Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Joe Kesterson"'
Autor:
Chris Beesley, Paul R. Dexter, Anand Krishnan, Heidi Schmidt, Alexandra M. Roch, Saeed Mehrabi, Sunghwan Sohn, Mathew J. Palakal, Hongfang Liu, C. Max Schmidt, Joe Kesterson
Publikováno v:
Journal of Biomedical Informatics. 54:213-219
In Electronic Health Records (EHRs), much of valuable information regarding patients’ conditions is embedded in free text format. Natural language processing (NLP) techniques have been developed to extract clinical information from free text. One c
Publikováno v:
Applied Clinical Informatics. :154-163
Summary Background: Small numbers of tests with pending results are documented in hospital discharge summaries leading to breakdown in communication and medical errors due to inadequate followup. Objective: Evaluate effect of using a computerized pro
Autor:
Martin C. Were, Jason Cadwallader, Joe Kesterson, Chite Asirwa, Babar A. Khan, Marc B. Rosenman, Xiaochun Li
Publikováno v:
Journal of General Internal Medicine. 24:1002-1006
Poor communication of tests whose results are pending at hospital discharge can lead to medical errors.To determine the adequacy with which hospital discharge summaries document tests with pending results and the appropriate follow-up providers.Retro
Publikováno v:
Journal of Hospital Medicine. 2:5-12
Information on the prognostic utility of the admission complete blood count (CBC) and differential count is lacking.To identify independent predictors of mortality from the varied number and morphology of cells in the complete blood count defined as
Autor:
Anantha Shekhar, Sujuan Gao, Joe Kesterson, Chenkun Wang, Hugh C. Hendrie, Noll L. Campbell, Christopher M. Callahan
Publikováno v:
Alzheimer disease and associated disorders. 30(2)
A retrospective cohort study was conducted including 3688 patients age 60 years or older without dementia enrolled in a depression screening study in primary care clinics. Information on antidepressant use and incident dementia during follow-up was r
Autor:
Saeed, Mehrabi, Anand, Krishnan, Alexandra M, Roch, Heidi, Schmidt, DingCheng, Li, Joe, Kesterson, Chris, Beesley, Paul, Dexter, Max, Schmidt, Mathew, Palakal, Hongfang, Liu
Publikováno v:
Studies in health technology and informatics. 216
In this study we have developed a rule-based natural language processing (NLP) system to identify patients with family history of pancreatic cancer. The algorithm was developed in a Unstructured Information Management Architecture (UIMA) framework an
Publikováno v:
Gastroenterology. 126:1287-1292
Background & Aims: Studies that evaluate the risk of hepatotoxicity from statins in hyperlipidemic subjects with elevated baseline serum transaminases are lacking. We conducted a study to test the hypothesis that patients with elevated baseline liver
Autor:
Daniel O. Clark, Jesse C. Stewart, Joe Kesterson, Hugh C. Hendrie, Christopher M. Callahan, Sujuan Gao, Timothy E. Stump, Chenkun Wang
Visit-to-visit blood pressure variability has received considerable attention recently. The objective of our study is to define a variability measure that is independent of change over time and determine the association between longitudinal summary m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b3d2e81f5f7741d9137007f4b360798
https://europepmc.org/articles/PMC4057357/
https://europepmc.org/articles/PMC4057357/
Autor:
Saeed, Mehrabi, C Max, Schmidt, Joshua A, Waters, Chris, Beesley, Anand, Krishnan, Joe, Kesterson, Paul, Dexter, Mohammed A, Al-Haddad, William M, Tierney, Mathew, Palakal
Publikováno v:
Studies in health technology and informatics. 192
Pancreatic cancer is one of the deadliest cancers, mostly diagnosed at late stages. Patients with pancreatic cysts are at higher risk of developing cancer and their surveillance can help to diagnose the disease in earlier stages. In this retrospectiv
Autor:
Martin C, Were, Sergey, Gorbachev, Jason, Cadwallader, Joe, Kesterson, Xiaochun, Li, J Marc, Overhage, Jeff, Friedlin
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium. 2010
We evaluate the performance of a Natural Language Processing (NLP) application designed to extract follow-up provider information from free-text discharge summaries at two hospitals.We compare performance by the NLP application, called the Regenstrie