- Artificial Intelligence(AI) in healthcare is the use of algorithms and software to approximate human cognition in the analysis of complex medical data. Specifically, AI is the ability for computer algorithms to approximate conclusions without direct human input.
- The primary aim of health-related AI applications is to analyze relationships between prevention or treatment techniques and patient outcomes.AI programs have been developed and applied to practices such as diagnosis processes, treatment protocol development, drug development, personalized medicine,and patient monitoring and care.
- Medical institutions such as The Mayo Clinic, Memorial Sloan Kettering Cancer Center, Massachusetts General Hospital, and National Health Service, have developed AI algorithms for their departments. Large technology companies such as IBM and Google, and startups such as Welltok and Ayasdi, have also developed AI algorithms for healthcare.
- Artificial intelligence in medicine may be characterized as the scientific discipline pertaining to research studies, projects, and applications that aim at supporting decision-based medical tasks through knowledge- and data-intensive computer-based solutions that ultimately support and improve the performance of a human care provider.
- The purpose of this special issue is to demonstrate the potential of several intelligent approaches exploited in medical informatics technologies and applications.
- While research on the use of AI in healthcare aims to validate its efficacy in improving patient outcomes before its broader adoption, its use may nonetheless introduce several new types of risk to patients and healthcare providers, such as algorithmic bias, Do not resuscitate implications, and other machine morality issues. These challenges of the clinical use of AI has brought upon potential need for regulations.
Medical and technological advancements occurring over this half-century period that have simultaneously enabled the growth healthcare-related applications of AI include:
- Improvements in computing power resulting in faster data collection and data processing.
- Increased volume and availability of health-related data from personal and healthcare-related devices.
- Growth of genomic sequencing databases
- Widespread implementation of electronic health record systems.
- Improvements in natural language processing and computer vision, enabling machines to replicate human perceptual processes.
- Enhanced the precision of robot-assisted surgery.
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