scholarly journals Deep Learning on Histopathology Images for Breast Cancer Classification: A Bibliometric Analysis

Healthcare ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 10
Author(s):  
Siti Khairi ◽  
Mohd Bakar ◽  
Sakhinah Bakar ◽  
Nurwahyuna Rosli ◽  
◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
Bibliometric Analysis ◽  
Human Error ◽  
Research Collaboration ◽  
The United States ◽  
Research Area ◽  
Related Field ◽  
Cancer Breast ◽  
Histopathology Image Analysis

Medical imaging is gaining significant attention in healthcare, including breast cancer. Breast cancer is the most common cancer-related death among women worldwide. Currently, histopathology image analysis is the clinical gold standard in cancer diagnosis. However, the manual process of microscopic examination involves laborious work and can be misleading due to human error. Therefore, this study explored the research status and development trends of deep learning on breast cancer image classification using bibliometric analysis. Relevant works of literature were obtained from the Scopus database between 2014 and 2021. The VOSviewer and Bibliometrix tools were used for analysis through various visualization forms. This study is concerned with the annual publication trends, co-authorship networks among countries, authors, and scientific journals. The co-occurrence network of the authors’ keywords was analyzed for potential future directions of the field. Authors started to contribute to publications in 2016, and the research domain has maintained its growth rate since. The United States and China have strong research collaboration strengths. Only a few studies use bibliometric analysis in this research area. This study provides a recent review on this fast-growing field to highlight status and trends using scientific visualization. It is hoped that the findings will assist researchers in identifying and exploring the potential emerging areas in the related field.

scholarly journals A Bibliometric Analysis of the Global Trend of Using Alginate, Gelatine, and Hydroxyapatite for Bone Tissue Regeneration Applications

Polymers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 647
Author(s):  
Mohamed Saiful Firdaus Hussin ◽  
Aludin Mohd Serah ◽  
Khairul Azri Azlan ◽  
Hasan Zuhudi Abdullah ◽  
Maizlinda Izwana Idris ◽  
...  
Keyword(s):  
Tissue Engineering ◽  
Bone Tissue Engineering ◽  
Bone Tissue ◽  
Bibliometric Analysis ◽  
Research Work ◽  
The United States ◽  
Research Area ◽  
Bone Tissue Regeneration ◽  
Future Research ◽  
Starting Point

Collecting information from previous investigations and expressing it in a scientometrics study can be a priceless guide to getting a complete overview of a specific research area. The aim of this study is to explore the interrelated connection between alginate, gelatine, and hydroxyapatite within the scope of bone tissue and scaffold. A review of traditional literature with data mining procedures using bibliometric analyses was considered to identify the evolution of the selected research area between 2009 and 2019. Bibliometric methods and knowledge visualization technologies were implemented to investigate diverse publications based on the following indicators: year of publication, document type, language, country, institution, author, journal, keyword, and number of citations. An analysis using a bibliometric study found that 7446 papers were located with the keywords “bone tissue” and “scaffold”, and 1767 (alginate), 185 (gelatine), 5658 (hydroxyapatite) papers with those specific sub keywords. The number of publications that relate to “tissue engineering” and bone more than doubled between 2009 (1352) and 2019 (2839). China, the United States and India are the most productive countries, while Sichuan University and the Chinese Academy of Science from China are the most important institutions related to bone tissue scaffold. Materials Science and Engineering C is the most productive journal, followed by the Journal of Biomedical Materials Research Part A. This paper is a starting point, providing the first bibliometric analysis study of bone tissue and scaffold considering alginate, gelatine and hydroxyapatite. A bibliometric analysis would greatly assist in giving a scientific insight to support desired future research work, not only associated with bone tissue engineering applications. It is expected that the analysis of alginate, gelatine and hydroxyapatite in terms of 3D bioprinting, clinical outcomes, scaffold architecture, and the regenerative medicine approach will enhance the research into bone tissue engineering in the near future. Continued studies into these research fields are highly recommended.

