Type-2 Neutrosophic Set and Their Applications in Medical Databases Deadlock Resolution

Electronic patient data gives many advantages,but also new difficulties.Deadlocks may delay procedures like acquiring patient information.Distributed deadlock resolution solutions introduce uncertainty due to inaccurate transaction properties.Soft computing-based solutions have been developed to solve this challenge.In a single framework,ambiguous,vague,incomplete,and inconsistent transaction attribute information has received minimal attention.The work presented in this paper employed type-2 neutrosophic logic,an extension of type-1 neutrosophic logic,to handle uncertainty in real-time deadlock-resolving systems.The proposed method is structured to reflect multiple types of knowledge and relations among transactions’features that include validation factor degree,slackness degree,degree of deadline-missed transaction based on the degree of membership of truthiness,degree ofmembership of indeterminacy,and degree ofmembership of falsity.Here,the footprint of uncertainty(FOU)for truth,indeterminacy,and falsity represents the level of uncertainty that exists in the value of a grade of membership.We employed a distributed real-time transaction processing simulator(DRTTPS)to conduct the simulations and conducted experiments using the benchmark Pima Indians diabetes dataset(PIDD).As the results showed,there is an increase in detection rate and a large drop in rollback rate when this new strategy is used.The performance of Type-2 neutrosophicbased resolution is better than the Type-1 neutrosophic-based approach on the execution ratio scale.The improvement rate has reached 10%to 20%,depending on the number of arrived transactions.

Study on myocardial infarction based on nationwide inpatient sample database:a bibliometric analysis from 2000 to 2022

Background:Studies on myocardial infarction(MI)based on large medical databases have become popular in recent years.The influence of the National Inpatient Sample(NIS),the largest collection of administrative healthcare data across the United States,on the field of MI has not been well investigated.This study aimed to quantify the contribution of NIS to MI research using bibliometric methods.Methods:We searched the Web of Science Core Collection database to identify publications on MI using NIS from 2000 to 2022.Bibliometric indicators,such as the number of publications,citations,and Hirsch index(H-index),were summarized by years,authors,organizations,and journals.VOSviewer and CiteSpace software were used to analyze the keywords and trends of the hot spots.Results:A total of 342 articles on MI based on NIS were included.A significant growth in outputs related to MI using the NIS from 2000 to 2020 was observed.The publications were mainly from the United States.The Mayo Clinic was the most prolific institution and had the most citations and the highest H-index.The American Journal of Cardiology ranked first among journals with the highest number of publications,citations,and H-index.Mortality and healthcare management are the main focuses of this field.Personalized risks and care are receiving increased attention.Conclusion:This study suggests that NIS significantly contributes to high-quality output in MI research.More efforts are needed to improve the impact of knowledge gained from the NIS on MI.