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Week 5 Discussion
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Week 5 Discussion
Meeting medical challenges with artificial intelligence has never been too easy. Sometimes a machine can not access a patient’s medical condition which a doctor can more promptly or otherwise accurately. However, doctor’s are limited and can not be present everywhere at the same time. The new technological advancements allow doctors to transmit their knowledge into these machines so that these expert systems, neural networks, and genetic algorithms can be performing the same tasks more accurately (Miller, & Brown, 2018). An example of an expert system can be identified as a symbolic lisp machine. Moreover, an example of a neural network can be taken as deep reservoir computing, and lastly, an example for genetic algorithms can be considered as Java. While discussing genetic algorithms, it is essential to have an in-depth analysis of this particular artificial intelligence. It is important to analyze how health practitioners use it to manage clinical functions on a daily basis.
This Java system recognized as one of the genetic algorithms is widely used in many computer systems. It contains binary values from 0 and 1. Each number has a fitness value thus five 1s would make it maximum fitness where one 1s would make it the lowest fitness. When using this particular intelligence method to assess a person’s health, the genetic algorithm tries to maximize the fitness function to provide a number to evaluate the individual (Ghaheri et al. 2015). So if the value is five 1s, that means the patient is fit, but if the amount has one 1s, that means that the patient has the lowest fitness and would require further medical assessment. This method is widely used across hospitals and clinics and helps save time and cost of both the patient and the doctor. Such practices can influence a positive change amongst the medical profession and help with more advancements in the field of artificial medical intelligence.
References
Ghaheri, A., Shoar, S., Naderan, M., & Hoseini, S. S. (2015). The applications of genetic algorithms in medicine. Oman medical journal, 30(6), 406.
Miller, D. D., & Brown, E. W. (2018). Artificial intelligence in medical practice: the question to the answer?. The American journal of medicine, 131(2), 129-133.
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