scholarly journals Endoscopic Papillary Abnormalities and Stone Recognition (EPSR) during Flexible Ureteroscopy: A Comprehensive Review

2021 ◽  
Vol 10 (13) ◽  
pp. 2888
Author(s):  
Christophe Almeras ◽  
Benjamin Pradere ◽  
Vincent Estrade ◽  
Paul Meria ◽  
on behalf of the Lithiasis Committee of the French Urological Association
Keyword(s):  
Artificial Intelligence ◽  
High Risk ◽  
Crystallization Process ◽  
Flexible Ureteroscopy ◽  
Stone Analysis ◽  
Comprehensive Review ◽  
Stone Formers ◽  
Microscopic Evaluation ◽  
Distortion Effect ◽  
Improved Performance

Introduction: The increasing efficiency of the different lasers and the improved performance of endoscopic devices have led to smaller stone fragments that impact the accuracy of microscopic evaluation (morphological and infrared). Before the stone destruction, the urologist has the opportunity to analyze the stone and the papillary abnormalities endoscopically (endoscopic papillary recognition (EPR) and endoscopic stone recognition (ESR)). Our objective was to evaluate the value for those endoscopic descriptions. Methods: The MEDLINE and EMBASE databases were searched in February 2021 for studies on endoscopic papillary recognition and endoscopic stone recognition. Results: If the ESR provided information concerning the main crystallization process, EPR provided information concerning the origin of the lithogenesis and its severity. Despite many actual limitations, those complementary descriptions could support the preventive care of the stone formers in improving the diagnosis of the lithogenesis mechanism and in identifying high-risk stone formers. Conclusion: Until the development of an Artificial Intelligence recognition, the endourologist has to learn EPSR to minimize the distortion effect of the new lasers on the stone analysis and to improve care efficiency of the stone formers patients.

scholarly journals Applications of Artificial Intelligence in COVID-19 Pandemic: A Comprehensive Review

2021 ◽  
pp. 115695
Author(s):  
Muzammil Khan ◽  
Muhammad Taqi Mehran ◽  
Zeeshan Ul Haq ◽  
Zahid Ullah ◽  
Salman Raza Naqvi
Keyword(s):  
Artificial Intelligence ◽  
Comprehensive Review

scholarly journals IoT Technologies during and Beyond COVID-19: A Comprehensive Review

2021 ◽  
Vol 13 (5) ◽  
pp. 105
Author(s):  
Mohamed Yousif ◽  
Chaminda Hewage ◽  
Liqaa Nawaf
Keyword(s):  
Social Impact ◽  
Contact Tracing ◽  
Privacy And Security ◽  
Comprehensive Review ◽  
Iot Applications ◽  
Depth Analysis ◽  
Challenges And Opportunities ◽  
Potential Applications ◽  
Readiness Level ◽  
Improved Performance

The COVID-19 pandemic provided a much-needed sanity check for IoT-inspired frameworks and solutions. IoT solutions such as remote health monitoring and contact tracing provided support for authorities to successfully manage the spread of the coronavirus. This article provides the first comprehensive review of key IoT solutions that have had an impact on COVID-19 in healthcare, contact tracing, and transportation during the pandemic. Each sector is investigated in depth; and potential applications, social and economic impact, and barriers for mass adaptation are discussed in detail. Furthermore, it elaborates on the challenges and opportunities for IoT framework solutions in the immediate post-COVID-19 era. To this end, privacy and security concerns of IoT applications are analyzed in depth and emerging standards and code of practices for mass adaptation are also discussed. The main contribution of this review paper is the in-depth analysis and categorization of sector-wise IoT technologies, which have the potential to be prominent applications in the new normal. IoT applications in each selected sector are rated for their potential economic and social impact, timeline for mass adaptation, and Technology Readiness Level (TRL). In addition, this article outlines potential research directions for next-generation IoT applications that would facilitate improved performance with preserved privacy and security, as well as wider adaptation by the population at large.

scholarly journals COVID-19 in the Age of Artificial Intelligence: A Comprehensive Review

2021 ◽  
Author(s):  
Jawad Rasheed ◽  
Akhtar Jamil ◽  
Alaa Ali Hameed ◽  
Fadi Al-Turjman ◽  
Ahmad Rasheed
Keyword(s):  
Artificial Intelligence ◽  
Comprehensive Review

Additional Treatments for High-Risk Obstetric Antiphospholipid Syndrome: a Comprehensive Review

