Abstract
Artificial intelligence (AI) has wide applications in healthcare, including dermatology. Machine learning (ML) is a subfield of AI involving statistical models and algorithms that can progressively learn from data to predict the characteristics of new samples and perform a desired task. Although it has a significant role in the detection of skin cancer, dermatology skill lags behind radiology in terms of AI acceptance. With continuous spread, use, and emerging technologies, AI is becoming more widely available even to the general population. AI can be of use for the early detection of skin cancer. For example, the use of deep convolutional neural networks can help to develop a system to evaluate images of the skin to diagnose skin cancer. Early detection is key for the effective treatment and better outcomes of skin cancer. Specialists can accurately diagnose the cancer, however, considering their limited numbers, there is a need to develop automated systems that can diagnose the disease efficiently to save lives and reduce health and financial burdens on the patients. ML can be of significant use in this regard. In this article, we discuss the fundamentals of ML and its potential in assisting the diagnosis of skin cancer.
Highlights
Published: 20 December 2021Cancer is one of the major healthcare burdens across the world
It should be noted that different results from different studies suggest that the amount of data presented to the Artificial intelligence (AI) system, the methodology used for the study, and the complexity of disease may affect the level of difficulty for a given task and the performance of both AI algorithms and human observers
We feel that if increased accuracy and early detection is possible with Machine learning (ML), it may be well accepted by the clinicians
Summary
Cancer is one of the major healthcare burdens across the world. Global statistics suggest almost 10.0 million deaths (9.9 million excluding non-melanoma skin cancer) due to cancer in the year 2020. Several advancements in science and technology have resulted in the availability of different non-invasive imaging methods to detect melanoma [4] The accuracy of these methods in the diagnosis of melanoma and other skin cancers is still a point of discussion. There is rising optimism regarding applications of AI in healthcare, ranging from assistance in medical diagnostics, treatment and administrative support to reduce timelines of new drug development. It may be of benefit as an adjuvant in clinical decision making [9]. Important websites related to skin cancer and related AI resources were browsed to gather information on the topic
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