39 results match your criteria Artificial Intelligence Review[Journal]


Global bibliometric mapping of the frontier of knowledge in the field of artificial intelligence for the period 1990-2019.

Artif Intell Rev 2022 Jun 8:1-31. Epub 2022 Jun 8.

George Washington University, GWU School of Business, Washington, DC 20052 USA.

Artificial Intelligence (AI) has emerged as a field of knowledge that is displacing and disrupting technologies, leading to changes in human life. Therefore, the purpose of this study is to scientifically map this topic and its ramifications, in order to analyze its growth. The study was developed under the bibliometric approach and considered the period 1990-2019. Read More

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A state-of-the-art survey of object detection techniques in microorganism image analysis: from classical methods to deep learning approaches.

Artif Intell Rev 2022 Jun 7:1-72. Epub 2022 Jun 7.

Biomedical Information College, University of Luebeck, Luebeck, Germany.

Microorganisms play a vital role in human life. Therefore, microorganism detection is of great significance to human beings. However, the traditional manual microscopic detection methods have the disadvantages of long detection cycle, low detection accuracy in large orders, and great difficulty in detecting uncommon microorganisms. Read More

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A survey on the use of association rules mining techniques in textual social media.

Artif Intell Rev 2022 May 12:1-26. Epub 2022 May 12.

Department of Computer Science and Artificial Intelligence, University of Granada, Granada, Spain.

The incursion of social media in our lives has been much accentuated in the last decade. This has led to a multiplication of data mining tools aimed at obtaining knowledge from these data sources. One of the greatest challenges in this area is to be able to obtain this knowledge without the need for training processes, which requires structured information and pre-labelled datasets. Read More

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Applications of artificial neural networks in microorganism image analysis: a comprehensive review from conventional multilayer perceptron to popular convolutional neural network and potential visual transformer.

Artif Intell Rev 2022 May 4:1-58. Epub 2022 May 4.

Institute for Medical Informatics, University of Luebeck, Luebeck, Germany.

Microorganisms are widely distributed in the human daily living environment. They play an essential role in environmental pollution control, disease prevention and treatment, and food and drug production. The analysis of microorganisms is essential for making full use of different microorganisms. Read More

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Developments in the detection of diabetic retinopathy: a state-of-the-art review of computer-aided diagnosis and machine learning methods.

Artif Intell Rev 2022 Apr 26:1-50. Epub 2022 Apr 26.

VNU Information Technology Institute, Vietnam National University, Hanoi, Vietnam.

The exponential increase in the number of diabetics around the world has led to an equally large increase in the number of diabetic retinopathy (DR) cases which is one of the major complications caused by diabetes. Left unattended, DR worsens the vision and would lead to partial or complete blindness. As the number of diabetics continue to increase exponentially in the coming years, the number of qualified ophthalmologists need to increase in tandem in order to meet the demand for screening of the growing number of diabetic patients. Read More

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Deep Neuro-Fuzzy System application trends, challenges, and future perspectives: a systematic survey.

Artif Intell Rev 2022 Apr 13:1-49. Epub 2022 Apr 13.

Department of Computer Sciences, College of Computing, Al Qunfudhah, Umm Al-Qura University, Makkah, Saudi Arabia.

Deep neural networks (DNN) have remarkably progressed in applications involving large and complex datasets but have been criticized as a black-box. This downside has recently become a motivation for the research community to pursue the ideas of hybrid approaches, resulting in novel hybrid systems classified as deep neuro-fuzzy systems (DNFS). Studies regarding the implementation of DNFS have rapidly increased in the domains of computing, healthcare, transportation, and finance with high interpretability and reasonable accuracy. Read More

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An empirical evaluation of kernels for time series.

Artif Intell Rev 2022 27;55(3):1803-1820. Epub 2021 Jul 27.

School of Computer Science, University College Dublin, Dublin, Ireland.

There exist a variety of distance measures which operate on time series kernels. The objective of this article is to compare those distance measures in a support vector machine setting. A support vector machine is a state-of-the-art classifier for static (non-time series) datasets and usually outperforms k-Nearest Neighbour, however it is often noted that that 1-NN DTW is a robust baseline for time-series classification. Read More

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A new fusion of whale optimizer algorithm with Kapur's entropy for multi-threshold image segmentation: analysis and validations.

