Papers by Maria Avramouli
Proceedings of the 26th Pan-Hellenic Conference on Informatics
The drug discovery process is a time-consuming and quite expensive process. The predictive models... more The drug discovery process is a time-consuming and quite expensive process. The predictive models of machine learning algorithms have been used efficiently for years in various stages of the drug discovery pipeline. The complexity of these algorithms increases as the size of the molecule increases, adding a single atom to a molecule increases the number of possible combinations. Quantum computers with quantum supremacy can play an important role in complex calculations. Combining the two technologies in practice is a complex endeavor that requires diverse, interdisciplinary teams of scientists working together to be able to integrate the two technologies with the goal of reducing cost and time in drug discovery. CCS CONCEPTS • Computing methodologies → Machine learning; Machine learning algorithms; • Hardware → Emerging technologies; Quantum technologies; • Applied computing → Life and medical sciences; Computational biology.
The drug discovery process is a rigorous and time-consuming endeavor, typically requiring several... more The drug discovery process is a rigorous and time-consuming endeavor, typically requiring several years of extensive research and development. Although classical machine learning (ML) has proven successful in this field, its computational demands in terms of speed and resources are significant. In recent years, researchers have sought to explore the potential benefits of quantum computing (QC) in the context of ML, leading to the emergence of Quantum Machine Learning (QML) as a distinct research field. The objective of the current study is twofold: first, to present a review of the proposed QML algorithms for application in the drug discovery pipeline, and second, to compare QML algorithms with their classical and hybrid counterparts in terms of their efficiency. A query-based search of various databases took place, and five different categories of algorithms were identified in which QML was implemented. The majority of QML applications in drug discovery are primarily focused on the...
Quantum Machine Learning: Current State and Challenges
25th Pan-Hellenic Conference on Informatics
In recent years, machine learning has penetrated a large part of our daily lives, which creates s... more 
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Papers by Maria Avramouli