Difference between revisions of "Artificial Neural Networks"

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Back? [[Extensions to our physical path... but what about mental power?]]
[[China becoming the largest economy]]


==Description:==
==Description:==


[[Image:NEURON.jpg|thumb|Picture of a neuron]]
According to the CBP (Centraal Plan Bureau) the demand for health care in The Netherlands will increase with 40% between 2000 and 2015. To be able to supply the required healthcare improved efficiencies and tailor-made health care at home are required. Technological innovations in health care equipment and ICT innovations are essential to improve the efficiencies and treatment at home. New developments are telecare, telemedicine, e-health and domotica.  
Artificial Neural Networks (ANNs) are information processing models that are inspired by the way biological nervous systems, such as the brain, process information. The models are composed of a large number of highly interconnected processing elements (neurones) working together to solve specific problems. ANNs, like people, learn by example. Contrary to conventional computers -that can only solve problems if the set of instructions or algorithms are known- ANNs are very flexible, powerfull and trainable. Conventional computers and neural networks are complementary: a large number of tasks require the combination of a learning approach and a set of instructions. Mostly, the conventional computer is used to supervise the neural network.


For more information: http://en.wikipedia.org/wiki/Neural_network 
The objectives of innovation in health care are:
 
- increased efficiency
- reduced costs
- increased quality and tailor-made health care


==Enablers:==
==Enablers:==


1. Research & Development: Mathimaticians, Psychologists, Neurosurgeons,...
1. Aging population <br>
 
2. Technological innovations <br>
2. Applications using artificial neural networks (e.g. sales forecasting, data validation, etc from NeuroDimension) [http://www.nd.com].
3. Developments in ICT <br>
 
4. Open markets in health care <br>
3. Funding from international institutes ( e.g. IST).
 
4. New technologies that enable profound research of the human brain activity.


==Inhibitors:==
==Inhibitors:==


1. Outcome ethical issues: Is there a danger developing technologies that might perform similar (thinking) functions as the human brain?  
1. Too much focus on technology, to little focus on patient. (It works, but does is help the patient?) <br>
 
2. A critical mass needs to adopt an innovation <br>
2. Research ethical issues: Is it ethical to perform research and do experiments on the human brain and its functions?
3. Lack of time, communication and financial resources <br>
 
3. Lack of scope and focus: this new technology might create the next information society revolution, thus interest is high and widely spread over several industries. 


==Paradigms:==
==Paradigms:==


1. Simple tasks can already be learned today by artificial neural networks. Further investigation, in the power of those systems as well as in the power of the combination with conventional computer systems, will increase the power of a connected world or the internet.  
Due to the aging population in The Netherlands the demand for health care will increase. Technological innovations and innovations in ICT can make health care more efficient, cheaper, more patient-friendly and better tailor-made. The open markets in health care make effective implementations of innovations in health care possible.


2. ANNs will disappear as black boxes into our daily lives, supporting us with simple decision making where making a mistake is allowed (children's level). To increase the learning effect and for control purposes, these boxes will be interconnected via the internet.
 
==Experts:==
==Experts:==
 
1. Engineers <br>
Prof. Dr. Hugo de GARIS,
2. ICT specialists <br>
 
3. Technological experts <br>
Associate Professor,
4. Managers in health care <br>
 
5. Health insurance experts <br>
Head, Brain Builder Group,
6. Patient representatives
 
Computer Science Dept.,
 
Utah State University, USU,
 
Old Main 423, Logan,
 
Utah, UT 84322-4205, USA.
 
tel: + 1 435 797 0959
 
fax: + 1 435 797 3265
 
cell: +1 435 512 1826
 
degaris@cs.usu.edu
 
http://www.cs.usu.edu/~degaris
 
 
 
==Timing:==
 
1933: psychologist Edward Thorndike suggests that human learning consists in the strengthening of some (then unknown) property of neurons.
 
1943: first artificial neuron is produced (neurophysiologist Warren McCulloch & logician Walter Pits).
 
1949: psychologist Donald Hebb suggests that a strengthening of the connections between neurons in the brain accounts for learning.
 
1954: first computer simulations of small neural networks at MIT (Belmont Farley and Wesley Clark).
 
1958: Rosenblatt designs and develops the Perceptron, the first neuron with three layers.
 
1969: Minsky and Papert generalises the limitations of single layer Perceptrons to multilayered systems (e.g. the XOR function is not possible with a 2-layer Perceptron)
 
1972: A. Henry Klopf develops a basis for learning in artificial neurons based on a biological principle for neuronal learning called heterostasis.
 
1974: Paul Werbos develops the back-propagation learning method, the most well known and widely applied of the neural networks today.
 
1975: Fukushima (F. Kunihiko) develops a step wise trained multilayered neural network for interpretation of handwritten characters (Cognitron).  
 
1986: David Rumelhart & James McClelland train a network of 920 artificial neurons to form the past tenses of English verbs (University of California at San Diego).


==Web Resources:==
==Web Resources:==


1. http://www.doc.ic.ac.uk/~nd/surprise_96/journal/vol4/cs11/report.html
www.zorgmarketingplatform.nl <br>
 
www.managementkennisbank.nl
2. http://www.inns.org/
 
3. http://www.nd.com/
 
4. http://www.dacs.dtic.mil/techs/neural/neural_ToC.html
 
5. http://www.ieee-nns.org/
 
6. http://www.economist.com/opinion/PrinterFriendly.cfm?Story_ID=1143317: The mind's eye
 
7. http://www.hirnforschung.net/cneuro/

Latest revision as of 06:26, 6 September 2011

China becoming the largest economy

Description:

According to the CBP (Centraal Plan Bureau) the demand for health care in The Netherlands will increase with 40% between 2000 and 2015. To be able to supply the required healthcare improved efficiencies and tailor-made health care at home are required. Technological innovations in health care equipment and ICT innovations are essential to improve the efficiencies and treatment at home. New developments are telecare, telemedicine, e-health and domotica.

The objectives of innovation in health care are: - increased efficiency - reduced costs - increased quality and tailor-made health care

Enablers:

1. Aging population
2. Technological innovations
3. Developments in ICT
4. Open markets in health care

Inhibitors:

1. Too much focus on technology, to little focus on patient. (It works, but does is help the patient?)
2. A critical mass needs to adopt an innovation
3. Lack of time, communication and financial resources

Paradigms:

Due to the aging population in The Netherlands the demand for health care will increase. Technological innovations and innovations in ICT can make health care more efficient, cheaper, more patient-friendly and better tailor-made. The open markets in health care make effective implementations of innovations in health care possible.

Experts:

1. Engineers
2. ICT specialists
3. Technological experts
4. Managers in health care
5. Health insurance experts
6. Patient representatives

Web Resources:

www.zorgmarketingplatform.nl
www.managementkennisbank.nl

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