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Ruogu Fang

Showing results (51-60 of 67) with videos related to

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Arxiv|January 3, 2024
Morphological Profiling for Drug Discovery in the Era of Deep LearningQiaosi Tang, Ranjala Ratnayake, Gustavo Seabra, et al.
Briefings in Bioinformatics|June 17, 2024
Morphological profiling for drug discovery in the era of deep learningQiaosi Tang, Ranjala Ratnayake, Gustavo Seabra, et al.
Brain Stimulation|October 13, 2020
Machine learning and individual variability in electric field characteristics predict tDCS treatment responseAlejandro Albizu, Ruogu Fang, Aprinda Indahlastari, et al.
Nature Computational Science|December 4, 2025
Revealing neurocognitive and behavioral patterns through unsupervised manifold learning of dynamic brain dataZixia Zhou, Junyan Liu, Wei Emma Wu, et al.
Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association|December 26, 2025
BiomarkersTyler Ann Busch, Kevin Iversen, Skylar Stolte, et al.
Kidney360|May 5, 2026
Reinforcement Learning for Intraoperative Hypotension Management with Consideration to Postoperative Acute Kidney InjuryEsra Adiyeke, Tianqi Liu, Venkata Sai Dheeraj Naganaboin, et al.
Arxiv|June 10, 2025
Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learningEsra Adiyeke, Tianqi Liu, Venkata Sai Dheeraj Naganaboina, et al.
Frontiers in Aging Neuroscience|December 24, 2021
Baseline Neuroimaging Predicts Decline to Dementia From Amnestic Mild Cognitive ImpairmentJoseph M Gullett, Alejandro Albizu, Ruogu Fang, et al.
Arxiv|February 6, 2026
Physiology-Informed Generative Multi-Task Network for Contrast-Free CT PerfusionWasif Khan, John Rees, Kyle B See, et al.
Frontiers in Human Neuroscience|February 11, 2026
Diagnostically competitive performance of a physiology-informed generative multi-task network for contrast-free CT perfusionWasif Khan, John Rees, Kyle B See, et al.
Pageof 7

Showing results (51-60 of 67) with videos related to

Sort By:
Pageof 7
Arxiv|January 3, 2024
Morphological Profiling for Drug Discovery in the Era of Deep LearningQiaosi Tang, Ranjala Ratnayake, Gustavo Seabra, et al.
Briefings in Bioinformatics|June 17, 2024
Morphological profiling for drug discovery in the era of deep learningQiaosi Tang, Ranjala Ratnayake, Gustavo Seabra, et al.
Brain Stimulation|October 13, 2020
Machine learning and individual variability in electric field characteristics predict tDCS treatment responseAlejandro Albizu, Ruogu Fang, Aprinda Indahlastari, et al.
Nature Computational Science|December 4, 2025
Revealing neurocognitive and behavioral patterns through unsupervised manifold learning of dynamic brain dataZixia Zhou, Junyan Liu, Wei Emma Wu, et al.
Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association|December 26, 2025
BiomarkersTyler Ann Busch, Kevin Iversen, Skylar Stolte, et al.
Kidney360|May 5, 2026
Reinforcement Learning for Intraoperative Hypotension Management with Consideration to Postoperative Acute Kidney InjuryEsra Adiyeke, Tianqi Liu, Venkata Sai Dheeraj Naganaboin, et al.
Arxiv|June 10, 2025
Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learningEsra Adiyeke, Tianqi Liu, Venkata Sai Dheeraj Naganaboina, et al.
Frontiers in Aging Neuroscience|December 24, 2021
Baseline Neuroimaging Predicts Decline to Dementia From Amnestic Mild Cognitive ImpairmentJoseph M Gullett, Alejandro Albizu, Ruogu Fang, et al.
Arxiv|February 6, 2026
Physiology-Informed Generative Multi-Task Network for Contrast-Free CT PerfusionWasif Khan, John Rees, Kyle B See, et al.
Frontiers in Human Neuroscience|February 11, 2026
Diagnostically competitive performance of a physiology-informed generative multi-task network for contrast-free CT perfusionWasif Khan, John Rees, Kyle B See, et al.
Pageof 7