Zobrazeno 1 - 10
of 25
pro vyhledávání: '"David Kartchner"'
Publikováno v:
AI, Vol 3, Iss 1, Pp 211-228 (2022)
A major bottleneck preventing the extension of deep learning systems to new domains is the prohibitive cost of acquiring sufficient training labels. Alternatives such as weak supervision, active learning, and fine-tuning of pretrained models reduce t
Externí odkaz:
https://doaj.org/article/ea76a52f90a245db8ba410bac6a8ab48
Autor:
David Kartchner, Kevin McCoy, Janhvi Dubey, Dongyu Zhang, Kevin Zheng, Rushda Umrani, James J. Kim, Cassie S. Mitchell
Publikováno v:
Biology, Vol 12, Iss 9, p 1269 (2023)
Multiple studies have reported new or exacerbated persistent or resistant hypertension in patients previously infected with COVID-19. We used literature-based discovery to identify and prioritize multi-scalar explanatory biology that relates resistan
Externí odkaz:
https://doaj.org/article/bafefac1b296476cb79b4957636a2490
Optimizations for Computing Relatedness in Biomedical Heterogeneous Information Networks: SemNet 2.0
Autor:
Anna Kirkpatrick, Chidozie Onyeze, David Kartchner, Stephen Allegri, Davi Nakajima An, Kevin McCoy, Evie Davalbhakta, Cassie S. Mitchell
Publikováno v:
Big Data and Cognitive Computing, Vol 6, Iss 1, p 27 (2022)
Literature-based discovery (LBD) summarizes information and generates insight from large text corpuses. The SemNet framework utilizes a large heterogeneous information network or “knowledge graph” of nodes and edges to compute relatedness and ran
Externí odkaz:
https://doaj.org/article/a663c64fb3e74aeab9365802baf44ddf
Autor:
Kevin McCoy, Sateesh Gudapati, Lawrence He, Elaina Horlander, David Kartchner, Soham Kulkarni, Nidhi Mehra, Jayant Prakash, Helena Thenot, Sri Vivek Vanga, Abigail Wagner, Brandon White, Cassie S. Mitchell
Publikováno v:
Pharmaceutics, Vol 13, Iss 6, p 794 (2021)
Link prediction in artificial intelligence is used to identify missing links or derive future relationships that can occur in complex networks. A link prediction model was developed using the complex heterogeneous biomedical knowledge graph, SemNet,
Externí odkaz:
https://doaj.org/article/69316bd872524a48ba7821f74793df6d
Autor:
Abigail Wagner, David Kartchner, Sateesh Gudapati, Sri Vivek Vanga, Lawrence He, Soham Kulkarni, Elaina Horlander, Helena Thenot, Kevin McCoy, Brandon White, Nidhi Mehra, Jayant Prakash, Cassie S. Mitchell
Publikováno v:
Pharmaceutics, Vol 13, Iss 794, p 794 (2021)
Pharmaceutics
Volume 13
Issue 6
Pharmaceutics
Volume 13
Issue 6
Link prediction in artificial intelligence is used to identify missing links or derive future relationships that can occur in complex networks. A link prediction model was developed using the complex heterogeneous biomedical knowledge graph, SemNet,
Publikováno v:
EMNLP (Findings)
We study the problem of learning neural text classifiers without using any labeled data, but only easy-to-provide rules as multiple weak supervision sources. This problem is challenging because rule-induced weak labels are often noisy and incomplete.
Publikováno v:
ICHI
One of the primary challenges of healthcare delivery is aggregating disparate, asynchronous data sources into meaningful indicators of individual health. We combine natural language word embedding and network modeling techniques to learn meaningful r
Autor:
Denitza P. Blagev, John B. Cannon, Per H. Gesteland, Elizabeth A. Joy, Benjamin D. Horne, Michelle G. Hofmann, C. Arden Pope, Jacob S. Lefler, E. Kent Korgenski, Grant I. Hansen, Natalie Torosyan, David Kartchner
Publikováno v:
American journal of respiratory and critical care medicine. 198(6)
Nearly 60% of U.S. children live in counties with particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PMTo evaluate the association between ambient PMUsing an observational case-crossover design, subjects (n = 146,397) were stud
Publikováno v:
ICHI
Identifying disease comorbidities and grouping medical diagnoses into disease incidents are two important problems in health care delivery and assessment. Using vector space embeddings produced using the Global Vectors (GloVe) algorithm, we are able
Publikováno v:
ICHI
Identifying future high-cost patients allows healthcare organizations to take preventative measures to both reduce future patient costs and lessen the burden of illness. This paper expands upon past risk adjustment strategies to predict the persisten