J Blair Christian
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Explore the profile of J Blair Christian including associated specialties, affiliations and a list of published articles.
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11
Citations
91
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Recent Articles
1.
Yoon H, Klasky H, Blanchard A, Christian J, Durbin E, Wu X, et al.
BMC Med Inform Decis Mak
. 2024 Sep;
24(Suppl 5):262.
PMID: 39289714
Background: Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing...
2.
Alawad M, Gao S, Qiu J, Schaefferkoetter N, Hinkle J, Yoon H, et al.
IEEE EMBS Int Conf Biomed Health Inform
. 2022 Sep;
2019.
PMID: 36081613
Automated text information extraction from cancer pathology reports is an active area of research to support national cancer surveillance. A well-known challenge is how to develop information extraction tools with...
3.
Stewart R, Erwin S, Piburn J, Nagle N, Kaufman J, Peluso A, et al.
Appl Geogr
. 2022 Aug;
146:102759.
PMID: 35945952
In the opening months of the pandemic, the need for situational awareness was urgent. Forecasting models such as the Susceptible-Infectious-Recovered (SIR) model were hampered by limited testing data and key...
4.
Spannaus A, Papamarkou T, Erwin S, Christian J
Sci Rep
. 2022 Jun;
12(1):10761.
PMID: 35750796
The role of epidemiological models is crucial for informing public health officials during a public health emergency, such as the COVID-19 pandemic. However, traditional epidemiological models fail to capture the...
5.
Yoon H, Stanley C, Christian J, Klasky H, Blanchard A, Durbin E, et al.
Cancer Biomark
. 2022 Feb;
33(2):185-198.
PMID: 35213361
Background: With the use of artificial intelligence and machine learning techniques for biomedical informatics, security and privacy concerns over the data and subject identities have also become an important issue...
6.
Blanchard A, Gao S, Yoon H, Christian J, Durbin E, Wu X, et al.
IEEE J Biomed Health Inform
. 2022 Jan;
26(6):2796-2803.
PMID: 35020599
Recent applications ofdeep learning have shown promising results for classifying unstructured text in the healthcare domain. However, the reliability of models in production settings has been hindered by imbalanced data...
7.
Gao S, Kotevska O, Sorokine A, Christian J
PLoS One
. 2021 Feb;
16(2):e0246310.
PMID: 33561139
Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts...
8.
Yoon H, Klasky H, Gounley J, Alawad M, Gao S, Durbin E, et al.
J Biomed Inform
. 2020 Sep;
110:103564.
PMID: 32919043
Objective: In machine learning, it is evident that the classification of the task performance increases if bootstrap aggregation (bagging) is applied. However, the bagging of deep neural networks takes tremendous...
9.
Hasan S, Rivera D, Wu X, Durbin E, Christian J, Tourassi G
IEEE J Biomed Health Inform
. 2020 May;
24(7):1952-1967.
PMID: 32386166
Cancer registries collect unstructured and structured cancer data for surveillance purposes which provide important insights regarding cancer characteristics, treatments, and outcomes. Cancer registry data typically (1) categorize each reportable cancer...
10.
Alawad M, Gao S, Qiu J, Yoon H, Christian J, Penberthy L, et al.
J Am Med Inform Assoc
. 2019 Nov;
27(1):89-98.
PMID: 31710668
Objective: We implement 2 different multitask learning (MTL) techniques, hard parameter sharing and cross-stitch, to train a word-level convolutional neural network (CNN) specifically designed for automatic extraction of cancer data...