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Considerations for a Universal Exchange Language for Healthcare

Considerations for a Universal Exchange Language for Healthcare. Barry Robson 1,2 , Ulysses G.J. Balis 1,3 & Thomas P. Caruso 1,4 (Presenting) 1 Member, Biomedical Informatics Think Tank TM , a Division of Projectivity, Inc., Vienna, VA, USA

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Considerations for a Universal Exchange Language for Healthcare

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  1. Considerations for a Universal Exchange Language for Healthcare Barry Robson1,2, Ulysses G.J. Balis1,3 & Thomas P. Caruso1,4 (Presenting) 1Member, Biomedical Informatics Think TankTM, a Division of Projectivity, Inc., Vienna, VA, USA 2 Department of Mathematics & Computer Science, University of Wisconsin-Stout, Stout, WI, USA and St. Matthew's University School of Medicine, Florida & Grand Cayman, Cayman Islands 3Associate Professor and Director, Division of Pathology Informatics, University of Michigan, Ann Arbor, MI, USA 4Business Ambitions, LLC, Vienna, VA, USA Biomedical Informatics Think Tank is a Trademark of Projectivity, Inc.

  2. Considerations for a UEL for Healthcare • PCAST Recommends: security-enabled XML-like metadata tagged data elements • Ensure Uniformity: as few attributes as possible for (1) patient data, (2) statistical summaries & metrics of medicine drawn from data analysis of many patients, (3) semantic triples for the Semantic Web, and (4) probabilistic rules for inference • Advance Research: usemath principles for optimum probability analysis • Consider Matrix Mathematics: from widely accepted quantum mechanics • Use data element tag <Bra|Relator|Ket> as analogous to <Subject|Verb|Object> triples of W3C specifications where Verb can be a matrix “operator” • Each Subject and Object formulated as one or more Metadata:=Orthodata - i.e. attributes! • Uses vector/matrix formalisms from quantum mechanics, the universal mathematics & physics probability language. • Use probability vector [pfwd, pbwd], e.g. probabilities that overeating causes obesity, and obesity causes overeating. • Empirical probabilities expressed in a spinor form where ha √ +1, i.e. the hyperbolic number. pfwd = P(A|B), pbwd = P(B|A), and assoc = K(A;B) <A|B> = [(1-h) P(A|B)+ (1+h) P(B|A) ] = [(1-h) P(A)+ (1+h) P(B) ] K(A;B) • With pfwd=P(A|B), pbwd=P(B|A) PLUS, as a “bonus”, the assoc constant K(A; B) = P(A,B) / P(A)P(B) as attributes in a <Bra|Relator|Ket> which acts as an XML-like “tag”, all relevant probabilities and measures (e.g. risk factor, odds ratios, etc.) of EBM and epidemiology can be calculated.

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