Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome.
González-Cruz C, Jofre MA, Podlipnik S, Combalia M, Gareau D, Gamboa M, Vallone MG, Faride Barragán-Estudillo Z, Tamez-Peña AL, Montoya J, América Jesús-Silva M, Carrera C, Malvehy J, Puig S.
González-Cruz C, et al.
Actas Dermosifiliogr (Engl Ed). 2020 May;111(4):313-316. doi: 10.1016/j.ad.2019.09.002. Epub 2020 Apr 2.
Actas Dermosifiliogr (Engl Ed). 2020.
PMID: 32248945
Free article.
English, Spanish.
RESULTS: Of the 2,849 images chosen from our database, 968 (34%) met the inclusion criteria for analysis by the ML system. Only 64.7% of nevi and 36.6% of melanoma met the inclusion criteria. ...
RESULTS: Of the 2,849 images chosen from our database, 968 (34%) met the inclusion criteria for analysis by the ML system. Only 64.7% …