東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back to Search results for [ null ]

Switch To: Labeled | MARC Mode | ISBD

Digital Skin Imaging Applications: A...

Sun, Mary D. ,

Linked to FindBook

Google Book

Amazon

博客來

Digital Skin Imaging Applications: Assessment of Image Acquisition Technique Features, Post-Acquisition Image Utilization, and Technology Standards /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Digital Skin Imaging Applications: Assessment of Image Acquisition Technique Features, Post-Acquisition Image Utilization, and Technology Standards // Mary D. Sun.
Author:	Sun, Mary D. ,
Description:	1 electronic resource (47 pages)
Notes:	Source: Masters Abstracts International, Volume: 84-10.
Contained By:	Masters Abstracts International84-10.
Subject:	Bioinformatics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30419595
ISBN:	9798379415372

Digital Skin Imaging Applications: Assessment of Image Acquisition Technique Features, Post-Acquisition Image Utilization, and Technology Standards /
Sun, Mary D. ,

Digital Skin Imaging Applications: Assessment of Image Acquisition Technique Features, Post-Acquisition Image Utilization, and Technology Standards /Mary D. Sun. - 1 electronic resource (47 pages)

Source: Masters Abstracts International, Volume: 84-10.

Background: The rapid adoption of digital skin imaging applications has increased the utilization of smartphone-acquired images in dermatology. While this has enormous potential for scaling the assessment of concerning skin lesions, the insufficient quality of images taken with, and analyses provided by consumer applications can potentially harm patients due to lack of diagnostic interpretability. We aim to characterize the current state of publicly discoverable digital skin imaging applications through a comprehensive assessment of their image acquisition features, post-acquisition image utilization processes, and technical characteristics.Methods: Publicly discoverable mobile, web, and desktop-based skin imaging applications, identified through keyword searches in mobile app stores, Google Search queries, previous teledermatology studies, and expert recommendations were independently assessed by three reviewers. Applications were categorized by primary, function, in-app connection to a healthcare provider, and user type. Applications were then further assessed by three independent reviewers for post-imaging content, tools, and functionality. Publicly available information was used to determine the presence or absence of relevant technology standards and/or data characteristics.Results: Just over half (57%) of 191 included skin imaging applications had at least one of fourteen image acquisition technique features. Those that were consumer-facing, intended for educational use, and designed for both patient and physician users had significantly greater feature richness (p<0.05). A total of 20 post-image acquisition features were identified across three categories: metadata attachment, functional tools, and image processing. Over 80% of all applications implemented metadata features, with nearly half having metadata features only. Individual feature occurrence and feature richness varied significantly by primary audience (p<0.0001) and function (p<0.0001). Less than half of all applications requested consent for user-uploaded photos and fewer than 10% provided clear data use and privacy policies.Conclusions: Very few skin imaging applications included more than one image acquisition technique feature, with feature richness varying significantly by audience, function, and user categories. Users of digital dermatology tools should consider which applications have standardized features that improve image quality. Post-imaging functionality in skin imaging applications also varies significantly by audience and function, though nearly all implement basic metadata labeling. Technical standards are often not implemented or reported consistently. Gaps in the provision of clear consent, data privacy, and data use policies should be urgently addressed.

English

ISBN: 9798379415372Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Biodesign

Digital Skin Imaging Applications: Assessment of Image Acquisition Technique Features, Post-Acquisition Image Utilization, and Technology Standards /
LDR:04276nmm a22004453i 4500 001 2396160
005 20250522083201.5
006 m o d
007 cr|nu||||||||
008 251215s2023 miu||||||m |||||||eng d
020 $a 9798379415372
035 $a (MiAaPQD)AAI30419595
035 $a AAI30419595
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Sun, Mary D. , $e author. $0 (orcid)0000-0003-3964-3858 $3 3765755
245 1 0 $a Digital Skin Imaging Applications: Assessment of Image Acquisition Technique Features, Post-Acquisition Image Utilization, and Technology Standards / $c Mary D. Sun.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2023
300 $a 1 electronic resource (47 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 84-10.
500 $a Advisors: Halpern, Allan Committee members: Gabrilove, Janice.
502 $b M.S. $c Icahn School of Medicine at Mount Sinai $d 2023.
520 $a Background: The rapid adoption of digital skin imaging applications has increased the utilization of smartphone-acquired images in dermatology. While this has enormous potential for scaling the assessment of concerning skin lesions, the insufficient quality of images taken with, and analyses provided by consumer applications can potentially harm patients due to lack of diagnostic interpretability. We aim to characterize the current state of publicly discoverable digital skin imaging applications through a comprehensive assessment of their image acquisition features, post-acquisition image utilization processes, and technical characteristics.Methods: Publicly discoverable mobile, web, and desktop-based skin imaging applications, identified through keyword searches in mobile app stores, Google Search queries, previous teledermatology studies, and expert recommendations were independently assessed by three reviewers. Applications were categorized by primary, function, in-app connection to a healthcare provider, and user type. Applications were then further assessed by three independent reviewers for post-imaging content, tools, and functionality. Publicly available information was used to determine the presence or absence of relevant technology standards and/or data characteristics.Results: Just over half (57%) of 191 included skin imaging applications had at least one of fourteen image acquisition technique features. Those that were consumer-facing, intended for educational use, and designed for both patient and physician users had significantly greater feature richness (p<0.05). A total of 20 post-image acquisition features were identified across three categories: metadata attachment, functional tools, and image processing. Over 80% of all applications implemented metadata features, with nearly half having metadata features only. Individual feature occurrence and feature richness varied significantly by primary audience (p<0.0001) and function (p<0.0001). Less than half of all applications requested consent for user-uploaded photos and fewer than 10% provided clear data use and privacy policies.Conclusions: Very few skin imaging applications included more than one image acquisition technique feature, with feature richness varying significantly by audience, function, and user categories. Users of digital dermatology tools should consider which applications have standardized features that improve image quality. Post-imaging functionality in skin imaging applications also varies significantly by audience and function, though nearly all implement basic metadata labeling. Technical standards are often not implemented or reported consistently. Gaps in the provision of clear consent, data privacy, and data use policies should be urgently addressed.
546 $a English
590 $a School code: 1734
650 4 $a Bioinformatics. $3 553671
650 4 $a Medical imaging. $3 3172799
650 4 $a Computer science. $3 523869
653 $a Biodesign
653 $a Bioinformatics
653 $a Dermatology
653 $a Health technology
653 $a Technology policy
653 $a Telemedicine
690 $a 0715
690 $a 0574
690 $a 0984
710 2 $a Icahn School of Medicine at Mount Sinai. $b Clinical Research. $e degree granting institution. $3 3765756
720 1 $a Halpern, Allan $e degree supervisor.
773 0 $t Masters Abstracts International $g 84-10.
790 $a 1734
791 $a M.S.
792 $a 2023
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30419595