scholarly journals Evolution of the Scientific Literature on Input–Output Analysis: A Bibliometric Analysis of 1990–2017

2018 ◽  
Vol 10 (9) ◽  
pp. 3135 ◽  
Author(s):  
Yulei Xie ◽  
Ling Ji ◽  
Beibei Zhang ◽  
Gordon Huang
Keyword(s):  
Bibliometric Analysis ◽  
Citation Index ◽  
Publication Output ◽  
The United States ◽  
Input Output ◽  
Output Analysis ◽  
Related Field ◽  
Input Output Analysis ◽  
Research Institution ◽  
Productive Research

This study attempts to characterize the literature related to input–output analysis between 1990–2017 through bibliometric analysis technology based on the Science Citation Index and Social Sciences Citation Index databases. By means of bibliometric tools, this paper provides deep insights on the patterns of these articles, the most influential works and authors, and the emerging research topics. The results imply that China and the United States (USA) are the leading countries in terms of publication output. The Chinese Academy of Sciences is the most productive research institution, followed by Beijing Normal University and the University of Sydney. The Journal of Cleaner Production, Ecological Economics, and Energy Policy are the top mainstream journals in the input–output analysis-related field. Based on network analysis, this paper also discovers the hidden collaboration patterns and interrelations of countries, institutions, and authors. The bibliographic coupling and keywords concurrence networks are adopted to illustrate the input–output analysis evolution over time, and identify the current key research hotspots. The obtained results will help scientific researchers better understand the research status and frontier trends in this field, permit researchers to know the current research interests in the input–output analysis field, and provide useful information for further investigation and publication strategies.

Toward robust mammography-based models for breast cancer risk

2021 ◽  
Vol 13 (578) ◽  
pp. eaba4373 ◽  
Author(s):  
Adam Yala ◽  
Peter G. Mikhael ◽  
Fredrik Strand ◽  
Gigin Lin ◽  
Kevin Smith ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Deep Learning ◽  
High Risk ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Massachusetts General Hospital ◽  
The United States ◽  
University Hospital ◽  
Chang Gung Memorial Hospital ◽  
Risk Models

Improved breast cancer risk models enable targeted screening strategies that achieve earlier detection and less screening harm than existing guidelines. To bring deep learning risk models to clinical practice, we need to further refine their accuracy, validate them across diverse populations, and demonstrate their potential to improve clinical workflows. We developed Mirai, a mammography-based deep learning model designed to predict risk at multiple timepoints, leverage potentially missing risk factor information, and produce predictions that are consistent across mammography machines. Mirai was trained on a large dataset from Massachusetts General Hospital (MGH) in the United States and tested on held-out test sets from MGH, Karolinska University Hospital in Sweden, and Chang Gung Memorial Hospital (CGMH) in Taiwan, obtaining C-indices of 0.76 (95% confidence interval, 0.74 to 0.80), 0.81 (0.79 to 0.82), and 0.79 (0.79 to 0.83), respectively. Mirai obtained significantly higher 5-year ROC AUCs than the Tyrer-Cuzick model (P < 0.001) and prior deep learning models Hybrid DL (P < 0.001) and Image-Only DL (P < 0.001), trained on the same dataset. Mirai more accurately identified high-risk patients than prior methods across all datasets. On the MGH test set, 41.5% (34.4 to 48.5) of patients who would develop cancer within 5 years were identified as high risk, compared with 36.1% (29.1 to 42.9) by Hybrid DL (P = 0.02) and 22.9% (15.9 to 29.6) by the Tyrer-Cuzick model (P < 0.001).

scholarly journals Production Trends, Collaboration, and Main Topics of the Integrative and Complementary Oncology Research Area: A Bibliometric Analysis

2019 ◽  
Vol 18 ◽  
pp. 153473541984640 ◽  
Author(s):  
Jose A. Moral-Munoz ◽  
Lidia Carballo-Costa ◽  
Enrique Herrera-Viedma ◽  
Manuel J. Cobo
Keyword(s):  
Bibliometric Analysis ◽  
The United States ◽  
Research Area ◽  
Current Status ◽  
Future Research ◽  
Nf Kappa B ◽  
Republic Of China ◽  
The Past ◽  
Oncology Research ◽  
Complementary Oncology

