Machine learning-based coronary artery disease diagnosis: A comprehensive review

R Alizadehsani, M Abdar, M Roshanzamir… - Computers in biology …, 2019 - Elsevier
Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …

[HTML][HTML] Synthetic biology for the directed evolution of protein biocatalysts: navigating sequence space intelligently

A Currin, N Swainston, PJ Day, DB Kell - Chemical Society Reviews, 2015 - pubs.rsc.org
The amino acid sequence of a protein affects both its structure and its function. Thus, the
ability to modify the sequence, and hence the structure and activity, of individual proteins in …

Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of nanoscale heat transport

L Lu, R Pestourie, SG Johnson, G Romano - Physical Review Research, 2022 - APS
Deep neural operators can learn operators mapping between infinite-dimensional function
spaces via deep neural networks and have become an emerging paradigm of scientific …

Local rule-based explanations of black box decision systems

R Guidotti, A Monreale, S Ruggieri, D Pedreschi… - arXiv preprint arXiv …, 2018 - arxiv.org
The recent years have witnessed the rise of accurate but obscure decision systems which
hide the logic of their internal decision processes to the users. The lack of explanations for …

Factual and counterfactual explanations for black box decision making

R Guidotti, A Monreale, F Giannotti… - IEEE Intelligent …, 2019 - ieeexplore.ieee.org
The rise of sophisticated machine learning models has brought accurate but obscure
decision systems, which hide their logic, thus undermining transparency, trust, and the …

Design of an electric vehicle fast-charging station with integration of renewable energy and storage systems

JA Domínguez-Navarro, R Dufo-López… - International Journal of …, 2019 - Elsevier
The development of electric vehicles (EVs) depends on several factors: the EV's acquisition
price, autonomy, the charging process and the charging infrastructure. This paper is focused …

Genetic algorithm based approach for autonomous mobile robot path planning

C Lamini, S Benhlima, A Elbekri - Procedia Computer Science, 2018 - Elsevier
In this study, an improved crossover operator is suggested, for solving path planning
problems using genetic algorithms (GA) in static environment. GA has been widely applied …

A unified framework for deep symbolic regression

M Landajuela, CS Lee, J Yang… - Advances in …, 2022 - proceedings.neurips.cc
The last few years have witnessed a surge in methods for symbolic regression, from
advances in traditional evolutionary approaches to novel deep learning-based systems …

Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling

F Zhang, Y Mei, S Nguyen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …

GA: A package for genetic algorithms in R

L Scrucca - Journal of Statistical Software, 2013 - jstatsoft.org
Genetic algorithms (GAs) are stochastic search algorithms inspired by the basic principles of
biological evolution and natural selection. GAs simulate the evolution of living organisms …