Artif Intell Rev 2022 Mar 21:1-71. Epub 2022 Mar 21.

Department of Mathematics Faculty of Science, Mansoura University, Mansoura, 35516 Egypt.

The separation of an object from other objects or the background by selecting the optimal threshold values remains a challenge in the field of image segmentation. Threshold segmentation is one of the most popular image segmentation techniques. The traditional methods for finding the optimum threshold are computationally expensive, tedious, and may be inaccurate. Read More

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Modality specific U-Net variants for biomedical image segmentation: a survey.

Artif Intell Rev 2022 Mar 1:1-45. Epub 2022 Mar 1.

IIIT Allahabad, Prayagraj, 211015 India.

With the advent of advancements in deep learning approaches, such as deep convolution neural network, residual neural network, adversarial network; U-Net architectures are most widely utilized in biomedical image segmentation to address the automation in identification and detection of the target regions or sub-regions. In recent studies, U-Net based approaches have illustrated state-of-the-art performance in different applications for the development of computer-aided diagnosis systems for early diagnosis and treatment of diseases such as brain tumor, lung cancer, alzheimer, breast cancer, etc., using various modalities. Read More

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AI-aided general clinical diagnoses verified by third-parties with dynamic uncertain causality graph extended to also include classification.

Artif Intell Rev 2022 Jan 29:1-37. Epub 2022 Jan 29.

Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing, China.

Artificial intelligence (AI)-aided general clinical diagnosis is helpful to primary clinicians. Machine learning approaches have problems of generalization, interpretability, etc. Dynamic Uncertain Causality Graph (DUCG) based on uncertain casual knowledge provided by clinical experts does not have these problems. Read More

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January 2022

A complete framework for accurate recognition and prognosis of COVID-19 patients based on deep transfer learning and feature classification approach.

Artif Intell Rev 2022 Jan 29:1-46. Epub 2022 Jan 29.

Computers and Control Systems Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt.

The sudden appearance of COVID-19 has put the world in a serious situation. Due to the rapid spread of the virus and the increase in the number of infected patients and deaths, COVID-19 was declared a pandemic. This pandemic has its destructive effect not only on humans but also on the economy. Read More

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January 2022

Multi-criteria decision-making for coronavirus disease 2019 applications: a theoretical analysis review.

Artif Intell Rev 2022 Jan 27:1-84. Epub 2022 Jan 27.

Department of Biology, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, 35900 Perak, Tanjong Malim Malaysia.

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Read More

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January 2022

Human activity recognition in artificial intelligence framework: a narrative review.

Artif Intell Rev 2022 Jan 18:1-54. Epub 2022 Jan 18.

Stroke Diagnostic and Monitoring Division, AtheroPointTM, Roseville, CA 95661 USA.

Human activity recognition (HAR) has multifaceted applications due to its worldly usage of acquisition devices such as smartphones, video cameras, and its ability to capture human activity data. While electronic devices and their applications are steadily growing, the advances in Artificial intelligence (AI) have revolutionized the ability to extract deep hidden information for accurate detection and its interpretation. This yields a better understanding of rapidly growing acquisition devices, AI, and applications, the three pillars of HAR under one roof. Read More

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January 2022

Advantage matrix: two novel multi-attribute decision-making methods and their applications.

Authors:
Bin Yu Zeshui Xu

Artif Intell Rev 2022 Jan 17:1-22. Epub 2022 Jan 17.

Business School, Sichuan University, Chengdu, 610064 Sichuan People's Republic of China.

By comparing attributes of objects in an information system, the advantage matrix on the object set is established in this paper. The contributions can be identified as follows: (1) The advantage degree is proposed by the accumulation of the advantage matrix. (2) Based on the advantage matrix, the advantage (disadvantage) neighborhood approximation operator and the advantage (disadvantage) correlation approximation operator are defined and studied. Read More

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January 2022

Estimation of most effected cycles and busiest network route based on complexity function of graph in fuzzy environment.

Artif Intell Rev 2022 Jan 10:1-18. Epub 2022 Jan 10.

Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore, 721102 West Bengal India.

Connectivity and strength has a major role in the field of network connecting with real world life. Complexity function is one of these parameter which has manifold number of applications in molecular chemistry and the theory of network. Firstly, this paper introduces the thought of complexity function of fuzzy graph with its properties. Read More

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January 2022

Group decision-making with Fermatean fuzzy soft expert knowledge.

