ANN (Artificial Neural Network)
An artificial neural network (ANN), usually called “neural network” (NN), is a mathematical model or computational model that tries to simulate the structure and/or functional aspects of biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase. Modern neural networks are non-linear statistical data modeling tools. They are usually used to model complex relationships between inputs and outputs or to find patterns in data. (definition courtesy of Wikipedia)
ANNs are now being used for medical diagnoses.
The advantages that machines with artificial intelligence, or more specifically, Artificial Neural Networks (ANN) bring to this field are many:
”¢ They bring down the costs of medical diagnoses and treatment.
”¢ They can learn from information and data that is made available on a continuous basis, and so, take logical decisions without making errors.
”¢ When doctors are tired and overworked, they tend to make mistakes that affect the lives and health of their patients. Machines are not limited or hampered by physical constraints and can work for long hours without giving in to emotions or fatigue.
”¢ They help minimize invasive procedures – a case in point is the ANN program used last year by the Mayo Clinic to help doctors accurately diagnose patients with the heart infection endocarditis without the need for an invasive procedure, thus reducing overall healthcare costs and costs to the patient as well.
”¢ The highly structured reasoning abilities of ANNs allow doctors to make “educated” decisions based on their intuitions. With ANN, intuition is backed by solid knowledge, a combination that reduces the risk of medical errors by a great percentage.
”¢ They provide doctors with all the facts needed to make accurate decisions, facts that are often ignored or forgotten in the myriad of things going on in the minds of physicians because of their professional and personal lives.