Abstract Number: 306

Artificial intelligence, predicting outcomes in photodynamic therapy

A. Yazdabadi,, F. Moloney,, R. Hambly,, N. Mansoor,, C. Quinlan,, Z. Shah,, P. Lenane,, N. Ralph,, E. Schudell,, H. Asadi,

Meeting: 2017 Dermcoll

Session Information

Date: -

Session Title: Posters

Session Time: -

Photodynamic therapy (PDT) is a well-established method to treat various cutaneous disorders. Machine learning or artificial intelligence was pioneered by Arthur Samuel in 1959. He defined it as “field of study that gives computers the ability to learn without being explicitly programmed.” Thus in machine learning, algorithms are designed with the capability of not only making predictions but also learning from new data.i This technique is widely used in other areas and is now slowly emerging in medicine and lends itself well to predicting outcomes using specific modalities treatment modalities such as PDT. We present a novel artificial intelligence model for the prediction of pain and outcomes for actinic keratosis, superficial basal cell carcinomas and Bowen’s Disease treated with PDT.li Bryan R. Look Ahead Machine Learning in Radiology. 2016; Available from: http://www.rsna.org/News.aspx?id= 19018.