The role of artificial intelligence in early detection of skin cancer
The use of AI tools in healthcare has led to significant advances in diagnostic and treatment methods, and doctors are increasingly testing and using AI robots in daily medical practice. As for skin cancer in particular, AI-powered diagnostic tools are expected to be widely used in this field in the future due to their significant role in helping dermatologists and medical students diagnose skin cancer cases with high accuracy.
Here are more details about the role of artificial intelligence in early detection of skin cancer:
Artificial Intelligence and Skin Cancer Diagnosis:
According to a study conducted at Stanford University School of Medicine and published in April of this year in the journal npj Digital Medicine, AI-powered tools could improve the accuracy of skin cancer diagnosis for doctors and medical students.
The researchers stressed that AI-based skin cancer diagnosis tools are developing rapidly, and these tools are expected to be widely used after they are verified and appropriate tests are conducted.
To investigate the impact of AI assistance on the accuracy of skin cancer diagnosis, the researchers conducted a systematic review and meta-analysis of a set of studies containing more than 67,000 assessments of potential skin cancers performed by a variety of medical students and dermatologists with and without AI assistance.
The researchers confirmed that artificial intelligence tools play an assistant role for doctors and do not work as a substitute for them, and the team investigated how artificial intelligence assistance affects doctors’ diagnostic performance.
Jiyeong Kim, a researcher at the Stanford Center for Digital Health, explained that the study he conducted with colleagues compared doctors working without the help of artificial intelligence with doctors who used artificial intelligence to diagnose skin cancer.
The study found that healthcare providers at all levels of training and specialties generally benefited from using AI tools in their work. Doctors and students not using AI were able to accurately diagnose 74.8% of skin cancer cases and correctly identify 81.5% of patients with skin cancer-like conditions. Those working with AI were able to correctly identify 81.1% of skin cancer cases and 86.1% of skin cancer-like lesions.
To determine which group benefited most from the use of AI in diagnosis, the researchers conducted subgroup analyses. These analyses showed that all medical groups benefited from these tools, but the largest improvements were among non-dermatologists.
The researchers noted that these results highlight the potential of AI to improve the learning experience for students in imaging-based medical specialties such as dermatology and radiology.
“This is a clear demonstration of how AI can be used in collaboration with physicians to improve patient care,” said Dr. Eleni Linos, director of the Center for Digital Health and professor of dermatology and epidemiology at Stanford University and a co-author of the study.
“If this technology can improve the accuracy of a doctor’s diagnosis and save him time, it will be beneficial to both the doctor and the patient,” she added. “In addition to helping patients get an accurate diagnosis of their conditions, it can help reduce doctor fatigue and improve personal relationships between doctors and their patients.”
Conclusion:
This study is one of a number of studies investigating how advanced analytics tools powered by AI and deep learning can enhance cancer care. It points to future developments in healthcare, particularly in the diagnosis of skin cancer, which has become increasingly prevalent at this time.
According to a study published in the journal BMJ Oncology , the number of people under the age of 50 diagnosed with cancer worldwide has increased by about 80% in three decades, and over the past decade, melanoma skin cancer rates have increased by about two-thirds (38%).
These numbers indicate the need for advanced tools that can detect this type of cancer quickly. The earlier skin cancer is detected, the easier it is to treat.