Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Abderrahmane Ez-Zahout
Mohammed V University
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Spark-powered bioactivity prediction: a comparison of machine learning approaches Nazif Tchagafo; Abderrahmane Ez-Zahout; Ahiod Belaid
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i3.pp2423-2430

Abstract

The arduous and expensive nature of drug discovery has long been a bottleneck in scientific progress. However, recent breakthroughs in computational power, notably machine learning (ML) and artificial intelligence (AI), are profoundly transforming the field. Automated machine learning (AutoML) presents itself as a significant advancement, streamlining model selection, and hyperparameter tuning. This study delves into the potential of AutoML to accelerate drug discovery by comparing it to classical ML techniques. The focus lies on predicting the bioactivity of epidermal growth factor receptor (EGFR), a critical protein implicated in many cancers. By utilizing the scalability of Apache Spark, vast and diverse datasets encompassing biological, chemical, and genomic data tied to EGFR are processed. This comparative analysis aims to evaluate the comparative performance of both approaches, thereby contributing actionable insights to drug discovery research.
Co-Authors Ahiod Belaid Nazif Tchagafo