RIYADH: To increase the efficiency and effectiveness of dermatological care, experts from Saudi Arabia's King Abdullah University of Science and Technology have developed a new diagnostic system, SkinGPT-4, which leverages the power of artificial intelligence.
Xin Gao, a professor of computer science, co-chair of the Center of Excellence on Smart Health, and head of the Bioinformatics Platform at KAUST, who led the research, says that SkinGPT-4 aims to identify appropriate treatments for skin, Diagnose and identify them. Diseases
Developed in partnership with Juexiao Zhou, PhD candidate at KAUST, first author of SkinGPT-4, Gao says the technology could provide a potentially life-saving service to patients, especially In rural areas where shortages are common. of trained dermatologists.
“These specific challenges in dermatology led to the creation of SkinGPT-4,” Gao told Arab News. “The variability in skin presentations and the need for specialized knowledge to accurately identify and treat these conditions highlighted the need for an innovative, AI-powered solution.”
The team identified the need for such a solution after recognizing the limitations of traditional diagnostic methods and the potential of AI, particularly large language models (LLMs) such as ChatGPT, to increase the accuracy and efficiency of dermatological diagnosis.
Gao said, “With SkinGPT-4, users can upload their own skin images for diagnosis and SkinGPT-4 can independently characterize and categorize skin conditions, analyze , can provide treatment recommendations, and allow for interactive diagnostics,” Gao said.
SkinGPT-4 diagnoses conditions that have distinct visual characteristics, such as acne, rosacea, melanoma, psoriasis, basal cell carcinoma, eczema, and more.
Development of SkinGPT-4 began with data collection and preprocessing, followed by model training and validation, Gao said. “The team collected a large data set of dermatological images and patient records to train the AI model,” he said.
“One of the key challenges was integrating diverse data types, including images and text, which required collaboration between computer scientists and dermatologists. The multidisciplinary team worked together to ensure Can AI effectively interpret and analyze skin disease images?
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The SkinGPT-4 diagnoses conditions that have distinct visual features, such as melanoma, psoriasis, and eczema.
• It uses a combination of computer vision algorithms, large language models, and natural language processing.
• This technology can help doctors and patients in rural areas where there is often a shortage of trained dermatologists.
SkinGPT-4 uses a combination of computer vision algorithms, LLMs, and natural language processing (NLP), enabling programs to understand human languages.
“The model processes dermatological images using a vision transformer (ViT) to identify patterns and characteristics of skin variations,” Gao said.
“VIT is combined with an LLM called Llama-2-13b-chat on our dataset with a customized two-step training strategy. By doing this, LLM can understand Llama-2-13b-chat skin disease images. and allows the diagnosis to be communicated with the patient in natural language.
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SkinGPT-4 may be particularly useful in diagnosing rare skin conditions that are not easily recognized by general practitioners.
“A patient presenting with an unusual rash can be quickly and accurately diagnosed using SkinGPT-4, which is trained on a wide array of dermatological images, including rare conditions,” Gao said.
“Additionally, for the management of chronic skin diseases such as psoriasis, SkinGPT-4 can monitor treatment progress and response, provide ongoing support and adjust treatment plans as needed.”
The researchers hope that SkinGPT-4 will be a game changer for remote or underserved areas where there is a shortage of dermatologists.
“For example, in a rural community where the nearest dermatologist is hundreds of miles away, a patient presents with a suspicious lesion that may be a rare form of skin cancer,” Gao said.
“Using SkinGPT-4, a local healthcare provider can take a high-resolution image of a wound and enter the patient's medical history into the system. SkinGPT-4 analyzes the image and patient information. , provides immediate initial assessment and recommendations for further action.
And as SkinGPT-4 evolves, Gao said the system will learn from its mistakes through a continuous learning and feedback mechanism.
“By analyzing misdiagnosis and adding corrections, the system can refine its algorithm and improve its accuracy over time,” he said. “This iterative learning process ensures that SkinGPT-4 evolves and adapts to new data and emerging trends in dermatology.”
However, Gao is keen to stress that SkinGPT-4 is not designed to completely replace dermatologists. Rather, the program is designed to serve as an evolving and improving tool, serving as an aid in facilitating communication between patients and physicians.
“Our ambition for SkinGPT-4 is to provide patients with more information about skin diseases, while providing valuable assistance to physicians in the diagnostic process.”