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Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification

SIMPLE SUMMARY: This study is a new way of providing potential opportunities for prevention, diagnosis, and therapy to investigate the comprehensive trends in cancer nanotechnology research. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed...

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Autores principales: Millagaha Gedara, Nuwan Indika, Xu, Xuan, DeLong, Robert, Aryal, Santosh, Jaberi-Douraki, Majid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431703/
https://www.ncbi.nlm.nih.gov/pubmed/34503227
http://dx.doi.org/10.3390/cancers13174417
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author Millagaha Gedara, Nuwan Indika
Xu, Xuan
DeLong, Robert
Aryal, Santosh
Jaberi-Douraki, Majid
author_facet Millagaha Gedara, Nuwan Indika
Xu, Xuan
DeLong, Robert
Aryal, Santosh
Jaberi-Douraki, Majid
author_sort Millagaha Gedara, Nuwan Indika
collection PubMed
description SIMPLE SUMMARY: This study is a new way of providing potential opportunities for prevention, diagnosis, and therapy to investigate the comprehensive trends in cancer nanotechnology research. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000–2021. It mined nearly 50,000 papers published in multiple reputed journals. The impact of our findings is significant, which focuses on hybrid medical models and content-based and bibliometric features for machine learning models in cancer detection, diagnosis, imaging, and therapy related to cancer nanotechnology in the world. We mainly identified and classified the top and significant keywords, countries, authors, affiliations, and research areas representing the documents in the top 100 journals in cancer nanotechnology, which will help researchers explore more powerful anticancer nanomedicines in the next five to ten years. ABSTRACT: This study presents a new way to investigate comprehensive trends in cancer nanotechnology research in different countries, institutions, and journals providing critical insights to prevention, diagnosis, and therapy. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000–2021. Inspired by hybrid medical models and content-based and bibliometric features for machine learning models, our results show cancer nanotechnology studies have expanded exponentially since 2010. The highest production of articles in cancer nanotechnology is mainly from US institutions, with several countries, notably the USA, China, the UK, India, and Iran as concentrated focal points as centers of cancer nanotechnology research, especially in the last five years. The analysis shows the greatest overlap between nanotechnology and DNA, RNA, iron oxide or mesoporous silica, breast cancer, and cancer diagnosis and cancer treatment. Moreover, more than 50% of the information related to the keywords, authors, institutions, journals, and countries are considerably investigated in the form of publications from the top 100 journals. This study has the potential to provide past and current lines of research that can unmask comprehensive trends in cancer nanotechnology, key research topics, or the most productive countries and authors in the field.
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spelling pubmed-84317032021-09-11 Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification Millagaha Gedara, Nuwan Indika Xu, Xuan DeLong, Robert Aryal, Santosh Jaberi-Douraki, Majid Cancers (Basel) Review SIMPLE SUMMARY: This study is a new way of providing potential opportunities for prevention, diagnosis, and therapy to investigate the comprehensive trends in cancer nanotechnology research. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000–2021. It mined nearly 50,000 papers published in multiple reputed journals. The impact of our findings is significant, which focuses on hybrid medical models and content-based and bibliometric features for machine learning models in cancer detection, diagnosis, imaging, and therapy related to cancer nanotechnology in the world. We mainly identified and classified the top and significant keywords, countries, authors, affiliations, and research areas representing the documents in the top 100 journals in cancer nanotechnology, which will help researchers explore more powerful anticancer nanomedicines in the next five to ten years. ABSTRACT: This study presents a new way to investigate comprehensive trends in cancer nanotechnology research in different countries, institutions, and journals providing critical insights to prevention, diagnosis, and therapy. This paper applied the qualitative method of bibliometric analysis on cancer nanotechnology using the PubMed database during the years 2000–2021. Inspired by hybrid medical models and content-based and bibliometric features for machine learning models, our results show cancer nanotechnology studies have expanded exponentially since 2010. The highest production of articles in cancer nanotechnology is mainly from US institutions, with several countries, notably the USA, China, the UK, India, and Iran as concentrated focal points as centers of cancer nanotechnology research, especially in the last five years. The analysis shows the greatest overlap between nanotechnology and DNA, RNA, iron oxide or mesoporous silica, breast cancer, and cancer diagnosis and cancer treatment. Moreover, more than 50% of the information related to the keywords, authors, institutions, journals, and countries are considerably investigated in the form of publications from the top 100 journals. This study has the potential to provide past and current lines of research that can unmask comprehensive trends in cancer nanotechnology, key research topics, or the most productive countries and authors in the field. MDPI 2021-09-01 /pmc/articles/PMC8431703/ /pubmed/34503227 http://dx.doi.org/10.3390/cancers13174417 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Millagaha Gedara, Nuwan Indika
Xu, Xuan
DeLong, Robert
Aryal, Santosh
Jaberi-Douraki, Majid
Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification
title Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification
title_full Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification
title_fullStr Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification
title_full_unstemmed Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification
title_short Global Trends in Cancer Nanotechnology: A Qualitative Scientific Mapping Using Content-Based and Bibliometric Features for Machine Learning Text Classification
title_sort global trends in cancer nanotechnology: a qualitative scientific mapping using content-based and bibliometric features for machine learning text classification
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8431703/
https://www.ncbi.nlm.nih.gov/pubmed/34503227
http://dx.doi.org/10.3390/cancers13174417
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