Abstract
The terminology Artificial Intelligence (AI) describes the application computing systems and technology to effectively simulate smart actions and smart thinking compared to the human mind. The concept of AI was introduced as the engineering and science of making smart machines that can operate without the engagement of humans using Machine Learning (ML). This research provides a wider scope of the concept of AI in the medical field, handling the various concepts and terms associated with the concept, including the present and future implementation of the concept. The major research materials applied are Google and PubMed searches, which were conducted using the “Artificial Intelligence” as the basic keyword. More references were retrieved by cross-referencing major publications. The advancements in AI technology in recent times and the present application of medicine have been analyzed critically. This paper ends with an assumption that AI focuses on implementing changes in the medical practices in previously unidentified ways. However, many of the application are still in the initial stages and require exploration and development. In addition, clinical experts have to comprehend and adapt with development for effective delivery of medical services.
Highlights
Several clinical issues are ideal for Artificial Intelligence (AI) technologies, because to advances in computing power and large quantities of data produced in medical systems
The concept of AI was introduced as the engineering and science of making smart machines that can operate without the engagement of humans using Machine Learning (ML)
There are two ways that AI systems vary from living beings: (1) Techniques are accurate: once a goal has been achieved, the machine learns primarily from the data input and could only fully comprehend what it has been conditioned to do; (2) Some deep learning methods are mechanical devices: they can anticipate with absolute accuracy but provide almost no intelligible elaboration of the reasoning behind their decision making, aside from the documentation as well as category of automated system used
Summary
Several clinical issues are ideal for AI technologies, because to advances in computing power and large quantities of data produced in medical systems. The following are two recent examples of reliable and medically relevant heuristics that may help both physicians and patients by simplifying diagnosis. One of the many known instances of AI Algorithms that surpass physicians in picture classification techniques is the first of such techniques. Scientists at Seoul Health Center and College of Medicine created the DLAD (Machine Learning based Automated Diagnosis) AI system to scan plain radiography and identify aberrant cell development, such as possible malignancies [1], in the autumn of 2018 (see Fig 1). The application's results are compared to that of various physicians' detecting skills, and it surpassed 17/18 physicians. You can see the image that was used to train AI applications. According to Automated Processes, the right column illustrates a region of potentially harmful cells that a doctor should study further
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