2016 ◽  
Vol 53 (1) ◽  
pp. 28-39 ◽  
Author(s):  
Amelia Ruffatti ◽  
Ariela Hoxha ◽  
Maria Favaro ◽  
Marta Tonello ◽  
Anna Colpo ◽  
...  
Keyword(s):  
High Risk ◽  
Antiphospholipid Syndrome ◽  
Comprehensive Review ◽  
Obstetric Antiphospholipid Syndrome

Artificial intelligence research in agriculture: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amit Sood ◽  
Rajendra Kumar Sharma ◽  
Amit Kumar Bhardwaj
Keyword(s):  
Artificial Intelligence ◽  
Peer Review ◽  
Diffusion Of Innovation ◽  
Comprehensive Review ◽  
Content Type ◽  
Design Elements ◽  
Extant Literature ◽  
Use Of Technology ◽  
Challenges And Opportunities ◽  
Market Factors

PurposeThe purpose of this paper is to provide a comprehensive review on the academic journey of artificial intelligence (AI) in agriculture and to highlight the challenges and opportunities in adopting AI-based advancement in agricultural systems and processes.Design/methodology/approachThe authors conducted a bibliometric analysis of the extant literature on AI in agriculture to understand the status of development in this domain. Further, the authors proposed a framework based on two popular theories, namely, diffusion of innovation (DOI) and the unified theory of acceptance and use of technology (UTAUT), to identify the factors influencing the adoption of AI in agriculture.FindingsFour factors were identified, i.e. institutional factors, market factors, technology factors and stakeholder perception, which influence adopting AI in agriculture. Further, the authors indicated challenges under environmental, operational, technological, economical and social categories with opportunities in this area of research and business.Research limitations/implicationsThe proposed conceptual model needs empirical validation across countries or states to understand the effectiveness and relevance.Practical implicationsPractitioners and researchers can use these inputs to develop technology and business solutions with specific design elements to gain benefit of this technology at larger scale for increasing agriculture production.Social implicationsThis paper brings new developed methods and practices in agriculture for betterment of society.Originality/valueThis paper provides a comprehensive review of extant literature and presents a theoretical framework for researchers to further examine the interaction of independent variables responsible for adoption of AI in agriculture.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-10-2020-0448

A Comprehensive Review of Recent Advances in the Estimation of Natural Gas Compressibility Factor

2021 ◽  
Author(s):  
Oluwasegun Cornelious Omobolanle ◽  
Oluwatoyin Olakunle Akinsete
Keyword(s):  
Artificial Intelligence ◽  
Equation Of State ◽  
Compressibility Factor ◽  
Operating Conditions ◽  
Measurement Equation ◽  
Comprehensive Review ◽  
Holistic Understanding ◽  
Deviation Factor ◽  
Gas Compressibility ◽  
Limited Accuracy

Abstract Accurate prediction of gas compressibility factor is essential for the evaluation of gas reserves, custody transfer and design of surface equipment. Gas compressibility factor (Z) also known as gas deviation factor can be evaluated by experimental measurement, equation of state and empirical correlation. However, these methods have been known to be expensive, complex and of limited accuracy owing to the varying operating conditions and the presence of non-hydrocarbon components in the gas stream. Recently, newer correlations with extensive application over wider range of operating conditions and crude mixtures have been developed. Also, artificial intelligence is now being deployed in the evaluation of gas compressibility factor. There is therefore a need for a holistic understanding of gas compressibility factor vis-a-vis the cause-effect relations of deviation. This paper presents a critical review of current understanding and recent efforts in the estimation of gas deviation factor.

Prediction of malignancy upgrade rate in high-risk breast lesions by artificial intelligence model

2021 ◽  
Author(s):  
Ozge Aslan ◽  
Aysenur Oktay ◽  
Basak Katuk ◽  
Riza Cenk Erdur ◽  
oguz dikenelli ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
High Risk ◽  
Breast Lesions ◽  
High Risk Breast

scholarly journals In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare

2021 ◽  
Vol 4 ◽  
Author(s):  
Mustafa Y. Topaloglu ◽  
Elisabeth M. Morrell ◽  
Suraj Rajendran ◽  
Umit Topaloglu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Dice Coefficient ◽  
New Paradigm ◽  
Underrepresented Groups ◽  
Patient Protection ◽  
Shapley Values ◽  
Geographically Distributed ◽  
Computationally Expensive ◽  
Improved Performance

