The synergy of cybernetical intelligence with medical image analysis for deep medicine: A methodological perspective
•The development process and application status of three basic models of deep learning in medical image field are reviewed and discussed.•With the advent of machine learning research boom, there are more research methods of deep learning.•Apply deep learning in the field of medical image analysis ha...
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Veröffentlicht in: | Computer methods and programs in biomedicine 2023-10, Vol.240, p.107677-107677, Article 107677 |
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container_title | Computer methods and programs in biomedicine |
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creator | Wong, Kelvin KL Ayoub, Muhammad Cao, Zaijie Chen, Cang Chen, Weimin Ghista, Dhanjoo N. Zhang, Chris W.J. |
description | •The development process and application status of three basic models of deep learning in medical image field are reviewed and discussed.•With the advent of machine learning research boom, there are more research methods of deep learning.•Apply deep learning in the field of medical image analysis has great practical significance and social value in high-precision intelligent recognition.
To introduce the concept of cybernetical intelligence, deep learning, development history, international research, algorithms, and the application of these models in smart medical image analysis and deep medicine are reviewed in this paper. This study also defines the terminologies for cybernetical intelligence, deep medicine, and precision medicine.
Through literature research and knowledge reorganization, this review explores the fundamental concepts and practical applications of various deep learning techniques and cybernetical intelligence by conducting extensive literature research and reorganizing existing knowledge in medical imaging and deep medicine. The discussion mainly centers on the applications of classical models in this field and addresses the limitations and challenges of these basic models.
In this paper, the more comprehensive overview of the classical structural modules in convolutional neural networks is described in detail from the perspective of cybernetical intelligence in deep medicine. The results and data of major research contents of deep learning are consolidated and summarized.
There are some problems in machine learning internationally, such as insufficient research techniques, unsystematic research methods, incomplete research depth, and incomplete evaluation research. Some suggestions are given in our review to solve the problems existing in the deep learning models. Cybernetical intelligence has proven to be a valuable and promising avenue for advancing various fields, including deep medicine and personalized medicine. |
doi_str_mv | 10.1016/j.cmpb.2023.107677 |
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To introduce the concept of cybernetical intelligence, deep learning, development history, international research, algorithms, and the application of these models in smart medical image analysis and deep medicine are reviewed in this paper. This study also defines the terminologies for cybernetical intelligence, deep medicine, and precision medicine.
Through literature research and knowledge reorganization, this review explores the fundamental concepts and practical applications of various deep learning techniques and cybernetical intelligence by conducting extensive literature research and reorganizing existing knowledge in medical imaging and deep medicine. The discussion mainly centers on the applications of classical models in this field and addresses the limitations and challenges of these basic models.
In this paper, the more comprehensive overview of the classical structural modules in convolutional neural networks is described in detail from the perspective of cybernetical intelligence in deep medicine. The results and data of major research contents of deep learning are consolidated and summarized.
There are some problems in machine learning internationally, such as insufficient research techniques, unsystematic research methods, incomplete research depth, and incomplete evaluation research. Some suggestions are given in our review to solve the problems existing in the deep learning models. Cybernetical intelligence has proven to be a valuable and promising avenue for advancing various fields, including deep medicine and personalized medicine.</description><identifier>ISSN: 0169-2607</identifier><identifier>EISSN: 1872-7565</identifier><identifier>DOI: 10.1016/j.cmpb.2023.107677</identifier><identifier>PMID: 37390794</identifier><language>eng</language><publisher>Ireland: Elsevier B.V</publisher><subject>Cybernetical intelligence ; Deep medicine ; Diagnosis ; Medical imaging ; Precision medicine</subject><ispartof>Computer methods and programs in biomedicine, 2023-10, Vol.240, p.107677-107677, Article 107677</ispartof><rights>2023</rights><rights>Copyright © 2023. Published by Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-ca7cdad4110f37c513a253f415cfc050511459f55454c679e7df248d8964c13e3</citedby><cites>FETCH-LOGICAL-c356t-ca7cdad4110f37c513a253f415cfc050511459f55454c679e7df248d8964c13e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.cmpb.2023.107677$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37390794$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wong, Kelvin KL</creatorcontrib><creatorcontrib>Ayoub, Muhammad</creatorcontrib><creatorcontrib>Cao, Zaijie</creatorcontrib><creatorcontrib>Chen, Cang</creatorcontrib><creatorcontrib>Chen, Weimin</creatorcontrib><creatorcontrib>Ghista, Dhanjoo N.</creatorcontrib><creatorcontrib>Zhang, Chris W.J.</creatorcontrib><title>The synergy of cybernetical intelligence with medical image analysis for deep medicine: A methodological perspective</title><title>Computer methods and programs in biomedicine</title><addtitle>Comput Methods Programs Biomed</addtitle><description>•The development process and application status of three basic models of deep learning in medical image field are reviewed and discussed.•With the advent of machine learning research boom, there are more research methods of deep learning.•Apply deep learning in the field of medical image analysis has great practical significance and social value in high-precision intelligent recognition.
To introduce the concept of cybernetical intelligence, deep learning, development history, international research, algorithms, and the application of these models in smart medical image analysis and deep medicine are reviewed in this paper. This study also defines the terminologies for cybernetical intelligence, deep medicine, and precision medicine.
Through literature research and knowledge reorganization, this review explores the fundamental concepts and practical applications of various deep learning techniques and cybernetical intelligence by conducting extensive literature research and reorganizing existing knowledge in medical imaging and deep medicine. The discussion mainly centers on the applications of classical models in this field and addresses the limitations and challenges of these basic models.
