Difference between revisions of "Computational informatics"

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''(This article was taken from Wikipedia)''
Informatics is the academic field concerned with the study of the structure, the communication, and the use of [[information]].  '''Computational informatics''', as a subfield of informatics, studies information using computational methodologies. Computational informatics can also be interpreted as the use of computational methods in the information sciences.


Informatics is the academic field concerned with the study of the structure, the communication, and the use of information.  Computational informatics, as a subfield of informatics, studies information using computational methodologies. Computational informatics can also be interpreted as the use of computational methods in the information sciences.
== Development ==
From a historical viewpoint, medical informatics scientists (also known as medical informaticians) started to use artificial intelligence and Baysian statistical methods in diagnosis and medical decision making, as early as in the 1970s.  An example is the [[MYCIN]] system developed at Stanford University.  The field has since evolved to use a wide range of computational methods and to interact with all possible scientific and other disciplinary domains. In the recent years, the field integrates the following:


== Development ==
# Computational techniques: Artificial intelligence, algorithms (for architectures ranging from single CPU to massively parallel machines), programming, object-oriented system design, databases, information retrieval, computer graphics and visualization.
# Probability, statistics and decision science: Theory of probability, statistical inference, cost/risk-benefit analysis, probabilistic analysis, stochastic modeling, decision theory, statistical data analysis, probabilistic networks, pattern classification, statistical learning and modeling, statistical data mining.
# Applied mathematics: Graph theory, differential equations, optimization theory, wavelets, group theory.
# Electrical engineering methods: signal and image processing.
# Domain knowledge: Art and cultural heritages, biology, chemistry, engineering, medicine, the Web.
# User sciences: Design, human-computer interaction, evaluation.
# Cyberinfrastructure for informatics: search engines, digital repositories, storage.
# Scientometrics and bibliometrics: science and policy evaluation, knowledge discovery.


From a historical viewpoint, medical informatics scientists (also known as medical informaticians) started to use artificial intelligence and Baysian statistical methods in diagnosis and medical decision making, as early as in the 1970s.  An example is the MYCIN system developed at Stanford University.  The field has since evolved to use a wide range of computational methods and to interact with all possible scientific and other disciplinary domains. In the recent years, the field integrates the following:
== Education ==
Several universities offer graduate programs in this area.  One example is the Penn State College of Information Sciences and Technology.  Some programs are targeted at specific domains.  For instance, the Biomedical Informatics Program at Stanford University focuses on technologies and methods for understanding biomedical data and to improve health care.


1) Computational techniques: Artificial intelligence, algorithms (for architectures ranging from single CPU to massively parallel machines), programming, object-oriented system design, databases, information retrieval, computer graphics and visualization.</br>
==Notes==
2) Probability, statistics and decision science: Theory of probability, statistical inference, cost/risk-benefit analysis, probabilistic analysis, stochastic modeling, decision theory, statistical data analysis, probabilistic networks, pattern classification, statistical learning and modeling, statistical data mining.</br>
3) Applied mathematics: Graph theory, differential equations, optimization theory, wavelets, group theory.</br>
4) Electrical engineering methods: signal and image processing.</br>
5) Domain knowledge: Art and cultural heritages, biology, chemistry, engineering, medicine, the Web.</br>
6) User sciences: Design, human-computer interaction, evaluation.</br>
7) Cyberinfrastructure for informatics: search engines, digital repositories, storage.</br>
8) Scientometrics and bibliometrics: science and policy evaluation, knowledge discovery.</br>


== Education ==
This article heavily reuses content from [http://en.wikipedia.org/wiki/Computational_informatics the Wikipedia article].


Several universities offer graduate programs in this area.  One example is the Penn State College of Information Sciences and Technology.  Some programs are targeted at specific domains.  For instance, the Biomedical Informatics Program at Stanford University focuses on technologies and methods for understanding biomedical data and to improve health care.
==References==
<references />


[[Category:Computational informatics]]
[[Category:Informatics]]

Latest revision as of 19:54, 24 February 2016

Informatics is the academic field concerned with the study of the structure, the communication, and the use of information. Computational informatics, as a subfield of informatics, studies information using computational methodologies. Computational informatics can also be interpreted as the use of computational methods in the information sciences.

Development

From a historical viewpoint, medical informatics scientists (also known as medical informaticians) started to use artificial intelligence and Baysian statistical methods in diagnosis and medical decision making, as early as in the 1970s. An example is the MYCIN system developed at Stanford University. The field has since evolved to use a wide range of computational methods and to interact with all possible scientific and other disciplinary domains. In the recent years, the field integrates the following:

  1. Computational techniques: Artificial intelligence, algorithms (for architectures ranging from single CPU to massively parallel machines), programming, object-oriented system design, databases, information retrieval, computer graphics and visualization.
  2. Probability, statistics and decision science: Theory of probability, statistical inference, cost/risk-benefit analysis, probabilistic analysis, stochastic modeling, decision theory, statistical data analysis, probabilistic networks, pattern classification, statistical learning and modeling, statistical data mining.
  3. Applied mathematics: Graph theory, differential equations, optimization theory, wavelets, group theory.
  4. Electrical engineering methods: signal and image processing.
  5. Domain knowledge: Art and cultural heritages, biology, chemistry, engineering, medicine, the Web.
  6. User sciences: Design, human-computer interaction, evaluation.
  7. Cyberinfrastructure for informatics: search engines, digital repositories, storage.
  8. Scientometrics and bibliometrics: science and policy evaluation, knowledge discovery.

Education

Several universities offer graduate programs in this area. One example is the Penn State College of Information Sciences and Technology. Some programs are targeted at specific domains. For instance, the Biomedical Informatics Program at Stanford University focuses on technologies and methods for understanding biomedical data and to improve health care.

Notes

This article heavily reuses content from the Wikipedia article.

References

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