Background: The prevalence of cancer has increased over time worldwide. Nevertheless, the number of deaths has been reduced during the past 2 decades. Thus, one-third of the cancer patients are users of complementary and alternative therapies, looking for other types of interventions. The main aim of the present study is to understand the current status of the research in integrative and complementary oncology. Three different aspects were analyzed: production trends, country collaboration, and leading research topics. Methods: The dataset was obtained from the documents indexed under the Integrative and Complementary Medicine category of the Web of Science database from 1976 to 2017. VOSviewer and SciMAT software were employed to perform the bibliometric analysis. Results: The Journal of Ethnopharmacology, China Medical University and the People’s Republic of China are the leading producers in the field. Regarding the collaboration, the United States and China present a close connection. The scientific community is focused on the following topics: apoptosis, breast cancer, oxidative stress, chemotherapy, and nuclear factor-Kappa-B (NF-Kappa-B). Conclusions: The present article shows potentially important information that allows understanding of the past, present, and future of research in integrative and complementary oncology. It is a useful evidence-based framework on which to base future research actions and academic directions.

scholarly journals A Bibliometric Analysis of Research on Acid Rain

2019 ◽  
Vol 11 (11) ◽  
pp. 3077 ◽  
Author(s):  
Ziqiang Liu ◽  
Jiayue Yang ◽  
Jiaen Zhang ◽  
Huimin Xiang ◽  
Hui Wei
Keyword(s):  
United States ◽  
Surface Water ◽  
Acid Rain ◽  
Bibliometric Analysis ◽  
Regional Scale ◽  
The United States ◽  
Research Area ◽  
Phosphorus Fractionation ◽  
Current Status ◽  
Negative Effects

With the continuation of industrialization and urbanization, acid rain (AR) has aroused extensive concern because of its potential negative effects on ecosystems. However, analysis of the current status and development trends in AR research area has seldom been systematically studied. Therefore, we motivated to conduct a bibliometric analysis of AR publications (1900–2018) using HistCite and CiteSpace software programs. Compared to traditional reviews by experts, this study offers an alternative method to quantitatively analyze and visualize the development of AR field at a large time scale. The results indicated that the overall concern of AR research studies had increased from 1900 to 2018. The most productive country was the United States, while the institution with the most publications was Chinese Academy of Sciences. “Environmental Sciences” was the most popular subject category, Water, Air, and Soil Pollution was the dominant journal, and C.T. Driscoll was the most prominent author in AR field. There were three hotspots in the field of AR, including analyzing AR status and its control policies in Europe, the United States, and China in the past few decades, investigating the ecological consequences of AR on plant histological, physiological, and biochemical traits, as well as surface water and soil properties, and the model application for quantitatively assessing AR and its effects on terrestrial and aquatic ecosystems at regional scale. Further, “behavior”, “phosphorus”, “fractionation”, “soil acidification”, “corrosion”, “performance”, “recovery”, “rainwater”, “trace element”, and “surface water” have been emerging active topics in recent years. This study can help new researchers to find out the most relevant subject categories, countries, institutions, journals, authors, and articles, and identify research trends and frontiers in the field of AR.

scholarly journals A five-year (2015 to 2019) analysis of studies focused on breast cancer prediction using machine learning: A systematic review and bibliometric analysis

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Zakia Salod ◽  
Yashik Singh
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Systematic Review ◽  
Bibliometric Analysis ◽  
The United States ◽  
Blood Analysis ◽  
Google Scholar ◽  
Breast Cancer Dataset ◽  
Cancer Dataset ◽  
Data Source

