoda Au, Randall Davis:
DCTclock: Clinically-Interpretable and Automated Artificial Intelligence Analysis of Drawing Behavior for Capturing Cognition. Frontiers Digit. Health 3: 750661 (2021) - [j4]Rhoda Au, Vijaya B. Kolachalama, Ioannis Ch. Paschalidis:
Redefining and Validating Digital Biomarkers as Fluid, Dynamic Multi-Dimensional Digital Signal Patterns. Frontiers Digit. Health 3: 751629 (2021) - 2020
- [j3]Ning An, Huitong Ding, Jiaoyun Yang, Rhoda Au, Ting Fang Alvin Ang:
Deep ensemble learning for Alzheimer's disease classification. J. Biomed. Informatics 105: 103411 (2020)
2010 – 2019
- 2019
- [i3]Ning An, Huitong Ding, Jiaoyun Yang, Rhoda Au, Ting Fang Alvin Ang:
Deep ensemble learning for Alzheimers disease classification. CoRR abs/1905.12827 (2019) - 2018
- [c3]Tuka Al Hanai, Rhoda Au, James R. Glass:
Role-specific Language Models for Processing Recorded Neuropsychological Exams. NAACL-HLT (2) 2018: 746-752 - 2017
- [c2]Tuka Alhanai, Rhoda Au, James R. Glass:
Spoken language biomarkers for detecting cognitive impairment. ASRU 2017: 409-416 - [i2]Tuka Alhanai, Rhoda Au, James R. Glass:
Spoken Language Biomarkers for Detecting Cognitive Impairment. CoRR abs/1710.07551 (2017) - 2016
- [j2]William Souillard-Mandar, Randall Davis, Cynthia Rudin, Rhoda Au, David J. Libon, Rodney Swenson, Catherine C. Price, Melissa Lamar, Dana L. Penney:
Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test. Mach. Learn. 102(3): 393-441 (2016) - [i1]William Souillard-Mandar, Randall Davis, Cynthia Rudin, Rhoda Au, Dana L. Penney:
Interpretable Machine Learning Models for the Digital Clock Drawing Test. CoRR abs/1606.07163 (2016) - 2015
- [j1]Randall Davis, David J. Libon, Rhoda Au, David Pitman, Dana L. Penney:
THink: Inferring Cognitive Status from Subtle Behaviors. AI Mag. 36(3): 49-60 (2015) - 2014
- [c1]Randall Davis, David J. Libon, Rhoda Au, David Pitman, Dana L. Penney:
THink: Inferring Cognitive Status from Subtle Behaviors. AAAI 2014: 2898-2905
Coauthor Index
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