AI has contributed a lot to the healthcare field, including dermatology. However, what are the challenges dermatologists are facing currently?
FREMONT, CA: The increasing significance of artificial intelligence (AI) globally, has led to countless attempts at leveraging such technology to deal with challenging healthcare issues. Thus, scientists are trying to integrate this technology in the field of dermatology as well.
The subject dermatology is based on morphological features, and most of the diagnoses are based on visual pattern recognition. Dermatology is extremely suitable for implementing AI image recognition capabilities for diagnosis.
What kind of challenges can AI bring in the future?
Presently many large dermatology companies are extensively using AI in their treatments. Many developed nations across the globe have actively formulated strategic plans for the development and promotion of AI.
Although dermatological AI has evolved exponentially in recent years, it has faced bottlenecks in the hospitals. Numerous issues are required to be solved urgently.
First, the existing scale of skin disease image data is still not sufficient, the quality and standard of skin images are not uniform, and there is a low level of information sharing between hospitals. Thus, it becomes difficult to achieve high-quality image data, which leads to unreliable research results.
Second, the integration of medical and AI intricate talents are extremely rare. It is indispensable to coordinate closely with multi-disciplinary personnel in computer science, medical, and biomedical.
Third, there are multiple kinds of diseases in dermatology. Dermatological AI can identify only one or a group of particular skin diseases. Making AI identify more skin disease is one of the bottlenecks in AI treatment of skin diseases.
Fourth, the present AI treatment also involves legal issues, data privacy issues, and ethical issues that have not been mitigated yet.
Fifth, the treatment of skin diseases require not only clinical and skin images but also detailed consideration of patient history, age, gender, and other information to achieve an accurate diagnosis. Hence, skin image data and information of the patient is required to be integrated, and AI is utilized to comprehensively evaluate these data, thereby playing a significant role in disease diagnosis, treatment decision-making, and future prognosis judgment.
Besides, AI is not an alternative for the interaction between the doctors and patients, nor can it offer patient care and humanistic care. In the face of these thorny issues, dermatologists and related field professionals are trying to resolve the multiple problems.