One area where human intelligence is limited is in the area of medicine. It often takes a doctor to determine a medical condition, and doctors cannot be everywhere. However, if the knowledge and processes that doctors use can be transmitted to machines, the knowledge and diagnosis of the medical field can be greatly expanded. Discuss how expert systems, neural networks, and genetic algorithms can help scientists meet medical challenges. Provide an example of each system. Select one of your three examples and describe the system more in-depth. Give an example of a system currently being used and describe how and where it is in use today. ANSWER Meeting Medical Challenges with Artificial Intelligence Artificial intelligence makes it possible for computer algorithms to approximate medical care conclusions without direct input from humans (Peek, Combi, Marin & Bellazzi, 2015). The use of technology in healthcare has dramatically expanded the medical field by allowing for the determination of health conditions without the presence of healthcare practitioners. The advanced systems have also led to the improvement in the record-keeping mechanisms and detection of minor details that could be … Medical scientists can solve health challenges through the use of neural networks, expert systems, and genetic algorithms. First of all, neural networks include algorithm sets, designed for the recognition of patterns. They are used in handling issues that humans are not good at dealing with, such as problems that include prediction (Misiunas, Oztekin, Chen & Chandra, 2016). This form of artificial intelligence system is currently applied in Atomwise company, where the power of neural networks and machine learning are used to assist healthcare researchers in the discovery of more effective treatments. Secondly, the expert system involves computer systems that simplify the correlation, analysis, and sharing of medical data to determine treatment effectiveness. The system also improves the health evaluation process and its comprehensiveness. Common examples of expert systems include MYCIN and DENDRAL. MYCIN is based on backward chaining and identifies bacteria that can cause acute infections. DENDRAL is applied for chemical analysis to get a prediction of the structure of molecules. Lastly, genetic algorithms are techniques for tacking optimization challenges, based on natural selection, a process that controls biological evolution (Witchey, 2015). The use of the genetic algorithm has benefited the healthcare industry in different medical specialties. Genetic algorithms … The most applied form of artificial intelligence in the present-day healthcare field is the expert systems. The systems offer a significant expertise level within a reasonable time. It takes less time compared to the duration humans could take to create a perfect solution for the same issue. Major components of an expert system are human expert, knowledge engineer, information base, inference engine, user interface, and finally, the user (Shi, Boudouh & Grunder, 2017). A typical example of expert system application is in the CaDet, which helps in the identification of cancer in its early stages. The system is used in cancer centers to detect cancer cells before they become toxic, creating room for improved life quality and survival chances… |
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