0000000001115586

AUTHOR

Lilia Geogieva

showing 1 related works from this author

Robustness, Stability, and Fidelity of Explanations for a Deep Skin Cancer Classification Model

2022

Skin cancer is one of the most prevalent of all cancers. Because of its being widespread and externally observable, there is a potential that machine learning models integrated into artificial intelligence systems will allow self-screening and automatic analysis in the future. Especially, the recent success of various deep machine learning models shows promise that, in the future, patients could self-analyse their external signs of skin cancer by uploading pictures of these signs to an artificial intelligence system, which runs such a deep learning model and returns the classification results. However, both patients and dermatologists, who might use such a system to aid their work, need to …

Fluid Flow and Transfer Processesexplainable artificial intelligenceskin cancerProcess Chemistry and TechnologyGeneral Engineeringconvolutional neural networkdeep learningsyväoppimineninterpretable machine learningpäätöksentukijärjestelmätneuroverkotdiagnostiikkaComputer Science Applicationsihosyöpälocal model-agnostic explanationskoneoppiminenGeneral Materials ScienceInstrumentationexplainable artificial intelligence; interpretable machine learning; skin cancer; convolutional neural network; deep learning; integrated gradients; local model-agnostic explanationsintegrated gradientsApplied Sciences
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