Machine and Deep Learning Models to Predict Acetylcholinesterase Activity

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  • Presentation type: Apresentação de Pôster / Poster Communications
  • Track: Machine Learning/Artificial Intelligence
  • Keywords: Alzheimer Disease; drug design; Machine Learning; Docking;

Authors:

  • 1 Universidade Federal de São João del Rei MG / Universidade Federal do Oeste do Pará
  • 2 Universidade Estadual de Feira de Santana
  • 3 University of the Incarnate Word

Machine and Deep Learning Models to Predict Acetylcholinesterase Activity

Alex Taranto

Universidade Federal de São João del-Rei

Abstract

There is urgency in finding new drugs capable of preventing the progress of the disease, controlling symptoms, and increasing the survival of patients with AD
Thus, supervised models, K-Nearest Neighbors (KNN), Decision Tree, Multilayer Perceptron (MLP), Support Vector Machine (SVM) and Deep Learning, were generated through Jupyter Notebook⁠.
Finally, the MLP model can contribute to the development of new compounds for the treatment of patients with Alzheimer's disease.

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