Explainable AI in Drug Sensitivity Prediction on Cancer Cell Lines

Explainable Artificial Intelligence (XAI) is a field that develops ways to explain predictions made by AI models. In this paper XAI which is a multifaceted approach is discussed which is capable of defining the value of features while producing predictions. Precision medicine and the forecast of can...

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Bibliographic Details
Published in2022 International Conference on Emerging Trends in Smart Technologies (ICETST) pp. 1 - 5
Main Authors Gillani, Ismat Saira, Shahzad, Muhammad, Mobin, Ansharah, Munawar, Muhammad Rizwan, Awan, Muhammad Usman, Asif, Muhammad
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.09.2022
Subjects
Cell lines
Drug sensitivity
Drug similarity
Explainable AI
Personalized drugs
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Summary:Explainable Artificial Intelligence (XAI) is a field that develops ways to explain predictions made by AI models. In this paper XAI which is a multifaceted approach is discussed which is capable of defining the value of features while producing predictions. Precision medicine and the forecast of cancer's reaction to a specific treatment or drug efficiency is an area of active research. Drug sensitivity forecasting on massive genomics data is a strenuous process in drug discovery. However, drug personalization on the other hand is a tedious and arduous matter. Explainable AI is one of the many properties that instills confidence and dependency in AI systems which is why more attention needs to be paid to XAI. This research is a step toward a more profound understanding of deep learning techniques [1] on gene expressions and drug chemical structures.
DOI:10.1109/ICETST55735.2022.9922931