Enhanced singular value decomposition for prediction of drugs and diseases with Hepatocellular carcinoma based on Multi-Source Bat Algorithm based random walk

Ibrahim, Sara; Thangamani, M.

doi:10.1016/j.measurement.2019.02.056

Cited by 9 publications

(5 citation statements)

References 30 publications

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“…The second job, a multiple-source bat algorithm oriented Random Walk (PDD-MBARW) [ 19] is used as an inclusive structure. A new improved SVD algorithm for a decrease of dimensionality will provided which will increase the accuracy of the forecast.…”

Section: Discussionmentioning

confidence: 99%

Innovative Drug and Disease Prediction with Dimensionality Reduction and Intelligence Based Random Walk Methods

Ibrahim¹

2019

IJATCSE

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Medicine is a chemical, which processes, cures, avoids or diagnoses illnesses. There are three phases in drug design: phase of discovery, preclinical phase, and phase of clinical development [1]. Associations of drug-disease reveal and have received excellent attention to the close relationship between drugs and illnesses. Computing techniques may monitor prospective sedate-illness Linkages and additional or expensive moist experiments are performed.A variety of computational methods for predicting sedate disease associations have been suggested in the latest years. Many medicine-sickness confederacies have been identified and saved in databases. Many organizations are however unaccounted for and need to be found. However, there have been few algorithms dedicated to medicines for a distinct illness. This is also one reason why many findings are not sufficiently predictive. The most prevalent form of hepatocellular carcinoma (HCC) in drug discovery. The second most common hepatobiliary disease following HCC is the Cholangiocarcinoma (CCA), representing 10 to 15 half of all liver carcinomas. .

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Section: Discussionmentioning

confidence: 99%

Innovative Drug and Disease Prediction with Dimensionality Reduction and Intelligence Based Random Walk Methods

Ibrahim¹

2019

IJATCSE

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“…The BA in the domain of feature selection has shown outstanding results and proved its scalability in addressing a such complex and high-dimensional problems such as gene selection [ 7 , 11 , 22 , 55 , 66 ], disease detection [ 64 , 65 , 135 ], cancer classification [ 143 ], fault diagnosis [ 105 ], and online feature selection [ 247 ]. The BA applications in this domain are presented in Fig.…”

Section: Applications Of Bat-inspired Algorithmmentioning

confidence: 99%

Recent advances of bat-inspired algorithm, its versions and applications

Alyasseri

Alomari

Al-Betar

et al. 2022

Neural Comput & Applic

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Bat-inspired algorithm (BA) is a robust swarm intelligence algorithm that finds success in many problem domains. The ecosystem of bat animals inspires the main idea of BA. This review paper scanned and analysed the state-of-the-art researches investigated using BA from 2017 to 2021. BA has very impressive characteristics such as its easy-to-use, simple in concepts, flexible and adaptable, consistent, and sound and complete. It has strong operators that incorporate the natural selection principle through survival-of-the-fittest rule within the intensification step attracted by local-best solution. Initially, the growth of the recent solid works published in Scopus indexed articles is summarized in terms of the number of BA-based Journal articles published per year, citations, top authors, work with BA, top institutions, and top countries. After that, the different versions of BA are highlighted to be in line with the complex nature of optimization problems such as binary, modified, hybridized, and multiobjective BA. The successful applications of BA are reviewed and summarized, such as electrical and power system, wireless and network system, environment and materials engineering, classification and clustering, structural and mechanical engineering, feature selection, image and signal processing, robotics, medical and healthcare, scheduling domain, and many others. The critical analysis of the limitations and shortcomings of BA is also mentioned. The open-source codes of BA code are given to build a wealthy BA review. Finally, the BA review is concluded, and the possible future directions for upcoming developments are suggested such as utilizing BA to serve in dynamic, robust, multiobjective, large-scaled optimization as well as improve BA performance by utilizing structure population, tuning parameters, memetic strategy, and selection mechanisms. The reader of this review will determine the best domains and applications used by BA and can justify their BA-related contributions.

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“…In fact, in an article entitled "7 Assessment Challenges of Moving Your Course Online (and a Dozen+ Solutions)" It was stated that assessments or quizzes that were effective in the face-to-face environment may require alterations or replacement to be effective in the current online setting due to problems of academic dishonesty that arises in online learning environments. Test question shuffling was introduced as one of the solutions to deter examinees from cheating as two students that are seated adjacent to each other have a reduced likelihood of being able to take the same test together due to different question orders [4,5,6].…”

Section: Fig 2 Future Work Source: [1]mentioning

confidence: 99%

An enhancement of planned random algorithm applied on an online questionnaire

Fontila

Garcia

Lagarta

et al. 2022

sajet

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Like many other innovations, randomization has been a key factor in various fields such as games, science, art, statistics, and other areas. But although treated as common knowledge, randomization is often misunderstood by users when they start to perceive relationships or connections between randomly distributed data, this tendency is known as apophenia. It is observed mostly when a randomized dataset shows the same elements in a row or in multiple repetitions, an occurrence that is plausible given the nature of randomization. Nevertheless, this may appear as biased or non-random to humans, thinking that since an element had appeared once or a couple of times then it should not appear next to or within a set amount of time, another user misunderstanding known as gambler’s fallacy.The Planned Random algorithm (PR algorithm) was created as a solution to this problem, as it introduces a non- random process to lessen the repetitions of data in the returned dataset and making the result less random to appear more random.This study aims to enhance the Planned Random algorithm by increasing its apparent randomness by further minimizing the repetition of data in a resulting dataset. 5 final test simulations were done for both the existing PR algorithm and enhanced PR algorithm wherein the enhanced algorithm showed a promising 22.22% decrease in both total and average repetitions compared to the existing algorithm.In conclusion, the enhanced algorithm had seen a significant increase in apparent randomness when compared to the existing PR algorithm.

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Enhanced singular value decomposition for prediction of drugs and diseases with Hepatocellular carcinoma based on Multi-Source Bat Algorithm based random walk

Cited by 9 publications

References 30 publications

Innovative Drug and Disease Prediction with Dimensionality Reduction and Intelligence Based Random Walk Methods

Innovative Drug and Disease Prediction with Dimensionality Reduction and Intelligence Based Random Walk Methods

Recent advances of bat-inspired algorithm, its versions and applications

An enhancement of planned random algorithm applied on an online questionnaire

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