Zhuoqiao Hong

Princeton University — United States

Computer Science · Physical Sciences

5h-index100citations18works8.92yr avg
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Research Topics

Topic Modeling(6), Machine Learning in Healthcare(4), Neurobiology of Language and Bilingualism(3), Natural Language Processing Techniques(2), Neural Networks and Applications(2)

Publications18 total

Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
2024· 5 citedOpen Access
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
2024Open Access
Author response: Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
2024Open Access
Author Correction: Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
Nature Communications·2024Open Access
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
2024· 1 citedOpen Access
Alignment of brain embeddings and artificial contextual embeddings in natural language points to common geometric patterns
Nature Communications·2024· 54 citedOpen Access
Remote Work and Careers
SSRN Electronic Journal·2024· 1 citedOpen Access
The fragility of artists’ reputations from 1795 to 2020
Proceedings of the National Academy of Sciences·2023· 2 citedOpen Access
Artificial intelligence implementation in pancreaticobiliary endoscopy
Expert Review of Gastroenterology & Hepatology·2022· 4 cited
Automated Detection of Bowel Preparation Scoring and Adequacy With Deep Convolutional Neural Networks
Journal of the Canadian Association of Gastroenterology·2022· 7 citedOpen Access
Brain embeddings with shared geometry to artificial contextual embeddings, as a code for representing language in the human brain
2022· 6 citedOpen Access
NeuraHealth: An Automated Screening Pipeline to Detect Undiagnosed Cognitive Impairment in Electronic Health Records with Deep Learning and Natural Language Processing
arXiv (Cornell University)·2022Open Access
Active deep learning to detect cognitive concerns in electronic health records
Alzheimer s & Dementia·2021· 4 cited
Using Deep Learning to Identify Patients with Cognitive Impairment in Electronic Health Records
arXiv (Cornell University)·2021Open Access
Automated detection of cecal intubation with variable bowel preparation using a deep convolutional neural network
Endoscopy International Open·2021· 13 citedOpen Access
Fr613 AUTOMATED DETECTION OF BOWEL PREPARATION ADEQUACY WITH DEEP CONVOLUTIONAL NEURAL NETWORKS
Gastroenterology·2021
Fr614 AUTOMATED DETECTION OF CECAL INTUBATION WITH VARIABLE BOWEL PREPARATION USING A DEEP CONVOLUTIONAL NEURAL NETWORK
Gastroenterology·2021· 1 cited
Natural Language Processing to Detect Cognitive Concerns in Electronic Health Records Using Deep Learning
arXiv (Cornell University)·2020· 1 citedOpen Access

Frequent Co-authors

Bobbi Aubrey(7), Samuel A. Nastase(7), Zaid Zada(7), Harshvardhan Gazula(7), Sasha Devore(7), Patricia Dugan(7), Daniel Friedman(7), Orrin Devinsky(7), Adeen Flinker(7), Uri Hasson(7), Ariel Goldstein(6), Werner Doyle(6), Daniel J. Low(5), Samir C. Grover(4), David D. Turner(4), Leonard Niekerken(4), Colin Magdamo(4), Ayush Noori(4), Yi-han Sheu(4), Elissa M. Ye(4)