Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Soheil Moosavinasab"'
Autor:
Rajeswari Swaminathan, Yungui Huang, Soheil Moosavinasab, Ronald Buckley, Christopher W. Bartlett, Simon M. Lin
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 14, Iss C, Pp 8-15 (2016)
The constant improvement and falling prices of whole human genome Next Generation Sequencing (NGS) has resulted in rapid adoption of genomic information at both clinics and research institutions. Considered together, the complexity of genomics data,
Externí odkaz:
https://doaj.org/article/1fab1b21556543579b45194bbe94a6a3
Publikováno v:
ACI Open. :e1-e12
Objective A large amount of clinical data are stored in clinical notes that frequently contain spelling variations, typos, local practice-generated acronyms, synonyms, and informal words. Instead of relying on established but infrequently updated ont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1ad7d79a1cdd4de8adb155996138120
https://doi.org/10.1055/s-0041-1729982
https://doi.org/10.1055/s-0041-1729982
Autor:
Simon Lin, Brendan Boyle, Steve Rust, Ariana Prinzbach, John Barnard, Soheil Moosavinasab, Yungui Huang
Publikováno v:
Journal of Pediatric Gastroenterology & Nutrition. 67:488-493
Objectives:Celiac disease (CD) is associated with a variety of extraintestinal autoimmune and inflammatory findings that manifest clinically as symptoms and comorbidities. Understanding these comorbidities may improve identification of the disease an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::62dc7c5369c181c334d8007d88edee19
https://doi.org/10.1097/mpg.0000000000002020
https://doi.org/10.1097/mpg.0000000000002020
Autor:
Lina Yossef-Salameh, Soheil Moosavinasab, Mark A. Klebanoff, Catalin S. Buhimschi, Irina A. Buhimschi, Emily A. Oliver, Patricia B. Reagan, Louis J. Muglia, Reena Oza-Frank
Publikováno v:
Obstetrics & Gynecology. 131:281-289
To compare preterm birth rates and gestational length in four race-nativity groups including Somali Americans.Using a retrospective cohort study design of Ohio birth certificates, we analyzed all singleton births between 2000 and 2015 from four group
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25eac174eb4c21f339f65a8621d4d038
https://doi.org/10.1097/aog.0000000000002427
https://doi.org/10.1097/aog.0000000000002427
Publikováno v:
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. 25
Various deep learning models have been developed for different healthcare predictive tasks using Electronic Health Records and have shown promising performance. In these models, medical codes are often aggregated into visit representation without con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::6adc1e395afceeb3cf1287996d793c3c
https://pubmed.ncbi.nlm.nih.gov/31797591
https://pubmed.ncbi.nlm.nih.gov/31797591
Publikováno v:
PSB
Various deep learning models have been developed for different healthcare predictive tasks using Electronic Health Records and have shown promising performance. In these models, medical codes are often aggregated into visit representation without con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0956a24bfef40563eec1a6668a9091f1
https://doi.org/10.1142/9789811215636_0011
https://doi.org/10.1142/9789811215636_0011
Autor:
En-Ju D, Lin, Jennifer L, Hefner, Xianlong, Zeng, Soheil, Moosavinasab, Thomas, Huber, Jennifer, Klima, Chang, Liu, Simon M, Lin
Publikováno v:
The American journal of managed care. 25(10)
Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financial data for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::61d4b0265cb9fb272e0a4a7a9d069844
https://pubmed.ncbi.nlm.nih.gov/31622071
https://pubmed.ncbi.nlm.nih.gov/31622071
Publikováno v:
KDD
Unstructured clinical texts contain rich health-related information. To better utilize the knowledge buried in clinical texts, discovering synonyms for a medical query term has become an important task. Recent automatic synonym discovery methods leve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89b045cf8df7ba53cbba32e257ce0f5f
Autor:
Srinivasan Parthasarathy, Jingong Huang, Xiang Yue, Ping Zhang, Simon Lin, Wen Zhang, Huan Sun, Soheil Moosavinasab, Yungui Huang, Zhen Wang
Publikováno v:
Bioinformatics
Graph embedding learning that aims to automatically learn low-dimensional node representations, has drawn increasing attention in recent years. To date, most recent graph embedding methods are evaluated on social and information networks and are not
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9797d05f4d0f267f5036c815a8f49408
Autor:
David Chen, Rajiv Ramnath, Manirupa Das, Soheil Moosavinasab, Yungui Huang, Eric Fosler-Lussier, Simon Lin, Steve Rust
Publikováno v:
BioNLP
In this work, we develop a novel, completely unsupervised, neural language model-based document ranking approach to semantic tagging of documents, using the document to be tagged as a query into the GLM to retrieve candidate phrases from top-ranked r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2c648dc6746932277b43d29fb96b42a
https://doi.org/10.18653/v1/w18-2313
https://doi.org/10.18653/v1/w18-2313