Abstract
would be aware of the types and categories of different datasets in biomedical informatics.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
Institute of Medicine, http.//iom.edu.
- 3.
In Einstein’s theory of Special Relativity, Euclidean 3-space plus time (the “4th-dimension”) are unified into the Minkowski space.
References
Adler R, Downarowicz T, Misiurewicz M (2008) Topological entropy (Online). http://www.scholarpedia.org/article/Topological_entropy. Accessed 10 Aug 2013
Adler RL, Konheim AG, Mcandrew MH (1965) Topological entropy. Trans Am Math Soc 114(2):309–319
Ahmadian L, Van Engen-Verheul M, Bakhshi-Raiez F, Peek N, Cornet R, De Keizer NF (2011) The role of standardized data and terminological systems in computerized clinical decision support systems: literature review and survey. Int J Med Inform 80(2):81–93
Aho AV, Hopcroft JE, Ullman JD (1983) Data structures and algorithms. Addison-Wesley, Boston, MA
Bemmel JHV, Musen MA (1997) Handbook of medical informatics. Springer, Heidelberg
Bessarabova M, Ishkin A, Jebailey L, Nikolskaya T, Nikolsky Y (2012) Knowledge-based analysis of proteomics data. BMC Bioinform 13(Suppl 16):S13
Bleiholder J, Naumann F (2008) Data fusion. ACM Comput Surv (CSUR) 41(1):1
Boisot M, Canals A (2004) Data, information and knowledge: have we got it right? J Evol Econ 14(1):43–67
Bramer M (2013) Principles of data mining, 2nd edn. Springer, Heidelberg
Clausius R (1850) On the motive power of heat, and on the laws which can be deduced from it for the theory of heat (reprint, 1960). Dover, New York
Cormen T (2013) Algorithms unlocked. The MIT Press, Cambridge, MA
Cormen TH, Leiserson CE, Rivest RL, Stein C (2009) Introduction to algorithms, 3rd edn. The MIT Press, Cambridge, MA
Darwin C (1859) On the origin of species by means of natural selection, or the preservation of favoured races in the struggle for life. John Murray, London
De Boer P-T, Kroese DP, Mannor S, Rubinstein RY (2005) A tutorial on the cross-entropy method. Ann Oper Res 134(1):19–67
Dehmer M, Mowshowitz A (2011) A history of graph entropy measures. Inform Sci 181(1):57–78
Dos Santos S, Brodlie K (2002) Visualizing and investigating multidimensional functions. Proceedings of the symposium on data visualisation 2002. Eurographics Association. pp. 173–182
Dos Santos S, Brodlie K (2004) Gaining understanding of multivariate and multidimensional data through visualization. Comput Graph 28(3):311–325
Duda RO, Hart PE, Stork DG (2000) Pattern Classification, 2nd edn. Wiley, New York
Edelsbrunner H, Harer JL (2010) Computational topology: an introduction. American Mathematical Society, Providence, RI
Ghrist R (2008) Barcodes: the persistent topology of data. Bull Am Math Soc 45(1):61–75
Golan A (2008) Information and entropy econometric: a review and synthesis. Found Trends Econ 2(1–2):1–145
Holzinger A (2003) Basiswissen IT/Informatik. Band 2: Informatik. Vogel Buchverlag, Wuerzburg
Holzinger A (2012) On knowledge discovery and interactive intelligent visualization of biomedical data: challenges in human–computer interaction & biomedical informatics. In: Helfert M, Fancalanci C, Filipe J (eds) DATA—International conference on data technologies and applications. INSTICC, Rome, pp 5–16
Holzinger A (2013) Human–computer interaction & knowledge discovery (HCI-KDD): what is the benefit of bringing those two fields to work together? In: Alfredo Cuzzocrea CK, Simos DE, Weippl E, Xu L (eds) Multidisciplinary Research and practice for information systems, Springer lecture notes in computer science LNCS 8127. Springer, New York, pp 319–328
Hornero R, Aboy M, Abasolo D, Mcnames J, Wakeland W, Goldstein B (2006) Complex analysis of intracranial hypertension using approximate entropy. Crit Care Med 34(1):87–95
Hufford MB, Xu X, Van Heerwaarden J, Pyhajarvi T, Chia J-M, Cartwright RA, Elshire RJ, Glaubitz JC, Guill KE, Kaeppler SM, Lai J, Morrell PL, Shannon LM, Song C, Springer NM, Swanson-Wagner RA, Tiffin P, Wang J, Zhang G, Doebley J, Mcmullen MD, Ware D, Buckler ES, Yang S, Ross-Ibarra J (2012) Comparative population genomics of maize domestication and improvement. Nat Genet 44(7):808–811
