Domain classification and analysis of national institutes of health‐funded medical physics research.
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| Title: | Domain classification and analysis of national institutes of health‐funded medical physics research. |
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| Authors: | Scarpelli, Matthew1 (AUTHOR), Whelan, Brendan2 (AUTHOR), Farahani, Keyvan3 (AUTHOR) farahank@mail.nih.gov |
| Source: | Medical Physics. Feb2021, Vol. 48 Issue 2, p605-614. 10p. |
| Subjects: | National Institutes of Health (U.S.), Medical physics, Research grants, Particle beams, Artificial intelligence, Databases |
| Abstract: | Purpose: The American Association of Physicists in Medicine (AAPM) previously developed a research database consisting of the National Institutes of Health (NIH) grants that were awarded to its members. The purpose of this report is to classify these NIH grants into various medical physics subdisciplines and analyze the scope of AAPM member research. Methods: For this report, an algorithm classified grant topics into medical physics research subdisciplines (grants from 2002 to 2019 were analyzed). This algorithm utilized a search for common words and phrases within grant titles, keywords, abstracts, and activity codes to perform the classification. AAPM member grants were compared with non‐AAPM member grants in various relevant subcategories to assess what percentage of these grants was held by AAPM members. Results: The percentage of AAPM member grants that included words relating to both imaging and therapy (image‐guided therapy grants) increased from 13% (27/207) in 2002 to 27% (79/293) in 2019. The percentage of AAPM member grants utilizing words relating to artificial intelligence increased from 8% in 2002 to 20% in 2019. From 2002 to 2019, AAPM member grants referenced cancer more than all other diseases combined. The majority of AAPM member grants included words relating to clinical research (81% of grants in 2002 and 99% in 2019). When comparing AAPM member with non‐AAPM member grants it was found that in 2019 AAPM members held a substantial fraction of all NIH grants that referenced stereotactic radiation therapies (41%), radionuclide therapies (10%), brachytherapies (35%), intensity‐modulated radiation therapies (45%), and external beam particle therapies (55%). From 2002 to 2019, the percentage of AAPM membership holding NIH grants decreased for males (3.2% down to 2.3%) and increased for females (0.8% up to 1.3%) Conclusions: The majority of grants awarded to AAPM members focus on clinical research, which underlies the translational aspect of medical physics and suggests medical physicists are uniquely positioned to help translate new technologies such as artificial intelligence into the clinic. Since 2002, NIH grants awarded to AAPM members have increasingly referenced some form of image‐guided therapy, suggesting opportunities for continued innovation of imaging technologies. A substantial fraction of all radiotherapy‐related research grants were awarded to AAPM members, emphasizing the important role physicists have in developing radiotherapy‐related treatments. [ABSTRACT FROM AUTHOR] |
| Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
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| Items | – Name: Title Label: Title Group: Ti Data: Domain classification and analysis of national institutes of health‐funded medical physics research. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Scarpelli%2C+Matthew%22">Scarpelli, Matthew</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Whelan%2C+Brendan%22">Whelan, Brendan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Farahani%2C+Keyvan%22">Farahani, Keyvan</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> farahank@mail.nih.gov</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medical+Physics%22">Medical Physics</searchLink>. Feb2021, Vol. 48 Issue 2, p605-614. 10p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22National+Institutes+of+Health+%28U%2ES%2E%29%22">National Institutes of Health (U.S.)</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+physics%22">Medical physics</searchLink><br /><searchLink fieldCode="DE" term="%22Research+grants%22">Research grants</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+beams%22">Particle beams</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: The American Association of Physicists in Medicine (AAPM) previously developed a research database consisting of the National Institutes of Health (NIH) grants that were awarded to its members. The purpose of this report is to classify these NIH grants into various medical physics subdisciplines and analyze the scope of AAPM member research. Methods: For this report, an algorithm classified grant topics into medical physics research subdisciplines (grants from 2002 to 2019 were analyzed). This algorithm utilized a search for common words and phrases within grant titles, keywords, abstracts, and activity codes to perform the classification. AAPM member grants were compared with non‐AAPM member grants in various relevant subcategories to assess what percentage of these grants was held by AAPM members. Results: The percentage of AAPM member grants that included words relating to both imaging and therapy (image‐guided therapy grants) increased from 13% (27/207) in 2002 to 27% (79/293) in 2019. The percentage of AAPM member grants utilizing words relating to artificial intelligence increased from 8% in 2002 to 20% in 2019. From 2002 to 2019, AAPM member grants referenced cancer more than all other diseases combined. The majority of AAPM member grants included words relating to clinical research (81% of grants in 2002 and 99% in 2019). When comparing AAPM member with non‐AAPM member grants it was found that in 2019 AAPM members held a substantial fraction of all NIH grants that referenced stereotactic radiation therapies (41%), radionuclide therapies (10%), brachytherapies (35%), intensity‐modulated radiation therapies (45%), and external beam particle therapies (55%). From 2002 to 2019, the percentage of AAPM membership holding NIH grants decreased for males (3.2% down to 2.3%) and increased for females (0.8% up to 1.3%) Conclusions: The majority of grants awarded to AAPM members focus on clinical research, which underlies the translational aspect of medical physics and suggests medical physicists are uniquely positioned to help translate new technologies such as artificial intelligence into the clinic. Since 2002, NIH grants awarded to AAPM members have increasingly referenced some form of image‐guided therapy, suggesting opportunities for continued innovation of imaging technologies. A substantial fraction of all radiotherapy‐related research grants were awarded to AAPM members, emphasizing the important role physicists have in developing radiotherapy‐related treatments. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medical Physics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mp.14469 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 10 StartPage: 605 Subjects: – SubjectFull: National Institutes of Health (U.S.) Type: general – SubjectFull: Medical physics Type: general – SubjectFull: Research grants Type: general – SubjectFull: Particle beams Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Databases Type: general Titles: – TitleFull: Domain classification and analysis of national institutes of health‐funded medical physics research. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Scarpelli, Matthew – PersonEntity: Name: NameFull: Whelan, Brendan – PersonEntity: Name: NameFull: Farahani, Keyvan IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2021 Type: published Y: 2021 Identifiers: – Type: issn-print Value: 00942405 Numbering: – Type: volume Value: 48 – Type: issue Value: 2 Titles: – TitleFull: Medical Physics Type: main |
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