Artif Intell Rev 2022 Jan 9:1-41. Epub 2022 Jan 9.

Department of Mathematics, Division of Science and Technology, University of Education, Lahore, Pakistan.

With the rapid growth of population, the global impact of solar technology is increasing by the day due to its advantages over other power production technologies. Demand for solar panel systems is soaring, thus provoking the arrival of many new manufacturers. Sale dealers or suppliers face an uncertain problem to choose the most adequate technological solution. Read More

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January 2022

Using artificial intelligence technology to fight COVID-19: a review.

Artif Intell Rev 2022 Jan 3:1-37. Epub 2022 Jan 3.

Petroleum Engineering School, Southwest Petroleum University, Chengdu, 610500 China.

In late December 2019, a new type of coronavirus was discovered, which was later named severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Since its discovery, the virus has spread globally, with 2,975,875 deaths as of 15 April 2021, and has had a huge impact on our health systems and economy. How to suppress the continued spread of new coronary pneumonia is the main task of many scientists and researchers. Read More

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January 2022

A comprehensive review of image analysis methods for microorganism counting: from classical image processing to deep learning approaches.

Artif Intell Rev 2022 29;55(4):2875-2944. Epub 2021 Sep 29.

Microscopic Image and Medical Image Analysis Group, College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169 China.

Microorganisms such as bacteria and fungi play essential roles in many application fields, like biotechnique, medical technique and industrial domain. Microorganism counting techniques are crucial in microorganism analysis, helping biologists and related researchers quantitatively analyze the microorganisms and calculate their characteristics, such as biomass concentration and biological activity. However, traditional microorganism manual counting methods, such as plate counting method, hemocytometry and turbidimetry, are time-consuming, subjective and need complex operations, which are difficult to be applied in large-scale applications. Read More

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September 2021

An automated essay scoring systems: a systematic literature review.

Artif Intell Rev 2022 23;55(3):2495-2527. Epub 2021 Sep 23.

Department of Information Technology, JNTUH College of Engineering, Nachupally, Kondagattu, Jagtial, TS India.

Assessment in the Education system plays a significant role in judging student performance. The present evaluation system is through human assessment. As the number of teachers' student ratio is gradually increasing, the manual evaluation process becomes complicated. Read More

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September 2021

Recent advancement in VM task allocation system for cloud computing: review from 2015 to2021.

Artif Intell Rev 2022 23;55(3):2529-2573. Epub 2021 Sep 23.

Department of Computer Science, Faculty of Science, Ibn Tofail University, Kénitra, Morocco.

Cloud computing is new technology that has considerably changed human life at different aspect over the last decade. Especially after the COVID-19 pandemic, almost all life activity shifted into cloud base. Cloud computing is a utility where different hardware and software resources are accessed on pay per user ground base. Read More

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September 2021

A comprehensive survey of recent trends in deep learning for digital images augmentation.

Artif Intell Rev 2022 4;55(3):2351-2377. Epub 2021 Sep 4.

Center for Artificial Intelligence Research and Optimization, Torrens University Australia, Fortitude Valley, Brisbane, QLD 4006 Australia.

Deep learning proved its efficiency in many fields of computer science such as computer vision, image classifications, object detection, image segmentation, and more. Deep learning models primarily depend on the availability of huge datasets. Without the existence of many images in datasets, different deep learning models will not be able to learn and produce accurate models. Read More

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September 2021

Differential evolution and particle swarm optimization against COVID-19.

Artif Intell Rev 2022 19;55(3):2149-2219. Epub 2021 Aug 19.

Faculty of Polish Studies, University of Warsaw, Krakowskie Przedmiescie 26/28, 00-927 Warsaw, Poland.

COVID-19 disease, which highly affected global life in 2020, led to a rapid scientific response. Versatile optimization methods found their application in scientific studies related to COVID-19 pandemic. Differential Evolution (DE) and Particle Swarm Optimization (PSO) are two metaheuristics that for over two decades have been widely researched and used in various fields of science. Read More

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Machine Learning in Drug Discovery: A Review.

Artif Intell Rev 2022 11;55(3):1947-1999. Epub 2021 Aug 11.