Jaynes ET (1957) Information theory and statistical mechanics. Phys Rev 106(4):620
Joyce AR, Palsson BØ (2006) The model organism as a system: integrating “omics” data sets. Nat Rev Mol Cell Biol 7(3):198–210
Kaski S, Peltonen J (2011) Dimensionality reduction for data visualization (applications corner). IEEE Sig Process Mag 28(2):100–104
Körner J (1973) Coding of an information source having ambiguous alphabet and the entropy of graphs. 6th Prague conference on information theory. pp. 411–425
Kreuzthaler M, Bloice MD, Faulstich L, Simonic KM, Holzinger A (2011) A comparison of different retrieval strategies working on medical free texts. J Univ Comput Sci 17(7):1109–1133
Lane N, Martin W (2010) The energetics of genome complexity. Nature 467(7318):929–934
Lanzagorta M, Uhlmann J (2008) Quantum computer science. Morgan & Claypool, San Francisco
Lieberman E, Hauert C, Nowak MA (2005) Evolutionary dynamics on graphs. Nature 433(7023):312–316
Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers AH (2011) Big data: the next frontier for innovation, competition, and productivity. McKinsey Global Institute, Washington, DC
Marinescu DC (2011) Classical and quantum information. Academic, Burlington, MA
Mowshowitz A (1968) Entropy and the complexity of graphs: I. An index of the relative complexity of a graph. Bull Math Biol 30(1):175–204
Ottmann T, Widmayer P (2012) Algorithmen und Datenstrukturen (5. Auflage). Spektrum Akademischer Verlag, Heidelberg
Patel VL, Arocha JF, Zhang J (2004) Thinking and reasoning in medicine Key. In: Holyoak K (ed) Cambridge handbook of thinking and reasoning. Cambridge University Press, Cambridge
Patel VL, Ramoni MF (1997) Cognitive models of directional inference in expert medical reasoning. In: Feltovich PJ, Ford KM (eds) Expertise in context: human and machine. The MIT Press, Cambridge, MA, pp 67–99
Peirce CS (1955) Abduction and induction. In: Peirce CS, Buchler J (eds) Philosophical writings of Peirce. Dover Publications, New York, pp 150–156
Pincus SM (1991) Approximate Entropy as a measure of system complexity. Proc Natl Acad Sci U S A 88(6):2297–2301
Posner E (1975) Random coding strategies for minimum entropy. IEEE Trans Inform Theory 21(4):388–391
Richman JS, Moorman JR (2000) Physiological time-series analysis using approximate entropy and sample entropy. Am J Physiol Heart Circ Physiol 278(6):H2039–H2049
Riffle M, Eng JK (2009) Proteomics data repositories. Proteomics 9(20):4653–4663
Rubinstein RY (1997) Optimization of computer simulation models with rare events. Eur J Oper Res 99(1):89–112
Shannon CE (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423
Simon HA (1973) The structure of ill structured problems. Artif Intell 4(3–4):181–201
Simonic KM, Holzinger A, Bloice M, Hermann J (2011) Optimizing long-term treatment of rheumatoid arthritis with systematic documentation. Proceedings of pervasive health—5th international conference on pervasive computing technologies for healthcare. IEEE, Dublin. pp. 550–554
Stevens SS (1946) On the theory of scales of measurement. Science 103:677–680
Thomas JJ, Cook KA (2005) Illuminating the path: the research and development agenda for visual analytics. IEEE Computer Society Press, New York
Wickens CD (1984) Engineering psychology and human performance. Charles Merrill, Columbus, OH
Yuan L, Kesavan H (1998) Minimum entropy and information measure. IEEE Trans Syst Man Cybern C Appl Rev 28(3):488–491
Zomorodian AJ (2005) Topology for computing. Cambridge University Press, Cambridge, MA
Author information
Authors and Affiliations
1 Supplementary Materials
Below is the link to the electronic supplementary material.
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Holzinger, A. (2014). Lecture 2 Fundamentals of Data, Information, and Knowledge. In: Biomedical Informatics. Springer, Cham. https://doi.org/10.1007/978-3-319-04528-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-04528-3_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-04527-6
Online ISBN: 978-3-319-04528-3
eBook Packages: EngineeringEngineering (R0)