IndexIntroductionSummaryConclusionIntroductionArtificial intelligence is the ability of a computer or computer-controlled robot to perform tasks commonly associated with intelligent beings. When asked about AI, the average person can immediately imagine the Hollywood portrayal of AI as a Terminator, however, this is a great exaggeration of AI's current capability. AI starts with a program that learns how to perform the basic tasks it has been trained to do, and with each succession of its task, the task will become more difficult. This “trains” the AI ​​on how to calculate or complete more complex tasks over time. Depending on the task the AI ​​was challenged to complete, the resulting AI may be more specialized in a particular task. While great strides have been made in the development of computer processing speed and memory capacity, there are no artificial intelligence programs that can match the flexibility of a human in broader scopes or tasks that require everyday knowledge. By specializing in a specific category, however, AI can match the performance levels of human experts such as medical diagnosis, search engines, or speech and writing recognition. The use of artificial intelligence has made its way into areas of medical science and has since been used in a number of different medical fields to advance therapeutic development. Artificial intelligence has since been widely used in a number of medical fields such as the diagnosis of acute and chronic diseases. In this critical essay, we will focus on the use of AI in melanoma detection, with references to Cui et al's research in evaluating the effectiveness of AI methods for melanoma. In this research, their goal is to determine the most effective AI method for diagnosing melanoma. Overall, the use of AI would represent a significant advantage in the diagnosis of diseases such as melanoma, given the accuracy of its results, however, this does not mean that it should be used blindly to diagnose every patient, rather it should be used supervision by human experts. however, be an integral part of the diagnosis. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original EssaySummaryThe use of artificial intelligence in the field of medical sciences has grown widely to include disease diagnosis. Research into evaluating the most effective AI method for diagnosing melanoma will be the focal area around which this review will revolve. The method seemed adequate, where both AI training methods, traditional machine learning and deep learning algorithms, were tested against the same sample data set, a large set consisting of 2200 images of which 564 were melanomas and the rest were non-melanomas, and a subset containing 606 images of which 295 were melanomas and 311 non-melanomas, ensuring reliable and valid results. In the evaluation of traditional AI machine learning, the use of 4 fully automatic image segmentation algorithms was appropriately used to segment melanoma. However, further explanations of what dilation, corrosion and hole filling are could be provided to further explain the image processing processes. The morphological characteristics, the area, the.