 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 |
|---|
| 1991 | 0 | 3 | 3 | | 1995 | 0 | 1 | 1 | | 2003 | 1 | 0 | 1 | | 2004 | 5 | 1 | 6 | | 2005 | 1 | 4 | 5 | | 2006 | 1 | 1 | 2 | | 2007 | 1 | 1 | 2 | | 2008 | 5 | 0 | 5 | | 2011 | 1 | 1 | 2 | | 2012 | 1 | 1 | 2 | | 2013 | 5 | 2 | 7 | | 2014 | 4 | 0 | 4 | | 2015 | 4 | 2 | 6 | | 2016 | 1 | 0 | 1 | | 2017 | 5 | 0 | 5 | | 2018 | 4 | 0 | 4 | | 2019 | 2 | 1 | 3 | | 2020 | 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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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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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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Schimpf B, Deanda K, Severenuk DA, Montgomery TM, Cooley GD, Kowalski RG, Vela-Duarte D, Jones WJ. Integration of Real-Time Electronic Health Records and Wireless Technology in a Mobile Stroke Unit. J Stroke Cerebrovasc Dis. 2019 Sep; 28(9):2530-2536.
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Kamitaki BK, Yum A, Lee J, Rishty S, Sivaraaman K, Esfahanizadeh A, Mani R, Wong S. Yield of conventional and automated seizure detection methods in the epilepsy monitoring unit. Seizure. 2019 Jul; 69:290-295.
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Culpepper WJ, Marrie RA, Langer-Gould A, Wallin MT, Campbell JD, Nelson LM, Kaye WE, Wagner L, Tremlett H, Chen LH, Leung S, Evans C, Yao S, LaRocca NG. Validation of an algorithm for identifying MS cases in administrative health claims datasets. Neurology. 2019 03 05; 92(10):e1016-e1028.
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Rajpurkar P, Irvin J, Ball RL, Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A, Langlotz CP, Patel BN, Yeom KW, Shpanskaya K, Blankenberg FG, Seekins J, Amrhein TJ, Mong DA, Halabi SS, Zucker EJ, Ng AY, Lungren MP. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Med. 2018 11; 15(11):e1002686.
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Joshi CN, Chapman KE, Bear JJ, Wilson SB, Walleigh DJ, Scheuer ML. Semiautomated Spike Detection Software Persyst 13 Is Noninferior to Human Readers When Calculating the Spike-Wave Index in Electrical Status Epilepticus in Sleep. J Clin Neurophysiol. 2018 Sep; 35(5):370-374.
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Del Rosario F, Farahi JM, Drendel J, Buntinx-Krieg T, Caravaglio J, Domozych R, Chapman S, Braunberger T, Dellavalle RP, Norris DA, Fathi R, Alkousakis T. Performance of a computer-aided digital dermoscopic image analyzer for melanoma detection in 1,076 pigmented skin lesion biopsies. J Am Acad Dermatol. 2018 05; 78(5):927-934.e6.
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Brown FC, O'Connor BP, Vitelli KM, Heinly M, Rommel GC, Davis RN. Comparison of the Computer and Hand Administered Versions of the Brown Location Test (BLT). Arch Clin Neuropsychol. 2018 Feb 01; 33(1):47-56.
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