Department of Pharmaceutical Chemistry, Maharishi Arvind College of Pharmacy, Jaipur, 302023 Rajasthan India.

This review provides the feasible literature on drug discovery through ML tools and techniques that are enforced in every phase of drug development to accelerate the research process and deduce the risk and expenditure in clinical trials. Machine learning techniques improve the decision-making in pharmaceutical data across various applications like QSAR analysis, hit discoveries, de novo drug architectures to retrieve accurate outcomes. Target validation, prognostic biomarkers, digital pathology are considered under problem statements in this review. Read More

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An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem.

Artif Intell Rev 2022 6;55(3):1887-1913. Epub 2021 Aug 6.

The Third Department of Neurology, the Second Affiliated Hospital of Xi'an Medical University, Xi'an, Shaanxi China.

Exploring efficiency approaches to solve the problems of decision making under uncertainty is a mainstream direction. This article explores the rough approximation of the uncertainty information with Pythagorean fuzzy information on multi-granularity space over two universes combined with grey relational analysis. Based on grey relational analysis, we present a new approach to calculate the relative degree or the attribute weight with Pythagorean fuzzy set and give a new descriptions for membership degree and non-membership. Read More

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News recommender system: a review of recent progress, challenges, and opportunities.

Artif Intell Rev 2022 21;55(1):749-800. Epub 2021 Jul 21.

Ryerson University, Toronto, Canada.

Nowadays, more and more news readers read news online where they have access to millions of news articles from multiple sources. In order to help users find the right and relevant content, news recommender systems (NRS) are developed to relieve the information overload problem and suggest news items that might be of interest for the news readers. In this paper, we highlight the major challenges faced by the NRS and identify the possible solutions from the state-of-the-art. Read More

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Prediction of global spread of COVID-19 pandemic: a review and research challenges.

Artif Intell Rev 2022 16;55(3):1607-1628. Epub 2021 Jul 16.

Department of Software Engineering, Faculty of Engineering, Koya University, Koysinjaq, Kurdistan Region-F.R. Iraq.

Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyze and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modeling tools to the latest artificial intelligence technology, the scientific community has used public and privately available data to help with predictions. Read More

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The role of AI technology in prediction, diagnosis and treatment of colorectal cancer.

Artif Intell Rev 2022 4;55(1):323-343. Epub 2021 Jul 4.

Tongji Medical College of Huazhong University of Science and Technology, Wuhan, 430030 People's Republic of China.

Artificial intelligence (AI) is a fascinating new technology that incorporates machine learning and neural networks to improve existing technology or create new ones. Potential applications of AI are introduced to aid in the fight against colorectal cancer (CRC). This includes how AI will affect the epidemiology of colorectal cancer and the new methods of mass information gathering like GeoAI, digital epidemiology and real-time information collection. Read More

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Over a decade of social opinion mining: a systematic review.

Artif Intell Rev 2021 25;54(7):4873-4965. Epub 2021 Jun 25.

ADAPT Centre, Dublin City University, Dublin, Ireland.

Social media popularity and importance is on the increase due to people using it for various types of social interaction across multiple channels. This systematic review focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from user-generated content represented across multiple social media platforms and in various media formats, like text, image, video and audio. Through Social Opinion Mining, natural language can be understood in terms of the different opinion dimensions, as expressed by humans. Read More

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An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions.

Artif Intell Rev 2022 3;55(1):181-206. Epub 2021 Jun 3.

Department of Mathematics, National Institute of Technology, Warangal, 506004 India.

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Read More

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A comprehensive survey of sine cosine algorithm: variants and applications.

Artif Intell Rev 2021 2;54(7):5469-5540. Epub 2021 Jun 2.

LISV Laboratory, University of Versailles St-Quentin-en-Yvelines, 10-12 Avenue of Europe, 78140 Velizy, France.

Sine Cosine Algorithm (SCA) is a recent meta-heuristic algorithm inspired by the proprieties of trigonometric sine and cosine functions. Since its introduction by Mirjalili in 2016, SCA has attracted great attention from researchers and has been widely used to solve different optimization problems in several fields. This attention is due to its reasonable execution time, good convergence acceleration rate, and high efficiency compared to several well-regarded optimization algorithms available in the literature. Read More

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