AI and laser technology in medical healthcare

Medical technology is advancing through the integration of artificial intelligence and laser systems to improve diagnostic and therapeutic outcomes. Early developments highlight the use of AI-supported systems, such as FotoFinder, which combine high-resolution digital dermoscopy with artificial intelligence to map skin surfaces and detect minute structural changes in moles for early skin cancer detection. Laser-based technologies are also being utilized for non-invasive gynecological treatments to address tissue elasticity and dryness.

As AI integration in dermatology progresses, professional medical bodies have begun defining its role. The Syndicat National des Dermatologues-Vénéréologues (SNDV) supports the use of AI in cutaneous imaging, provided it functions strictly as a tool to assist in spotting lesions rather than replacing medical expertise. The SNDV maintains that the final responsibility for medical decision-making must remain with a dermatologist. Similarly, the Haute Autorité de Santé (HAS) notes that while AI-based systems can aid in screening and diagnosis, they do not replace the necessity of professional validation.

Recent research has expanded these capabilities. In Germany, researchers at University Hospital Erlangen have utilized AI-supported image recognition combined with Line-Field Confocal Optical Coherence Tomography (LC-OCT) to detect basal cell carcinomas without visible skin changes, providing real-time, three-dimensional imaging. In the US, a scalable training program for primary care physicians has improved skin cancer screening rates among stem cell transplant survivors. Furthermore, scientists at King’s College London have identified immune patterns in B-cells that may predict melanoma patient responses to immunotherapy, potentially enabling more personalized cancer treatments.