 Diagnosis, Computer-Assisted
"Diagnosis, Computer-Assisted" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Application of computer programs designed to assist the physician in solving a diagnostic problem.
| Descriptor ID |
D003936
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| MeSH Number(s) |
E01.158 L01.313.500.750.100.158
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| Concept/Terms |
Diagnosis, Computer-Assisted- Diagnosis, Computer-Assisted
- Diagnosis, Computer Assisted
- Computer-Assisted Diagnosis
- Computer Assisted Diagnosis
- Computer-Assisted Diagnoses
- Diagnoses, Computer-Assisted
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Below are MeSH descriptors whose meaning is more general than "Diagnosis, Computer-Assisted".
Below are MeSH descriptors whose meaning is more specific than "Diagnosis, Computer-Assisted".
This graph shows the total number of publications written about "Diagnosis, Computer-Assisted" by people in this website by year, and whether "Diagnosis, Computer-Assisted" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 1995 | 0 | 1 | 1 | | 1997 | 1 | 1 | 2 | | 2004 | 5 | 1 | 6 | | 2005 | 1 | 2 | 3 | | 2006 | 2 | 1 | 3 | | 2007 | 2 | 1 | 3 | | 2008 | 4 | 0 | 4 | | 2011 | 1 | 1 | 2 | | 2012 | 5 | 1 | 6 | | 2013 | 6 | 0 | 6 | | 2014 | 4 | 0 | 4 | | 2015 | 4 | 1 | 5 | | 2016 | 1 | 1 | 2 | | 2017 | 3 | 0 | 3 | | 2018 | 4 | 1 | 5 | | 2019 | 4 | 1 | 5 | | 2020 | 1 | 1 | 2 | | 2021 | 2 | 0 | 2 | | 2024 | 1 | 1 | 2 |
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Below are the most recent publications written about "Diagnosis, Computer-Assisted" by people in Profiles.
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Rex DK, Bhavsar-Burke I, Buckles D, Burton J, Cartee A, Comar K, Edwards A, Fennimore B, Fischer M, Gerich M, Gilmore A, Hamdeh S, Hoffman J, Ibach M, Jackson M, James-Stevenson T, Kaltenbach T, Kaplan J, Kapur S, Kohm D, Kriss M, Kundumadam S, Kyanam Kabir Baig KR, Menard-Katcher P, Kraft C, Langworthy J, Misra B, Molloy E, Munoz JC, Norvell J, Nowak T, Obaitan I, Patel S, Patel M, Peter S, Reid BM, Rogers N, Ross J, Ryan J, Sagi S, Saito A, Samo S, Sarkis F, Scott FI, Siwiec R, Sullivan S, Wieland A, Zhang J, Repici A, Hassan C, Byrne MF, Rastogi A. Artificial Intelligence for Real-Time Prediction of the Histology of Colorectal Polyps by General Endoscopists. Ann Intern Med. 2024 Jul; 177(7):911-918.
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Maki JH, Patel NU, Ulrich EJ, Dhaouadi J, Jones RW. Part II: Effect of different evaluation methods to the application of a computer-aided prostate MRI detection/diagnosis (CADe/CADx) device on reader performance. Curr Probl Diagn Radiol. 2024 Sep-Oct; 53(5):614-623.
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Wang X, Bera K, Barrera C, Zhou Y, Lu C, Vaidya P, Fu P, Yang M, Schmid RA, Berezowska S, Choi H, Velcheti V, Madabhushi A. A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer. EBioMedicine. 2021 Jul; 69:103481.
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King CA, Brent D, Grupp-Phelan J, Casper TC, Dean JM, Chernick LS, Fein JA, Mahabee-Gittens EM, Patel SJ, Mistry RD, Duffy S, Melzer-Lange M, Rogers A, Cohen DM, Keller A, Shenoi R, Hickey RW, Rea M, Cwik M, Page K, McGuire TC, Wang J, Gibbons R. Prospective Development and Validation of the Computerized Adaptive Screen for Suicidal Youth. JAMA Psychiatry. 2021 05 01; 78(5):540-549.
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Chen JS, Coyner AS, Ostmo S, Sonmez K, Bajimaya S, Pradhan E, Valikodath N, Cole ED, Al-Khaled T, Chan RVP, Singh P, Kalpathy-Cramer J, Chiang MF, Campbell JP. Deep Learning for the Diagnosis of Stage in?Retinopathy of Prematurity: Accuracy and Generalizability across Populations and Cameras. Ophthalmol Retina. 2021 10; 5(10):1027-1035.
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Kang JS, Lee C, Song W, Choo W, Lee S, Lee S, Han Y, Bassi C, Salvia R, Marchegiani G, Wolfgang CL, He J, Blair AB, Kluger MD, Su GH, Kim SC, Song KB, Yamamoto M, Higuchi R, Hatori T, Yang CY, Yamaue H, Hirono S, Satoi S, Fujii T, Hirano S, Lou W, Hashimoto Y, Shimizu Y, Del Chiaro M, Valente R, Lohr M, Choi DW, Choi SH, Heo JS, Motoi F, Matsumoto I, Lee WJ, Kang CM, Shyr YM, Wang SE, Han HS, Yoon YS, Besselink MG, van Huijgevoort NCM, Sho M, Nagano H, Kim SG, Honda G, Yang Y, Yu HC, Do Yang J, Chung JC, Nagakawa Y, Seo HI, Choi YJ, Byun Y, Kim H, Kwon W, Park T, Jang JY. Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning. Sci Rep. 2020 11 18; 10(1):20140.
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Prince EW, Whelan R, Mirsky DM, Stence N, Staulcup S, Klimo P, Anderson RCE, Niazi TN, Grant G, Souweidane M, Johnston JM, Jackson EM, Limbrick DD, Smith A, Drapeau A, Chern JJ, Kilburn L, Ginn K, Naftel R, Dudley R, Tyler-Kabara E, Jallo G, Handler MH, Jones K, Donson AM, Foreman NK, Hankinson TC. Robust deep learning classification of adamantinomatous craniopharyngioma from limited preoperative radiographic images. Sci Rep. 2020 10 09; 10(1):16885.
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Ginestra JC, Giannini HM, Schweickert WD, Meadows L, Lynch MJ, Pavan K, Chivers CJ, Draugelis M, Donnelly PJ, Fuchs BD, Umscheid CA. Clinician Perception of a Machine Learning-Based Early Warning System Designed to Predict Severe Sepsis and Septic Shock. Crit Care Med. 2019 11; 47(11):1477-1484.
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Giannini HM, Ginestra JC, Chivers C, Draugelis M, Hanish A, Schweickert WD, Fuchs BD, Meadows L, Lynch M, Donnelly PJ, Pavan K, Fishman NO, Hanson CW, Umscheid CA. A Machine Learning Algorithm to Predict Severe Sepsis and Septic Shock: Development, Implementation, and Impact on Clinical Practice. Crit Care Med. 2019 11; 47(11):1485-1492.
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Damme KSF, Osborne KJ, Gold JM, Mittal VA. Detecting motor slowing in clinical high risk for psychosis in a computerized finger tapping model. Eur Arch Psychiatry Clin Neurosci. 2020 Apr; 270(3):393-397.
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