scholarly journals Deep learning-based facial image analysis in medical research: a systematic review protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e047549
Author(s):  
Zhaohui Su ◽  
Bin Liang ◽  
Feng Shi ◽  
J Gelfond ◽  
Sabina Šegalo ◽  
...  
Keyword(s):  
Systematic Review ◽  
Image Analysis ◽  
Deep Learning ◽  
Medical Research ◽  
Facial Image ◽  
Manual Search ◽  
Challenges And Opportunities ◽  
Ethical Approval ◽  
Meta Analyses ◽  
Facial Image Analysis

IntroductionDeep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people’s medical conditions. While positive findings are available, little is known about the state-of-the-art of deep learning-based facial image analysis in the medical context. For the consideration of patients’ welfare and the development of the practice, a timely understanding of the challenges and opportunities faced by research on deep-learning-based facial image analysis is needed. To address this gap, we aim to conduct a systematic review to identify the characteristics and effects of deep learning-based facial image analysis in medical research. Insights gained from this systematic review will provide a much-needed understanding of the characteristics, challenges, as well as opportunities in deep learning-based facial image analysis applied in the contexts of disease detection, diagnosis and prognosis.MethodsDatabases including PubMed, PsycINFO, CINAHL, IEEEXplore and Scopus will be searched for relevant studies published in English in September, 2021. Titles, abstracts and full-text articles will be screened to identify eligible articles. A manual search of the reference lists of the included articles will also be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was adopted to guide the systematic review process. Two reviewers will independently examine the citations and select studies for inclusion. Discrepancies will be resolved by group discussions till a consensus is reached. Data will be extracted based on the research objective and selection criteria adopted in this study.Ethics and disseminationAs the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations.PROSPERO registration numberCRD42020196473.

Color Cue in Facial Image Analysis

2006 ◽  
pp. 285-308
Author(s):  
Abdenour Hadid ◽  
Matti Pietikäinen ◽  
Birgitta Martinkauppi
Keyword(s):  
Image Analysis ◽  
Facial Image ◽  
Facial Image Analysis

scholarly journals Can physical testing be used to distinguish between migraine and cervicogenic headache sufferers? A protocol for a systematic review

BMJ Open ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. e031587 ◽  
Author(s):  
Ernesto Anarte ◽  
Gabriela Ferreira Carvalho ◽  
Annika Schwarz ◽  
Kerstin Luedtke ◽  
Deborah Falla
Keyword(s):  
Systematic Review ◽  
Differential Diagnosis ◽  
Diagnostic Accuracy ◽  
Meta Analysis ◽  
Cervicogenic Headache ◽  
Ethical Approval ◽  
Black Scale ◽  
Physical Tests ◽  
Meta Analyses ◽  
Asymptomatic Subjects

IntroductionDifferential diagnosis of migraine and cervicogenic headache (CGH) can be challenging given the large overlap of symptoms, commonly leading to misdiagnosis and ineffective treatment. In order to strengthen the differential diagnosis of headache, previous studies have evaluated the utility of physical tests to examine for musculoskeletal impairment, mainly in the cervical spine, which could be provoking or triggering headache. However, no systematic review has attempted to evaluate whether physical tests can differentiate CGH from migraine or both conditions from asymptomatic subjects.Methods/analysisA systematic review protocol has been designed and is reported in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P). A sensitive topic-based search strategy is planned which will include databases, hand searching of key journals and consultation of relevant leading authors in this field. Terms and keywords will be selected after discussion and agreement. Two independent reviewers will perform the search and select studies according to inclusion and exclusion criteria, including any cohort or observational studies evaluating the topic of this review; a third reviewer will confirm accuracy. A narrative synthesis will be developed for all included studies and, if possible, a meta-analysis will be conducted. The overall quality of the evidence will be assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklist for diagnostic accuracy studies and the Downs and Black scale for those studies where the QUADAS-2 checklist cannot be applied.Ethics and disseminationEthical approval is not required since no patient information will be collected. The results will provide a deeper understanding about the possibility of using physical tests to differentiate cervicogenic headache from migraine and from asymptomatic subjects, which has direct relevance for clinicians managing people with headache. The results will be published in a peer-reviewed journal and presented at scientific conferences.PROSPERO registration numberCRD42019135269.

