“Healthcare systems deal with multiple challenges in releasing information from data silos, finding it almost impossible to be implemented, maintained and upgraded, with difficulties ranging in the technical, security and human interaction fields.”
The authors propose an elegant mechanism “that promises healthcare interoperability through the transformation of healthcare data into the corresponding HL7 FHIR structure.”
These are great news! Very cool and practical research that can solve so many problems in the healthcare informatics field.
My only reserve with the paper is that early in the article they suggest adding and averaging similarities, which is a mathematically invalid exercise. Distances are arithmetically additive, but similarities (of the same or different kind or source) are not. We can make similarities additive and average them, but not in the arithmetic sense. Other than that, they work is a noble effort.
Closing a gap in the fractal geometry theory: Definition of fractal topography to essential understanding of scale-invariance.
One year old, but very relevant these days. Very important and enlightening research article.
A better understanding of scale-invariance by means of defining fractal topography opens the door to many practical applications. This was something loosely suggested in the literature, but not fully addressed. Great job!
If you are a chemist, biodesigner, or a researcher working in other fields, eventually you may need to fit a paired data set to a polynomial regression model. You could use software to do that, or build your own solution. This tutorial is aimed at those interested in the latter. Access it now at
Three different methods for implementing polynomial regression are described. Teachers and students might benefit from the tutorial since the calculations can be done with a spreadsheet software like Excel, by writing a computer program, or with a programmable calculator.
We have also included the new similarity measures proposed by Consonni & Todeschini (2012), and Todeschini, et al (2012).
Our Tutorial on Distance and Similarity was also updated, accordingly. Check it out at
Consonni, V. and Todeschini, R. (2012). New Similarity Coefficients for Binary Data. MATCH Commun. Math. Comput. Chem. 68, 581-592.
Todeschini, R., Consonni, V., Xiang, H., Holliday, J., Buscema, M., and Willet, P. (2012). Similarity Coefficients for Binary Chemoinformatics Data: Overview and Extended Comparison Using Simulated and Real Data Sets. J. Chem. Inf. Model. 52 (11).
We are getting closer to Mind Retrieval. The implications of being able to mine the brain are obvious for all sciences, in addition to homeland security, law and order, marketing research, etc.
I got last night this news, “Scientists map brain’s ‘thesaurus’ to help decode inner thoughts
Scientists at the University of California, Berkeley, have taken a step in that direction by building a “semantic atlas” that shows in vivid colors and multiple dimensions how the human brain organizes language. The atlas identifies brain areas that respond to words that have similar meanings
This is a new miner available at http://www.minerazzi.com/bioinfo. Use it to find or build genome, sequence, proteomics, RNA, pathway, metabolic, microarray, exosomal, PCR, phenotype, taxonomic, carbohydrate, metabolimic, drug design, and imaging collections. Search by topic or database.
Sample queries can be
[ cancer research ], [ rna and dna ], [ bioinformatics ], or similar.
If you are into bioinformatics databases, this miner is for you.