Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Beyond black‐box AI: Comparing ChatGPT‐4 interpretability and accuracy to CNNs in melanocytic lesions diagnosis
0
Zitationen
11
Autoren
2026
Jahr
Abstract
ChatGPT-4 demonstrated promising potential for accurate melanoma versus nevus classification without annotations, surpassing CNN-based models. However, its limited ability to describe dermoscopic features accurately highlights the need for further research and training.
Ähnliche Arbeiten
Dermatologist-level classification of skin cancer with deep neural networks
2017 · 13.296 Zit.
Tumor Angiogenesis: Therapeutic Implications
1971 · 10.096 Zit.
Improved Survival with Vemurafenib in Melanoma with BRAF V600E Mutation
2011 · 7.656 Zit.
Final Version of 2009 AJCC Melanoma Staging and Classification
2009 · 4.556 Zit.
Technical Details of Intraoperative Lymphatic Mapping for Early Stage Melanoma
1992 · 4.399 Zit.
Autoren
Institutionen
- Tel Aviv University(IL)
- Rabin Medical Center(IL)
- Pontificia Universidad Católica de Chile(CL)
- Ono Academic College(IL)
- Sheba Medical Center(IL)
- Rappaport Family Institute for Research in the Medical Sciences(IL)
- Poriya Medical Center(IL)
- Rutgers, The State University of New Jersey(US)
- Rutgers Sexual and Reproductive Health and Rights(NL)
- Environmental and Occupational Health Sciences Institute(US)
- Rambam Health Care Campus(IL)