Artificial Intelligence in Healthcare Department
Artificial Intelligence (AI) is the science and technology for creating intelligent machines that can display behaviors that people think are intelligent. He developed an expert system that uses conversation software – technology that machines can use to talk to people in natural languages. AI has come a long way. That starts to influence the decision. He began to provide data, analyze data trends, estimate, develop data consistency, measure uncertainty, and propose mitigation measures to anticipate the data needs of users to provide the information they provide. need in the most appropriate form and even propose alternative approaches.
Artificial intelligence through expert and knowledge-based systems is used in clinical settings. Expert systems contain medical knowledge and data files, especially for specific tasks, and can compare and justify the data collected from each patient to draw justified conclusions. The knowledge base in expert systems comes from a set of rules.
As explained by Enrico Coiera in his guide to medical informatics, the internet and telemedicine, there are several clinical / health tasks that AI and expert systems can apply. Some of them are:
Create reminders and reminders. An expert system that is connected to the monitor can warn of changes in patient conditions. It can even scan laboratory test results or drug orders and send reminders or warnings via a messaging system.
Help diagnose. Expert systems can help in making possible diagnoses based on patient data.
Critical planning and therapy. The system can look for inconsistencies, errors and omissions in the existing treatment plan, or formulate treatment based on the patient’s specific conditions and guidelines for the treatment received.
Agent to retrieve information. Fitness Software agents can be sent to find and retrieve information, such as the Internet, that is deemed relevant to certain problems. The agent knows the user’s preferences and needs and may also need medical knowledge to assess the importance and usefulness of what he has discovered.
Image recognition and interpretation. Many medical images can now be interpreted automatically, from flat X-rays to more complex images such as angiograms, CT scans and MRIs. This is useful, for example, in mass screening, when the system can report potentially abnormal images for detailed human attention.
