The accurate diagnosis and treatment of dermatological ailments rely on visual presentation and morphological attributes of skin lesions. However, misdiagnosis is common due to similarities between skin conditions, such as psoriasis and lichen planus. Psoriasis is a chronic inflammatory disorder affecting 1-3% of the global population, while lichen planus is an inflammatory skin pathology with no definitive cure. Distinguishing between these conditions is challenging, requiring clinical assessment and histopathological examination.
Recent studies have explored the use of artificial intelligence (AI) in dermatology to improve diagnostic accuracy. Deep learning models have been trained to identify skin diseases like psoriasis and lichen planus from images, achieving results comparable to experienced dermatologists. AI techniques have shown promise in accurately categorizing a wide range of skin diseases, enhancing diagnostic capabilities and reproducibility.
Researchers have developed advanced expert systems using deep learning models like EfficientNet and ResNet to identify various skin diseases, including psoriasis and lichen planus, with high accuracy rates. These AI systems can support clinicians in accurately diagnosing skin conditions, offering a reliable and efficient alternative to traditional diagnostic methods.
Overall, AI technologies have the potential to revolutionize the field of dermatology by improving diagnostic accuracy and efficiency in identifying complex skin diseases like psoriasis and lichen planus. By leveraging deep learning models and image analysis techniques, researchers are paving the way for more precise and reliable diagnosis of dermatological conditions.
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Source link: https://www.nature.com/articles/s41598-024-60526-4