Auto-KPCA: A Two-Step Hybrid Feature Extraction Technique for Quantitative Structure–Activity Relationship Modeling

Alsenan, Shrooq; Al-Turaiki, Isra; Hafez, Alaaeldin M.

doi:10.1109/access.2020.3047375

Cited by 7 publications

(3 citation statements)

References 46 publications

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“…Recently, Alsenan et al designed and developed a recurrent neural network (RNN) for predicting BBB permeability, which improves prediction accuracy further. The same authors proposed a dimensionality reduction technique Auto-KPCA, which applies kernel principal component analysis (KPCA) as a preprocessing step to enhance the accuracy performance of the subsequent deep learning model …”

Section: Machine Learning Helping In Prediction Of Chemotherapeutics ...mentioning

confidence: 99%

“…The same authors proposed a dimensionality reduction technique Auto-KPCA, which applies kernel principal component analysis (KPCA) as a preprocessing step to enhance the accuracy performance of the subsequent deep learning model. 126 Finally, it is noteworthy to mention that although the above methods can accurately predict BBB permeability of a given chemical, they do not directly help generate a de novo chemical structure with desirable BBB permeability properties. The state of the art for AI-based chemical synthesis 127 follows the methodology of inverse molecular design 128 and combines deep reinforcement learning with Monte Carlo tree search (MCTS) to search for a molecular structure with target properties that can be synthesized with known chemical reactions.…”

Section: Machine Learning Helping In Prediction Of Chemotherapeutics ...mentioning

confidence: 99%

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Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers

Singh

Chandrasekar

Janapareddy

et al. 2021

ACS Chem. Neurosci.

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The blood−brain barrier (BBB) is a prime focus for clinicians to maintain the homeostatic function in health and deliver the theranostics in brain cancer and number of neurological diseases. The structural hierarchy and in situ biochemical signaling of BBB neurovascular unit have been primary targets to recapitulate into the in vitro modules. The microengineered perfusion systems and development in 3D cellular and organoid culture have given a major thrust to BBB research for neuropharmacology. In this review, we focus on revisiting the nanoparticles based bimolecular engineering to enable them to maneuver, control, target, and deliver the theranostic payloads across cellular BBB as nanorobots or nanobots. Subsequently we provide a brief outline of specific case studies addressing the payload delivery in brain tumor and neurological disorders (e.g., Alzheimer's disease, Parkinson's disease, multiple sclerosis, etc.). In addition, we also address the opportunities and challenges across the nanorobots' development and design. Finally, we address how computationally powered machine learning (ML) tools and artificial intelligence (AI) can be partnered with robotics to predict and design the next generation nanorobots to interact and deliver across the BBB without causing damage, toxicity, or malfunctions. The content of this review could be references to multidisciplinary science to clinicians, roboticists, chemists, and bioengineers involved in cutting-edge pharmaceutical design and BBB research.

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Section: Machine Learning Helping In Prediction Of Chemotherapeutics ...mentioning

confidence: 99%

Section: Machine Learning Helping In Prediction Of Chemotherapeutics ...mentioning

confidence: 99%

Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers

Singh

Chandrasekar

Janapareddy

et al. 2021

ACS Chem. Neurosci.

View full text Add to dashboard Cite

show abstract

“…Among many current research methods, PCA elimination is a common method to eliminate multicollinearity [5]. In view of the disadvantage that PCA cannot deal with nonlinear problems, some scholars have found that introducing kernel function for processing can obtain higher precision processing effect [6]. Some studies have established an excellent economic management model based on KPCA to solve the problem of information entanglement between data [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Excess Consumption in College Students by KPAG Method During the COVID-19 Pandemic

Zhao¹,

Cao²

2021

J Aqua Live Prod

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With the arrival of COVID-19, some areas are under closed management, bringing about changes in the way people consume. It also leads to the excessive consumption of some people, especially college students. In order to give early warning to unreasonable consumption behavior, this study designed KPAG algorithm to give early warning to consumption risk. Using particle swarm optimization (PSO) kernel principal component analysis (KPCA) parameter optimization, optimal polynomial kernel to delete data information, and ant colony genetic algorithm (association) clustering analysis of data dimensionality reduction, according to the consumption behavior of college students are divided into three categories, for the consumption behavior of college students to build an early warning model. Through the classification and verification experiment of real data, the results show that compared with the traditional PCA data fitting method, the accuracy of the model in this paper can reach 90%, which is more reliable than the traditional algorithm, and the accuracy of the model is improved by nearly 20%, which can be used for effective early warning.

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Entropy Based Defect Detection for Patterned Fabrics

Ramya,

Jayalakshmi

2024

Multi-Strategy Learning Environment

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Auto-KPCA: A Two-Step Hybrid Feature Extraction Technique for Quantitative Structure–Activity Relationship Modeling

Cited by 7 publications

References 46 publications

Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers

Emerging Application of Nanorobotics and Artificial Intelligence To Cross the BBB: Advances in Design, Controlled Maneuvering, and Targeting of the Barriers

Analysis of Excess Consumption in College Students by KPAG Method During the COVID-19 Pandemic

Entropy Based Defect Detection for Patterned Fabrics

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