Keyword search (4,164 papers available)

"Accuracy" Keyword-tagged Publications:

Title Authors PubMed ID
1 Are MEDLINE searches sufficient for systematic reviews and meta-analyses of the diagnostic accuracy of depression screening tools? A review of meta-analyses Rice DB; Kloda LA; Levis B; Qi B; Kingsland E; Thombs BD; 27411746
LIBRARY
2 Reporting quality in abstracts of meta-analyses of depression screening tool accuracy: a review of systematic reviews and meta-analyses Rice DB; Kloda LA; Shrier I; Thombs BD; 27864250
LIBRARY
3 Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data Thölke P; Mantilla-Ramos YJ; Abdelhedi H; Maschke C; Dehgan A; Harel Y; Kemtur A; Mekki Berrada L; Sahraoui M; Young T; Bellemare Pépin A; El Khantour C; Landry M; Pascarella A; Hadid V; Combrisson E; O' Byrne J; Jerbi K; 37385392
IMAGING
4 How uncertainty affects information search among consumers: a curvilinear perspective He S; Rucker DD; 36471868
JMSB
5 Transparency and completeness of reporting of depression screening tool accuracy studies: A meta-research review of adherence to the Standards for Reporting of Diagnostic Accuracy Studies statement Nassar EL; Levis B; Neyer MA; Rice DB; Booij L; Benedetti A; Thombs BD; 36047034
PSYCHOLOGY
6 Sample size and precision of estimates in studies of depression screening tool accuracy: A meta-research review of studies published in 2018-2021 Nassar EL; Levis B; Neyer MA; Rice DB; Booij L; Benedetti A; Thombs BD; 35362161
PSYCHOLOGY
7 Inclusion of currently diagnosed or treated individuals in studies of depression screening tool accuracy: a meta-research review of studies published in 2018-2021 Nassar EL; Levis B; Rice DB; Booij L; Benedetti A; Thombs BD; 35334411
PSYCHOLOGY
8 A Simulation Toolkit for Testing the Sensitivity and Accuracy of Corticometry Pipelines OmidYeganeh M; Khalili-Mahani N; Bermudez P; Ross A; Lepage C; Vincent RD; Jeon S; Lewis LB; Das S; Zijdenbos AP; Rioux P; Adalat R; Van Eede MC; Evans AC; 34381348
PERFORM
9 Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data Bhandari PM; Levis B; Neupane D; Patten SB; Shrier I; Thombs BD; Benedetti A; 33838273
CONCORDIA
10 Equivalency of the diagnostic accuracy of the PHQ-8 and PHQ-9: a systematic review and individual participant data meta-analysis Wu Y; Levis B; Riehm KE; Saadat N; Levis AW; Azar M; Rice DB; Boruff J; Cuijpers P; Gilbody S; Ioannidis JPA; Kloda LA; McMillan D; Patten SB; Shrier I; Ziegelstein RC; Akena DH; Arroll B; Ayalon L; Baradaran HR; Baron M; Bombardier CH; Butterworth P; Carter G; Chagas MH; Chan JCN; Cholera R; Conwell Y; de Man-van Ginkel JM; Fann JR; Fischer FH; Fung D; Gelaye B; Goodyear-Smith F; Greeno CG; Hall BJ; Harrison PA; Härter M; Hegerl U; Hides L; Hobfoll SE; Hudson M; Hyphantis T; Inagaki M; Jetté N; Khamseh ME; Kiely KM; Kwan Y; Lamers F; Liu SI; Lotrakul M; Loureiro SR; Löwe B; McGuire A; Mohd-Sidik S; Munhoz TN; Muramatsu K; Osório FL; Patel V; Pence BW; Persoons P; Picardi A; Reuter K; Rooney AG; Santos IS; Shaaban J; Sidebottom A; Simning A; Stafford L; Sung S; Tan PLL; Turner A; van Weert HC; White J; Whooley MA; Winkley K; Yamada M; Benedetti A; Thombs BD; 31298180
LIBRARY
11 Diagnostic accuracy of the Depression subscale of the Hospital Anxiety and Depression Scale (HADS-D) for detecting major depression: protocol for a systematic review and individual patient data meta-analyses. Thombs BD, Benedetti A, Kloda LA, Levis B, Azar M, Riehm KE, Saadat N, Cuijpers P, Gilbody S, Ioannidis JP, McMillan D, Patten SB, Shrier I, Steele RJ, Ziegelstein RC, Loiselle CG, Henry M, Ismail Z, Mitchell N, Tonelli M 27075844
LIBRARY
12 Gesture-based registration correction using a mobile augmented reality image-guided neurosurgery system. Léger É, Reyes J, Drouin S, Collins DL, Popa T, Kersten-Oertel M 30800320
PERFORM

 

Title:Gesture-based registration correction using a mobile augmented reality image-guided neurosurgery system.
Authors:Léger ÉReyes JDrouin SCollins DLPopa TKersten-Oertel M
Link:https://www.ncbi.nlm.nih.gov/pubmed/30800320?dopt=Abstract
DOI:10.1049/htl.2018.5063
Publication:Healthcare technology letters
Keywords:GPS-like guidanceaugmented realityaugmented reality neuronavigation systemsbiomedical MRIbrainbrainshiftcomputerised tomographygesture-based methodgesture-based registration correctionimage distortionimage registrationmanual registration correctionmedian registration RMS errormedical image processingmobile augmented reality image-guided neurosurgery systemmobile computingneurophysiologyobject trackingpatient-to-image alignment accuracypreoperative imagessize 3 51 mmsurgeonsurgerysurgical proceduresurgical toolssurgical workflowtablet touchscreen capabilitytracking errors
PMID:30800320 Category:Healthc Technol Lett Date Added:2019-04-15
Dept Affiliation: PERFORM
1 Department of Computer Science and Software Engineering, Concordia University, Montréal, Canada.
2 Department of Biomedical Engineering, McGill University, Montréal, Canada.
3 PERFORM Centre, Concordia University, Montréal, Canada.

Description:

Gesture-based registration correction using a mobile augmented reality image-guided neurosurgery system.

Healthc Technol Lett. 2018 Oct;5(5):137-142

Authors: Léger É, Reyes J, Drouin S, Collins DL, Popa T, Kersten-Oertel M

Abstract

In image-guided neurosurgery, a registration between the patient and their pre-operative images and the tracking of surgical tools enables GPS-like guidance to the surgeon. However, factors such as brainshift, image distortion, and registration error cause the patient-to-image alignment accuracy to degrade throughout the surgical procedure no longer providing accurate guidance. The authors present a gesture-based method for manual registration correction to extend the usage of augmented reality (AR) neuronavigation systems. The authors' method, which makes use of the touchscreen capabilities of a tablet on which the AR navigation view is presented, enables surgeons to compensate for the effects of brainshift, misregistration, or tracking errors. They tested their system in a laboratory user study with ten subjects and found that they were able to achieve a median registration RMS error of 3.51 mm on landmarks around the craniotomy of interest. This is comparable to the level of accuracy attainable with previously proposed methods and currently available commercial systems while being simpler and quicker to use. The method could enable surgeons to quickly and easily compensate for most of the observed shift. Further advantages of their method include its ease of use, its small impact on the surgical workflow and its small-time requirement.

PMID: 30800320 [PubMed]





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