AI is rapidly transforming medicine and health care, allowing for significant advancements in fields such as medical diagnostics, drug development, treatment personalization, supportive health services, genomics, and public health management.
One of the major motivations for using AI in health care is to simulate or improve the efficiency of human healthcare professionals. Computer vision (CV) is another emerging application of AI which involves image processing, pattern recognition, and response. It is useful in many medical fields such as differentiating benign lesions from malignant ones. With an increase in the availability of a large amount of visual medical data, advanced processing algorithms, and superior storage devices and cameras, the use of CV in medicine is expected to continue growing.
There are concerns about the effectiveness and impact of artificial intelligence in the medical field because of the technical, emotional, and legal complexities of the field. AI-based technology could provide more accurate diagnoses, administration, decision-making, big data analytics, and post-graduate education. Every parameter and element cannot, however, be translated into a programming language. In addition, the data points that contribute to a medical decision are not based on clinical trials or peer-reviewed literature. AI is not the ultimate solution for all the challenges healthcare faces today. However, it is inevitable and advantageous for caregivers in many areas. However, AI does not cover the whole process of treatment: empathy, proper communication and the human touch are still equally essential. No application, software or device can replace personal connection and trust. The role of the human physician is inevitable. But AI could be a very useful cognitive assistant by augmenting doctors’ capabilities.
In the iToBoS project we are using CV to process images taken by the scanner to detect and diagnose skin lesions in a standard and rapid way to assist dermatologists. The iToBoS scanner will not replace doctors in the future, but it will extend doctors’ capabilities by decreasing diagnosis time and error and increasing treatment accuracy and efficiency.