Signal Processing, Computer-Assisted
"Signal Processing, 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.
Computer-assisted processing of electric, ultrasonic, or electronic signals to interpret function and activity.
| Descriptor ID |
D012815
|
| MeSH Number(s) |
L01.224.800
|
| Concept/Terms |
Signal Interpretation, Computer-Assisted- Signal Interpretation, Computer-Assisted
- Computer-Assisted Signal Interpretation
- Computer-Assisted Signal Interpretations
- Interpretation, Computer-Assisted Signal
- Interpretations, Computer-Assisted Signal
- Signal Interpretation, Computer Assisted
- Signal Interpretations, Computer-Assisted
|
Below are MeSH descriptors whose meaning is more general than "Signal Processing, Computer-Assisted".
Below are MeSH descriptors whose meaning is more specific than "Signal Processing, Computer-Assisted".
This graph shows the total number of publications written about "Signal Processing, Computer-Assisted" by people in this website by year, and whether "Signal Processing, 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 |
|---|
| 2002 | 0 | 1 | 1 |
| 2003 | 0 | 4 | 4 |
| 2004 | 2 | 2 | 4 |
| 2005 | 2 | 0 | 2 |
| 2006 | 3 | 4 | 7 |
| 2007 | 4 | 2 | 6 |
| 2008 | 2 | 1 | 3 |
| 2009 | 3 | 2 | 5 |
| 2010 | 2 | 0 | 2 |
| 2011 | 4 | 0 | 4 |
| 2012 | 1 | 0 | 1 |
| 2013 | 1 | 1 | 2 |
| 2014 | 0 | 3 | 3 |
| 2015 | 0 | 4 | 4 |
| 2016 | 1 | 1 | 2 |
| 2017 | 1 | 3 | 4 |
| 2018 | 0 | 2 | 2 |
| 2019 | 0 | 1 | 1 |
| 2020 | 0 | 2 | 2 |
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Below are the most recent publications written about "Signal Processing, Computer-Assisted" by people in Profiles.
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Ratnagiri MV, Ryan L, Strang A, Heinle R, Rahman T, Shaffer TH. Machine learning for automatic identification of thoracoabdominal asynchrony in children. Pediatr Res. 2021 04; 89(5):1232-1238.
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Frisch D, Oesterlein TG, Unger LA, Lenis G, Wakili R, Schmitt C, Luik A, Dossel O, Loewe A. Mapping and Removing the Ventricular Far Field Component in Unipolar Atrial Electrograms. IEEE Trans Biomed Eng. 2020 10; 67(10):2905-2915.
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Bini SA, Shah RF, Bendich I, Patterson JT, Hwang KM, Zaid MB. Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial. J Arthroplasty. 2019 10; 34(10):2242-2247.
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Li H, Nikam R, Kandula V, Chow HM, Choudhary AK. Comparison of NODDI and spherical mean signal for measuring intra-neurite volume fraction. Magn Reson Imaging. 2019 04; 57:151-155.
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Behere S, Baffa JM, Penfil S, Slamon N. Real-World Evaluation of the Eko Electronic Teleauscultation System. Pediatr Cardiol. 2019 Jan; 40(1):154-160.
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Maas E, Mailend ML. Fricative Contrast and Coarticulation in Children With and Without Speech Sound Disorders. Am J Speech Lang Pathol. 2017 Jun 22; 26(2S):649-663.
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Wang B, Zhang LI, Cong P, Chu H, Liu Y, Liu J, Surkis W, Xia Y. A New Formula for Estimating the True QT Interval in Left Bundle Branch Block. J Cardiovasc Electrophysiol. 2017 Jun; 28(6):684-689.
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Fosi T, Werner K, Boyd SG, De Haan M, Scott RC, Neville BG. Auditory processing following infantile spasms: An event-related potential study. Epilepsia. 2017 05; 58(5):872-881.
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Ngo L, Sperling MR, Skidmore C, Mintzer S, Nei M. Absolute spike frequency as a predictor of surgical outcome in temporal lobe epilepsy. Seizure. 2017 Apr; 47:83-86.
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Desebbe O, Joosten A, Suehiro K, Lahham S, Essiet M, Rinehart J, Cannesson M. A Novel Mobile Phone Application for Pulse Pressure Variation Monitoring Based on Feature Extraction Technology: A Method Comparison Study in a Simulated Environment. Anesth Analg. 2016 07; 123(1):105-13.