Is AI Truly Ready to Transform Skin Cancer Diagnosis?
We hear a lot about "Deep Learning" algorithms in the lab, but the ultimate test is their readiness for real-world patient care.
I am thrilled to share a major milestone: upon the explicit recommendation of the esteemed publisher MDPI (Basel, Switzerland), our latest systematic review has been officially published as a preprint while it advances toward final publication acceptance!
This paper maps the critical journey of AI in Dermato-Oncology from the bench to the bedside. In this review, we break down: 🔍 The real-world clinical readiness of current AI diagnostic tools. 🌉 How to successfully bridge the gap between laboratory testing and hospital deployment. 💡 The next frontier for digital health and translational medicine in oncology.
I invite my colleagues and healthcare innovators to read the full manuscript and join the conversation as we shape the future of medical AI.
🔗 Read it here: https://www.preprints.org/manuscript/202610.3057/v1
📌 DOI: 10.20944/preprints202610.3057.v1