The objective 1 of this study was to investigate trends in breast cancer (BC) prediction using machine learning (ML) publications by analysing country, first author, journal, institutional collaborations and co-occurrence of author keywords. The objective 2 was to provide a review of studies on BC prediction using ML and a blood analysis dataset (Breast Cancer Coimbra Dataset [BCCD]), the objective 3 was to provide a brief review of studies based on BC prediction using ML and patients’ fine needle aspirate cytology data (Wisconsin Breast Cancer Dataset [WBCD]). The design of this study was as follows: for objective 1: bibliometric analysis, data source PubMed (2015-2019); for objective 2: systematic review, data source: Google and Google Scholar (2018-2019); for objective 3: systematic review, data source: Google Scholar (2016-2019). The results showed that the United States of America (USA) produced the highest number of publications (n=803). In total, 2419 first authors contributed towards the publications. Breast Cancer Research and Treatment was the highest ranked journal. Institutional collaborations mainly occurred within the USA. The use of ML for BC screening and detection was the most researched topic. A total of 19 distinct papers were included for objectives 2 and 3. The findings from these studies were never presented to clinicians for validations. In conclusion, the use of ML for BC screening and detection is promising.

Diagnostic Breast Imaging and Breast Cancer Staging

2019 ◽  
Author(s):  
Nidhi Sharma
Keyword(s):  
Breast Cancer ◽  
Cancer Detection ◽  
Breast Imaging ◽  
Breast Mri ◽  
Cancer Staging ◽  
The United States ◽  
Patient Treatment ◽  
Architectural Distortion ◽  
Diagnostic Modality ◽  
Cancer Breast

This review is geared to provide surgeons practical insight on breast imaging, intended to improve breast cancer detection and staging. Breast cancer is a leading cause of death in women in the United States. The American Joint Committee on Cancer staging system provides a tumor-node-metastasis classification that helps in determining prognosis and patient treatment. There is an increasing role of radiologists in ascertaining the correct cancer stage. Screening mammography is the basic tool and most widely used modality to detect breast cancer. The diagnostic work-up of a patient recalled from screening is the next step in assessing the artifacts and benign findings from more suspicious lesions. Additional mammographic views, tomosynthesis, and ultrasonography play an important role in determining if the finding represents a true lesion and if so, to localize and determine its level of suspicion to be cancer. Breast MRI is used both as a screening tool and a diagnostic modality to help in cancer detection and treatment planning. Recognizing patterns of benign masses, malignant calcifications, architectural distortion, and masses via a multimodality approach is the essential first step in further diagnosis. A quick overview of common interventional breast procedures may serve as a practical reference for the readers. This review contains 10 figures, 8 tables, and 39 references. Key Words: breast cancer, breast MRI, breast ultrasonography, fibroadenoma, invasive ductal staging, male breast, mammograms, postoperative breast, screening

The 100 Most Cited Articles on the Applications of Stem Cells in Osteoarthritis: A Bibliometric Analysis

2020 ◽  
Author(s):  
Keda Yang ◽  
Siming Zhou ◽  
Lin Tao
Keyword(s):  
Stem Cells ◽  
Stem Cell ◽  
Cell Therapy ◽  
Bibliometric Analysis ◽  
Stem Cell Therapy ◽  
Molecular Mechanisms ◽  
The United States ◽  
Research Area ◽  
General Information ◽  
Publication Number

Abstract Background: Stem cells have been applied in the treatment of OA, which had attracted wide attention. However, the research area is relatively extensive, and the research level is variable. In this study, we reviewed the mechanisms and clinical applications of stem cells in OA by using bibliometric analysis for the first time. We also revealed the characteristics, superior results and developmental trends in this field.Methods: The Web of Science core collection database was used to search articles related to the application of stem cells in OA. We collected the general information from the top 100 cited articles. We analyzed and evaluated the articles according to publication number, journals, institutions, countries, keywords and extended keywords.Results: The 100 most cited articles were cited from 129 to 1353 times mainly reviews and original articles. These articles were published from 2001 to 2017 and distributed evenly in America, East Asia and European countries. The United States contributed most in published number and international cooperation. The top ten institutions are mainly major universities and Duke University published a maximum of 10 articles. In terms of journals ,57 articles were published in the top ten journals. The keywords were divided into 8 categories from molecular mechanisms to clinical application.Conclusions: In our study, we found that mesenchymal stem cells (MSCs) which could repair articular cartilage and inhibit local inflammation, are the most widely applied in research and treatment of OA. TGF-βwas crucial during the process. Exosomes are regarded as the active ingredients in stem cell therapy for OA. Microtissue engineering will contribute to accurate and effective stem cell therapy. The findings of our study will contribute to the continuous development of research and direct the research of stem cells in OA.

