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1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2016: 5793-5796, 2016 Aug.
Article in English | MEDLINE | ID: mdl-28269571

ABSTRACT

Laboratory error detection is a hard task yet plays an important role in efficient care of the patients. Quality controls are inadequate in detecting pre-analytic errors and are not frequent enough. Hence population- and patient-based detectors are developed. However, it is not clear what set of analytes leads to the most efficient error detectors. Here, we use three different scoring functions that can be used in detecting errors, to rank a set of analytes in terms of their strength in distinguishing erroneous measurements. We also observe that using evaluations of larger subsets of analytes in our analysis does not necessarily lead to a more accurate error detector. In our data set obtained from renal kidney disease inpatients, calcium, potassium, and sodium, emerged as the top-3 indicators of an erroneous measurement. Using the joint likelihood of these three analytes, we obtain an estimated AUC of 0.73 in error detection.


Subject(s)
Clinical Chemistry Tests/methods , Laboratories , Adult , Humans , Kidney Diseases/metabolism , Quality Control , Research Design , Young Adult
2.
Stud Health Technol Inform ; 52 Pt 1: 665-9, 1998.
Article in English | MEDLINE | ID: mdl-10384538

ABSTRACT

Current natural language processing techniques for recognition of concepts in the electronic medical record have been insufficient to allow their broad use for coding information automatically. We have undertaken a preliminary investigation into the use of machine learning methods to recognize procedure codes from emergency room dictations for a trauma registry. Our preliminary results indicate moderate success, and we believe future enhancements with additional learning techniques and selected natural language processing approaches will be fruitful.


Subject(s)
Artificial Intelligence , Registries , Traumatology/classification , Emergency Service, Hospital , Humans , Medical Records Systems, Computerized , Wounds and Injuries
3.
J Mot Behav ; 21(3): 225-44, 1989 Sep.
Article in English | MEDLINE | ID: mdl-15136262

ABSTRACT

The stability limits of erect stance are described as a geometrical structure in a movement space. Mechanical properties and response latency, a neural property, are determining factors for the stability limits. Standing stability limits of adults and young children are compared, and a simple scheme is suggested by means of which infants can discover the stability limits as they learn to stand. The mechanics of different standing movements are discussed because their spatial temporal properties relate directly to their different stability limits. The combination of the stability limits for different movements gives a total set of stability limits, a different structure for adults than for children.

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