Artificial intelligence in healthcare
Artificial Intelligence in Healthcare
Artificial Intelligence in Healthcare (pronunciation: /ɑːrˈtɪfɪʃəl ɪnˈtɛlɪdʒəns ɪn ˈhɛlθkeər/) refers to the use of complex algorithms and software, also known as Artificial Intelligence (AI), to emulate human cognition in the analysis, interpretation, and comprehension of complicated medical and healthcare data. The etymology of the term "Artificial Intelligence" is derived from the English words "artificial" meaning made or produced by human beings rather than occurring naturally and "intelligence" meaning the ability to acquire and apply knowledge and skills.
Related Terms
- Machine Learning: A subset of AI that involves the use of statistical techniques to enable machines to improve with experience.
- Deep Learning: A type of machine learning that trains a computer to perform human-like tasks, such as recognizing speech, identifying images or making predictions.
- Predictive Analytics: The use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.
- Natural Language Processing: A branch of AI that helps computers understand, interpret and manipulate human language.
- Robotics: A field of engineering focused on the design and manufacturing of robots, often used in healthcare for tasks such as surgery or patient care.
Applications
Artificial Intelligence in Healthcare is used in various applications such as Medical Imaging, Drug Discovery, Genomics, Patient Monitoring, and Telemedicine. These applications help in improving patient care, reducing healthcare costs, and enhancing efficiency and productivity.
Challenges
Despite its potential, the use of AI in healthcare also presents several challenges including data privacy, ethical considerations, and the need for regulatory oversight.
See Also
External links
- Medical encyclopedia article on Artificial intelligence in healthcare
- Wikipedia's article - Artificial intelligence in healthcare
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