scholarly journals Bibliometric Analysis Provides a Detailed Map of Information Literacy Literature in the Social Sciences and Humanities

2019 ◽  
Vol 14 (4) ◽  
pp. 177-178
Author(s):  
Jessica A. Koos
Keyword(s):  
Social Sciences ◽  
Bibliometric Analysis ◽  
Information Literacy ◽  
Research Collaboration ◽  
Activity Index ◽  
Developed Countries ◽  
The United States ◽  
Social Sciences And Humanities ◽  
The Social ◽  
Concept Of Information

A Review of: Bhardwaj, R.K. (2017). Information literacy in the social sciences and humanities: A bibliometric study. Information and Learning Science, 188(1/2), 67–89. https://doi.org/10.1108/ILS-09-2016-0068 Abstract Objective – To determine the scope and distribution of information literacy research documents in the humanities and social sciences published from 2001 to 2012. Design – Bibliometric analysis. Setting – N/A Subjects – 1,990 document records retrieved from a Scopus database search.  Methods – Using the database Scopus, the author created and conducted a search for documents related to the concept of information literacy. Articles, review papers, conference articles, notes, short surveys, and letters were included in the results. Only documents published from January 1, 2001 to December 31, 2012 were included in the study. The author then performed various bibliometric analyses of the results. Main Results – The author found that the number of publications and citations have increased over time, although the average citations per publication (ACPP) decreased significantly during the time period being studied. The majority of the literature published on this topic is in English and produced within the United States. The Transformative Activity Index was calculated to determine changes in publishing patterns across countries from 2001 to 2012. The amount of research collaboration across countries was calculated as well, with the U.S. being the most collaborative. The top journals publishing on this topic were identified by calculating the h-index. An individual from Universidad de Granada in Spain published the greatest number of articles from a single author, and this university was found to have produced the greatest amount of research. Documents produced by the United Kingdom have the highest citation rates. A total of 1,385 documents were cited at least once, and each item on average was cited five times. Conclusion – Most of the articles on information literacy in the social sciences and humanities comes from developed countries. The results of this study may help to inform those interested in researching this field further.

scholarly journals YEAST IN BIOPHARMACEUTICAL SCIENCES: VISUALISATION OF RESEARCH LANDSCAPE AND A BIBLIOMETRIC ANALYSIS

2021 ◽  
Vol 19 (1) ◽  
pp. 133-144
Author(s):  
JIE YEE WAN ◽  
CHIA WEI PHAN ◽  
NOORHIDAWATI ABDULLAH ◽  
YASAASWINI APPARAO ◽  
IAN MACREADIE
Keyword(s):  
United States ◽  
Bibliometric Analysis ◽  
Hot Spots ◽  
Research Output ◽  
The United States ◽  
Research Area ◽  
Steady Increase ◽  
Production Study ◽  
Scopus Database ◽  
Japan And China

The current study aims to analyse the trend in yeast research within the domain of biopharmaceutical sciences. Bibliographic information of the 1,000 most cited publications on yeast research in biopharmaceutical science was retrieved from the Scopus database. The data was then analysed by using bibliometric approaches. The data indicated a steady increase in publication numbers. The United States, Japan and China were among the highest research output countries. A total of 25 top core journals were identified. The keywords with the highest frequency included production, study and activity. To conclude, the current bibliometric analysis provides information that may be useful in locating research hot spots and gaps in the research area of yeast in biopharmaceutical science.

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