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pro vyhledávání: '"Aipeng Chen"'
Autor:
Jiaxing Liu, Shalini Gupta, Aipeng Chen, Chen-Kai Wang, Pratik Mishra, Hong-Jie Dai, Zoie Shui-Yee Wong, Jitendra Jonnagaddala
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e48145 (2023)
BackgroundElectronic health records (EHRs) in unstructured formats are valuable sources of information for research in both the clinical and biomedical domains. However, before such records can be used for research purposes, sensitive health informat
Externí odkaz:
https://doaj.org/article/b5fb6bc037c045c28e4998640704641f
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Abstract For research purposes, protected health information is often redacted from unstructured electronic health records to preserve patient privacy and confidentiality. The OpenDeID corpus is designed to assist development of automatic methods to
Externí odkaz:
https://doaj.org/article/bf43a13da7444d1aa4e7e7642ca37eee
Autor:
Solveig K. Sieberts, Jennifer Schaff, Marlena Duda, Bálint Ármin Pataki, Ming Sun, Phil Snyder, Jean-Francois Daneault, Federico Parisi, Gianluca Costante, Udi Rubin, Peter Banda, Yooree Chae, Elias Chaibub Neto, E. Ray Dorsey, Zafer Aydın, Aipeng Chen, Laura L. Elo, Carlos Espino, Enrico Glaab, Ethan Goan, Fatemeh Noushin Golabchi, Yasin Görmez, Maria K. Jaakkola, Jitendra Jonnagaddala, Riku Klén, Dongmei Li, Christian McDaniel, Dimitri Perrin, Thanneer M. Perumal, Nastaran Mohammadian Rad, Erin Rainaldi, Stefano Sapienza, Patrick Schwab, Nikolai Shokhirev, Mikko S. Venäläinen, Gloria Vergara-Diaz, Yuqian Zhang, the Parkinson’s Disease Digital Biomarker Challenge Consortium, Yuanjia Wang, Yuanfang Guan, Daniela Brunner, Paolo Bonato, Lara M. Mangravite, Larsson Omberg
Publikováno v:
npj Digital Medicine, Vol 4, Iss 1, Pp 1-12 (2021)
Abstract Consumer wearables and sensors are a rich source of data about patients’ daily disease and symptom burden, particularly in the case of movement disorders like Parkinson’s disease (PD). However, interpreting these complex data into so-cal
Externí odkaz:
https://doaj.org/article/45ee48713e9b4dd591d3f8cc81d31894
Autor:
Naga Lalitha Valli ALLA, Aipeng CHEN, Sean BATONGBACAL, Chandini NEKKANTTI, Hong-Jie Dai, Jitendra JONNAGADDALA
Publikováno v:
Computer Methods and Programs in Biomedicine Update, Vol 1, Iss , Pp 100024- (2021)
In Electronic Health Record (EHR) systems, key patient information is often captured in the form of unstructured clinical notes. The information from these notes can be extracted using Clinical Natural Language Processing (NLP). Training corpus is a
Externí odkaz:
https://doaj.org/article/b860cfd8b36b45eabc60a6c4bcb9c614
Publikováno v:
ACS Applied Nano Materials. 5:9920-9928
Publikováno v:
The Analyst. 147:4237-4248
Exosomes have been extensively studied as liquid biopsy biomarkers in the past decade. However, the origin and molecular heterogeneity of exosomes hinder the research development moving from proof-of-concept to clinical applications. Herein, we repor
Publikováno v:
TrAC Trends in Analytical Chemistry. 158:116840
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
For research purposes, protected health information is often redacted from unstructured electronic health records to preserve patient privacy and confidentiality. The OpenDeID corpus is designed to assist development of automatic methods to redact se
Autor:
Aipeng Chen, Shudong Wang
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030805036
ICBL
ICBL
The Covid-19 Pandemic has greatly changed the world and world education. This paper reviews the forced urgent transition to complete online learning in two different scenarios during the Covid-19 Pandemic in 2020. The two different scenarios are a Ja
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7565c60d6a43e259237d3981e9d94ae6
https://doi.org/10.1007/978-3-030-80504-3_24
https://doi.org/10.1007/978-3-030-80504-3_24
Publikováno v:
Studies in health technology and informatics. 264
Unstructured electronic health records are valuable resources for research. Before they are shared with researchers, protected health information needs to be removed from these unstructured documents to protect patient privacy. The main steps involve