Real-time gated-SPECT myocardial perfusion imaging with CZT detectors: A promising tool for monitoring left ventricular function

Assante, Roberta; Cuocolo, Alberto

doi:10.1007/s12350-017-0924-x

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…• Employee information: pushing information to employees about the company status and messaging • Conference bridges: using Toll-free conference bridges for employee, vendor, senior management, board of directors, and other key stakeholder phone calls • Stakeholder groups: using predefined groups that had been created for key stakeholders to push information via phone, text, or email Cloud computing "is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, services) that can be rapidly provisioned and released with minimal management effort or service provider interaction" (NIST definition). Cloud computing enables companies to use resources as a utility rather than having to build and maintain computing infrastructures in-house [13][14][15].…”

Section: Cloud Computing Offers Many Opportunities For Communication mentioning

confidence: 99%

Aligning a Cybersecurity Strategy with Communication Management in Organizations

Hamburg¹,

Grosch²

2018

Digital Communication Management

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Cyberattacks are a constant threat to organizations. Despite the improvement of cybersecurity (CS) techniques, criminals have developed sophisticated ways to disrupt systems and steal data particularly in organizations. The need to prepare them for cyberattacks is very important. CS professionals (CSPs), have a responsibility that should include protection against moral damage and protect moral rights to ensure the correctness, reliability, availability, and security of all aspects of information and information systems. In case of an emergency, effective communication is crucial. If IT systems fail, a quick communication with employees is necessary as well as to coordinate an effective response. This chapter starts with some explication about CS and later shows the problems organizations face when cyberattacks appear: The chapter describes methods for an efficient communication and its integration into CS strategy of the company. The scope of the chapter is to discuss with academics who work in the field of communication and CS and with students to find new scientific methods in this relative new domain based on some practical experience; and to help organizations and employees particularly CSPs to develop communication plans and to integrate them in their CS plans. The authors have experience will contribute that results will be integrated in the curriculum of cybersecurity from VET and HE students.

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Section: Cloud Computing Offers Many Opportunities For Communication mentioning

confidence: 99%

Aligning a Cybersecurity Strategy with Communication Management in Organizations

Hamburg¹,

Grosch²

2018

Digital Communication Management

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“…The experience of the specialist who examines the medical diagnosis plays an important role. At this point, machine learning, which is a sub-branch of artificial intelligence, can learn similarities in the images, or the determining features in the diagnosis on patient information 2 .…”

Section: Introductionmentioning

confidence: 99%

Classification of Individuals at Risk of Heart Disease Using Machine Learning

Akalin¹,

Veranyurt²,

Veranyurt³

2020

Cumhuriyet Medical Journal

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The aim of this study is to determine whether people have heart disease by using different machine learning algorithms with the data provided by the University of Cleveland. Method: 303 patient data provided by the University of Cleveland were classified using Gaussian Bayes, K-Nearest Neighbor and Random Forest Algorithms with and without feature scaling. With each algorithm, the data is divided into random training and test sets. This process was repeated 50 times for each algorithm. The test results were subjected to the T-test to check statistical independence. Results: In this study, 80.52% accuracy with K-Nearest Neighbor algorithm, 80.52% with Gaussian Bayes and 82.50% with Random Forest were observed with data scaling. The results of the three algorithms produced similar values and did not show statistical independence (p> 0.05). Without data scaling, 65.28% accuracy with the K-Nearest Neighbor algorithm, 80.52% with Gaussian Bayes and 82.19% with Random Forest were observed. The test results obtained with three algorithms showed statistical independence. Conclusions: Although there were data from 303 patients in the study, over 80% accurate prediction was obtained. The presence of endpoints that distort the distribution in the data used results in differences in the methods used. It has been confirmed that much closer estimates can be obtained on a scaled patient data. This study is an example of the use of artificial intelligence in detecting cardiac diseases that pose a risk all over the world. With a more detailed patient data, much higher accuracy rates can be obtained and included in health management processes in the pre-diagnosis of heart disease in the future.

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Machine learning for nuclear cardiology: The way forward

Shrestha

Sengupta

2019

Journal of Nuclear Cardiology

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Real-time gated-SPECT myocardial perfusion imaging with CZT detectors: A promising tool for monitoring left ventricular function

Cited by 5 publications

References 24 publications

Aligning a Cybersecurity Strategy with Communication Management in Organizations

Aligning a Cybersecurity Strategy with Communication Management in Organizations

Classification of Individuals at Risk of Heart Disease Using Machine Learning

Machine learning for nuclear cardiology: The way forward

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