In this paper, the more comprehensive overview of the classical structural modules in convolutional neural networks is described in detail from the perspective of cybernetical intelligence in deep medicine. The results and data of major research contents of deep learning are consolidated and summarized.
There are some problems in machine learning internationally, such as insufficient research techniques, unsystematic research methods, incomplete research depth, and incomplete evaluation research. Some suggestions are given in our review to solve the problems existing in the deep learning models. Cybernetical intelligence has proven to be a valuable and promising avenue for advancing various fields, including deep medicine and personalized medicine.</description><subject>Cybernetical intelligence</subject><subject>Deep medicine</subject><subject>Diagnosis</subject><subject>Medical imaging</subject><subject>Precision medicine</subject><issn>0169-2607</issn><issn>1872-7565</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kM1u2zAQhImiQe04fYEeCh5zkcsfUZSKXAKjbQoYyMU5EzS5tGnIokrKDvT2pSsnx552sTszwHwIfaFkSQmtvh2W5thvl4wwng-ykvIDmtNaskKKSnxE8yxqClYROUO3KR0IIUyI6hOacckbIptyjobNHnAaO4i7EQeHzbiF2MHgjW6x7wZoW7-DzgB-9cMeH8FOn6PeAdadbsfkE3YhYgvQT3_fwXf8mPdhH2xow-6fpYeYejCDP8MdunG6TfD5Ohfo5eePzeqpWD__-r16XBeGi2oojJbGaltSShyXRlCumeCupMI4QwQRlJaicUKUojSVbEBax8ra1k1VGsqBL9D9lNvH8OcEaVBHn0yupDsIp6RYzZmQtcipC8QmqYkhpQhO9TGXjKOiRF1oq4O60FYX2mqinU1fr_mnbW7-bnnDmwUPkwByy7OHqJLxF5rWx4xC2eD_l_8XmPyR0w</recordid><startdate>20231001</startdate><enddate>20231001</enddate><creator>Wong, Kelvin KL</creator><creator>Ayoub, Muhammad</creator><creator>Cao, Zaijie</creator><creator>Chen, Cang</creator><creator>Chen, Weimin</creator><creator>Ghista, Dhanjoo N.</creator><creator>Zhang, Chris W.J.</creator><general>Elsevier B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20231001</creationdate><title>The synergy of cybernetical intelligence with medical image analysis for deep medicine: A methodological perspective</title><author>Wong, Kelvin KL ; Ayoub, Muhammad ; Cao, Zaijie ; Chen, Cang ; Chen, Weimin ; Ghista, Dhanjoo N. ; Zhang, Chris W.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-ca7cdad4110f37c513a253f415cfc050511459f55454c679e7df248d8964c13e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cybernetical intelligence</topic><topic>Deep medicine</topic><topic>Diagnosis</topic><topic>Medical imaging</topic><topic>Precision medicine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wong, Kelvin KL</creatorcontrib><creatorcontrib>Ayoub, Muhammad</creatorcontrib><creatorcontrib>Cao, Zaijie</creatorcontrib><creatorcontrib>Chen, Cang</creatorcontrib><creatorcontrib>Chen, Weimin</creatorcontrib><creatorcontrib>Ghista, Dhanjoo N.</creatorcontrib><creatorcontrib>Zhang, Chris W.J.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Computer methods and programs in biomedicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wong, Kelvin KL</au><au>Ayoub, Muhammad</au><au>Cao, Zaijie</au><au>Chen, Cang</au><au>Chen, Weimin</au><au>Ghista, Dhanjoo N.</au><au>Zhang, Chris W.J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The synergy of cybernetical intelligence with medical image analysis for deep medicine: A methodological perspective</atitle><jtitle>Computer methods and programs in biomedicine</jtitle><addtitle>Comput Methods Programs Biomed</addtitle><date>2023-10-01</date><risdate>2023</risdate><volume>240</volume><spage>107677</spage><epage>107677</epage><pages>107677-107677</pages><artnum>107677</artnum><issn>0169-2607</issn><eissn>1872-7565</eissn><abstract>•The development process and application status of three basic models of deep learning in medical image field are reviewed and discussed.•With the advent of machine learning research boom, there are more research methods of deep learning.•Apply deep learning in the field of medical image analysis has great practical significance and social value in high-precision intelligent recognition.
To introduce the concept of cybernetical intelligence, deep learning, development history, international research, algorithms, and the application of these models in smart medical image analysis and deep medicine are reviewed in this paper. This study also defines the terminologies for cybernetical intelligence, deep medicine, and precision medicine.
Through literature research and knowledge reorganization, this review explores the fundamental concepts and practical applications of various deep learning techniques and cybernetical intelligence by conducting extensive literature research and reorganizing existing knowledge in medical imaging and deep medicine. The discussion mainly centers on the applications of classical models in this field and addresses the limitations and challenges of these basic models.
In this paper, the more comprehensive overview of the classical structural modules in convolutional neural networks is described in detail from the perspective of cybernetical intelligence in deep medicine. The results and data of major research contents of deep learning are consolidated and summarized.
There are some problems in machine learning internationally, such as insufficient research techniques, unsystematic research methods, incomplete research depth, and incomplete evaluation research. Some suggestions are given in our review to solve the problems existing in the deep learning models. Cybernetical intelligence has proven to be a valuable and promising avenue for advancing various fields, including deep medicine and personalized medicine.</abstract><cop>Ireland</cop><pub>Elsevier B.V</pub><pmid>37390794</pmid><doi>10.1016/j.cmpb.2023.107677</doi><tpages>1</tpages></addata></record> |
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subjects | Cybernetical intelligence Deep medicine Diagnosis Medical imaging Precision medicine |
title | The synergy of cybernetical intelligence with medical image analysis for deep medicine: A methodological perspective |
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