Artificial Intelligence and its subdomain, Machine Learning (ML), have shown the potential to make an unprecedented impact in healthcare. Federated Learning (FL) has been introduced to alleviate some of the limitations of ML, particularly the capability to train on larger datasets for improved performance, which is usually cumbersome for an inter-institutional collaboration due to existing patient protection laws and regulations. Moreover, FL may also play a crucial role in circumventing ML’s exigent bias problem by accessing underrepresented groups’ data spanning geographically distributed locations. In this paper, we have discussed three FL challenges, namely: privacy of the model exchange, ethical perspectives, and legal considerations. Lastly, we have proposed a model that could aide in assessing data contributions of a FL implementation. In light of the expediency and adaptability of using the Sørensen–Dice Coefficient over the more limited (e.g., horizontal FL) and computationally expensive Shapley Values, we sought to demonstrate a new paradigm that we hope, will become invaluable for sharing any profit and responsibilities that may accompany a FL endeavor.

scholarly journals Stone composition of renal stone formers from different global regions

2021 ◽  
Vol 93 (3) ◽  
pp. 307-312
Author(s):  
Adam Hali´nski ◽  
Kamran Hassan Bhatti ◽  
Luca Boeri ◽  
Jonathan Cloutier ◽  
Kaloyan Davidoff ◽  
...  
Keyword(s):  
Uric Acid ◽  
Calcium Phosphate ◽  
Calcium Oxalate ◽  
Urinary Stones ◽  
Ureteral Stones ◽  
Stone Analysis ◽  
Stone Composition ◽  
Stone Formers ◽  
Cystine Stones ◽  
Struvite Stones

Objective: To study urinary stone composition patterns in different populations around the world. Materials and methods: Data were collected by reviewing charts of 1204 adult patients of 10 countries with renal or ureteral stones (> 18 years) in whom a stone analysis was done and available. Any method of stone analysis was accepted, but the methodology had to be registered. Results: In total, we observed 710 (59%) patients with calcium oxalate, 31 (1%) with calcium phosphate, 161 (13%) with mixed calcium oxalate/calcium phosphate, 15 (1%) with carbapatite, 110 (9%) with uric acid, 7 (< 1%) with urate (ammonium or sodium), 100 (9%) with mixed with uric acid/ calcium oxalate, 56 (5%) with struvite and 14 (1%) with cystine stones. Calciumcontaining stones were the most common in all countries ranging from 43 to 91%. Oxalate stones were more common than phosphate or mixed phosphate/oxalate stones in most countries except Egypt and India. The rate of uric acid containing stones ranged from 4 to 34%, being higher in Egypt, India, Pakistan, Iraq, Poland and Bulgaria. Struvite stones occurred in less than 5% in all countries except India (23%) and Pakistan (16%). Cystine stones occurred in 1% of cases. Conclusions: The frequency of different types of urinary stones varies from country to country. Calcium-containing stones are prevalent in all countries. The frequency of uric acid containing stones seems to depend mainly on climatic factors, being higher in countries with desert or tropical climates. Dietary patterns can also lead to an increase in the frequency of uric acid containing stones in association with high obesity rates. Struvite stones are decreasing in most countries due to improved health conditions.

scholarly journals The Use of Artificial-Intelligence-Based Ensembles for Intrusion Detection: A Review

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Gulshan Kumar ◽  
Krishan Kumar
Keyword(s):  
Artificial Intelligence ◽  
Intrusion Detection ◽  
Supervised Learning ◽  
Ensemble Learning ◽  
Classification Performance ◽  
Intrusion Detection Systems ◽  
Future Directions ◽  
Comprehensive Review ◽  
Detection Systems ◽  
Combination Methods

In supervised learning-based classification, ensembles have been successfully employed to different application domains. In the literature, many researchers have proposed different ensembles by considering different combination methods, training datasets, base classifiers, and many other factors. Artificial-intelligence-(AI-) based techniques play prominent role in development of ensemble for intrusion detection (ID) and have many benefits over other techniques. However, there is no comprehensive review of ensembles in general and AI-based ensembles for ID to examine and understand their current research status to solve the ID problem. Here, an updated review of ensembles and their taxonomies has been presented in general. The paper also presents the updated review of various AI-based ensembles for ID (in particular) during last decade. The related studies of AI-based ensembles are compared by set of evaluation metrics driven from (1) architecture & approach followed; (2) different methods utilized in different phases of ensemble learning; (3) other measures used to evaluate classification performance of the ensembles. The paper also provides the future directions of the research in this area. The paper will help the better understanding of different directions in which research of ensembles has been done in general and specifically: field of intrusion detection systems (IDSs).

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