Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine
Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, e...
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| Veröffentlicht in: | Computers in biology and medicine 2023-08, Vol.162, p.107051-107051, Article 107051 |
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| creator | Gupta, Nancy Sanjay Kumar, Pravir |
| description | Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.
With artificial intelligence technology evolving, the medical and healthcare sectors are using big data for the diagnosis, treatment, and prognosis of numerous neurological diseases. This massive amount of data is gathered from various digital sources, including electronic health records, media, databases, etc. This data is analyzed, and numerous machine learning and deep learning algorithms are taught to detect risk factors, diagnose diseases, and suggest appropriate therapies. [Display omitted]
•Components of PM are therapy planning, risk projection, and diagnostic strategy.•AI-based precision medicine helps to identify and manage neurological diseases.•AI improves the availability of healthcare and lowers medical errors.•ML and multi-omics strategies aid in the development of disease predictive models.•AI-based PM includes image analysis, EHRs, wearable gadgets, etc. |
| doi_str_mv | 10.1016/j.compbiomed.2023.107051 |
| format | Article |
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With artificial intelligence technology evolving, the medical and healthcare sectors are using big data for the diagnosis, treatment, and prognosis of numerous neurological diseases. This massive amount of data is gathered from various digital sources, including electronic health records, media, databases, etc. This data is analyzed, and numerous machine learning and deep learning algorithms are taught to detect risk factors, diagnose diseases, and suggest appropriate therapies. [Display omitted]
•Components of PM are therapy planning, risk projection, and diagnostic strategy.•AI-based precision medicine helps to identify and manage neurological diseases.•AI improves the availability of healthcare and lowers medical errors.•ML and multi-omics strategies aid in the development of disease predictive models.•AI-based PM includes image analysis, EHRs, wearable gadgets, etc.</description><identifier>ISSN: 0010-4825</identifier><identifier>EISSN: 1879-0534</identifier><identifier>DOI: 10.1016/j.compbiomed.2023.107051</identifier><identifier>PMID: 37271113</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Accuracy ; Algorithms ; Artificial intelligence ; Big Data ; Customization ; Data analysis ; Data management ; Decision making ; Deep learning ; Disease ; Electronic health records ; Electronic medical records ; Handling ; Health care ; Health care industry ; Health services ; Healthcare industry ; Machine learning ; Medicine ; Multi-omics data ; Neurological diseases ; Neurological disorders ; Neurosciences ; Patients ; Physicians ; Precision medicine ; Supercomputers</subject><ispartof>Computers in biology and medicine, 2023-08, Vol.162, p.107051-107051, Article 107051</ispartof><rights>2023 Elsevier Ltd</rights><rights>Copyright © 2023 Elsevier Ltd. All rights reserved.</rights><rights>2023. Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c402t-2217741262cffdaf548ae3e3b2ec9a19339d351de995649ad347fdf5ec2356d03</citedby><cites>FETCH-LOGICAL-c402t-2217741262cffdaf548ae3e3b2ec9a19339d351de995649ad347fdf5ec2356d03</cites><orcidid>0000-0001-7444-2344</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2825496180?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>315,782,786,3554,27933,27934,46004,64394,64396,64398,72478</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37271113$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gupta, Nancy Sanjay</creatorcontrib><creatorcontrib>Kumar, Pravir</creatorcontrib><title>Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine</title><title>Computers in biology and medicine</title><addtitle>Comput Biol Med</addtitle><description>Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.
With artificial intelligence technology evolving, the medical and healthcare sectors are using big data for the diagnosis, treatment, and prognosis of numerous neurological diseases. This massive amount of data is gathered from various digital sources, including electronic health records, media, databases, etc. This data is analyzed, and numerous machine learning and deep learning algorithms are taught to detect risk factors, diagnose diseases, and suggest appropriate therapies. [Display omitted]
•Components of PM are therapy planning, risk projection, and diagnostic strategy.•AI-based precision medicine helps to identify and manage neurological diseases.•AI improves the availability of healthcare and lowers medical errors.•ML and multi-omics strategies aid in the development of disease predictive models.•AI-based PM includes image analysis, EHRs, wearable gadgets, etc.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Big Data</subject><subject>Customization</subject><subject>Data analysis</subject><subject>Data management</subject><subject>Decision making</subject><subject>Deep learning</subject><subject>Disease</subject><subject>Electronic health records</subject><subject>Electronic medical records</subject><subject>Handling</subject><subject>Health care</subject><subject>Health care industry</subject><subject>Health services</subject><subject>Healthcare industry</subject><subject>Machine 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data</topic><topic>Neurological diseases</topic><topic>Neurological disorders</topic><topic>Neurosciences</topic><topic>Patients</topic><topic>Physicians</topic><topic>Precision medicine</topic><topic>Supercomputers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gupta, Nancy Sanjay</creatorcontrib><creatorcontrib>Kumar, Pravir</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology 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Med</addtitle><date>2023-08</date><risdate>2023</risdate><volume>162</volume><spage>107051</spage><epage>107051</epage><pages>107051-107051</pages><artnum>107051</artnum><issn>0010-4825</issn><eissn>1879-0534</eissn><abstract>Mounting evidence has highlighted the implementation of big data handling and management in the healthcare industry to improve the clinical services. Various private and public companies have generated, stored, and analyzed different types of big healthcare data, such as omics data, clinical data, electronic health records, personal health records, and sensing data with the aim to move in the direction of precision medicine. Additionally, with the advancement in technologies, researchers are curious to extract the potential involvement of artificial intelligence and machine learning on big healthcare data to enhance the quality of patient's lives. However, seeking solutions from big healthcare data requires proper management, storage, and analysis, which imposes hinderances associated with big data handling. Herein, we briefly discuss the implication of big data handling and the role of artificial intelligence in precision medicine. Further, we also highlighted the potential of artificial intelligence in integrating and analyzing the big data that offer personalized treatment. In addition, we briefly discuss the applications of artificial intelligence in personalized treatment, especially in neurological diseases. Lastly, we discuss the challenges and limitations imposed by artificial intelligence in big data management and analysis to hinder precision medicine.
With artificial intelligence technology evolving, the medical and healthcare sectors are using big data for the diagnosis, treatment, and prognosis of numerous neurological diseases. This massive amount of data is gathered from various digital sources, including electronic health records, media, databases, etc. This data is analyzed, and numerous machine learning and deep learning algorithms are taught to detect risk factors, diagnose diseases, and suggest appropriate therapies. [Display omitted]
•Components of PM are therapy planning, risk projection, and diagnostic strategy.•AI-based precision medicine helps to identify and manage neurological diseases.•AI improves the availability of healthcare and lowers medical errors.•ML and multi-omics strategies aid in the development of disease predictive models.•AI-based PM includes image analysis, EHRs, wearable gadgets, etc.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>37271113</pmid><doi>10.1016/j.compbiomed.2023.107051</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0001-7444-2344</orcidid></addata></record> |
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| subjects | Accuracy Algorithms Artificial intelligence Big Data Customization Data analysis Data management Decision making Deep learning Disease Electronic health records Electronic medical records Handling Health care Health care industry Health services Healthcare industry Machine learning Medicine Multi-omics data Neurological diseases Neurological disorders Neurosciences Patients Physicians Precision medicine Supercomputers |
| title | Perspective of artificial intelligence in healthcare data management: A journey towards precision medicine |
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