Utilization of Facial Image Analysis Technology for Blink Detection

2018 ◽  
Vol 44 ◽  
pp. S297-S301
Author(s):  
Momoko Kitazawa ◽  
Michitaka Yoshimura ◽  
Kuo-Ching Liang ◽  
Satoshi Wada ◽  
Masaru Mimura ◽  
...  
Keyword(s):  
Image Analysis ◽  
Facial Image ◽  
Blink Detection ◽  
Facial Image Analysis

scholarly journals Particulate Production and Composite Dust during Routine Dental Procedures. A Systematic Review with Meta-Analyses

Materials ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2513 ◽  
Author(s):  
Anna Iliadi ◽  
Despina Koletsi ◽  
Theodore Eliades ◽  
George Eliades
Keyword(s):  
Systematic Review ◽  
Risk Of Bias ◽  
P Value ◽  
Dental Practice ◽  
Qualitative Synthesis ◽  
Eligibility Criteria ◽  
Manual Search ◽  
Dust Generation ◽  
Dental Procedures ◽  
Meta Analyses

Composite dust generation is most likely a continuous and daily procedure in dental practice settings. The aim of this systematic review was to identify, compile and evaluate existing evidence on interventions and composite material properties related to the production of aerosolized dust during routine dental procedures. Seven electronic databases were searched, with no limits, supplemented by a manual search, on 27 April 2020 for published and unpublished research. Eligibility criteria comprised of studies of any design, describing composite dust production related to the implementation of any procedure in dental practice. Study selection, data extraction and risk of bias (RoB) assessment was undertaken independently either in duplicate, or confirmed by a second reviewer. Random effects meta-analyses of standardized mean differences (SMD) with associated 95% confidence intervals (CIs) were employed where applicable. A total of 375 articles were initially identified, resulting in 13 articles being included in the qualitative synthesis, of which 5 contributed to meta-analyses overall. Risk of bias recordings ranged between low and high, pertaining to unclear/raising some concerns, in most cases. All types of composites, irrespective of the filler particles, released significant amounts of nano-sized particles after being ground, with potentially disruptive respiratory effects. Evidence supported increased % distribution of particles < 100 nm for nanocomposite Filtek Supreme XTE compared to both conventional hybrid Z100MP (SMD: 1.96, 95% CI: 0.85, 3.07; p-value; 0.001) and nano- hybrid Tetric EvoCeram (SMD: 1.62, 95% CI: 0.56, 2.68; p-value: 0.003). For cytotoxicity considerations of generated aerosolized particles, both nanocomposites Filtek Supreme XTE and nanohybrid GradiO revealed negative effects on bronchial epithelial cell viability, as represented by % formazan reduction at 330–400 μg/mL for 24 hours, with no recorded differences between them (SMD: 0.19; 95% CI: −0.17, 0.55; p-value: 0.30). Effective and more rigorous management of dental procedures potentially liable to the generation of considerable amounts of aerosolized composite dust should be prioritized in contemporary dental practice. In essence, protective measures for the clinician and the practices’ personnel should also be systematically promoted and additional interventions may be considered in view of the existing evidence.

scholarly journals Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review

Diagnostics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 29 ◽  
Author(s):  
Lea Pehrson ◽  
Michael Nielsen ◽  
Carsten Ammitzbøl Lauridsen
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Deep Learning ◽  
Machine Learning Algorithms ◽  
Ct Scans ◽  
Lung Nodules ◽  
Original Research ◽  
Feature Based ◽  
High Level ◽  
Meta Analyses

The aim of this study was to provide an overview of the literature available on machine learning (ML) algorithms applied to the Lung Image Database Consortium Image Collection (LIDC-IDRI) database as a tool for the optimization of detecting lung nodules in thoracic CT scans. This systematic review was compiled according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Only original research articles concerning algorithms applied to the LIDC-IDRI database were included. The initial search yielded 1972 publications after removing duplicates, and 41 of these articles were included in this study. The articles were divided into two subcategories describing their overall architecture. The majority of feature-based algorithms achieved an accuracy >90% compared to the deep learning (DL) algorithms that achieved an accuracy in the range of 82.2%–97.6%. In conclusion, ML and DL algorithms are able to detect lung nodules with a high level of accuracy, sensitivity, and specificity using ML, when applied to an annotated archive of CT scans of the lung. However, there is no consensus on the method applied to determine the efficiency of ML algorithms.

scholarly journals Effect of repetitive transcranial magnetic stimulation (rTMS) for insomnia: a protocol for a systematic review

BMJ Open ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. e029206 ◽  
Author(s):  
Yu He ◽  
Nianyi Sun ◽  
Zhiqiang Wang ◽  
Wenchen Zou
Keyword(s):  
Systematic Review ◽  
Transcranial Magnetic Stimulation ◽  
Magnetic Stimulation ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Data Extraction ◽  
Meta Analysis ◽  
Bibliographic Databases ◽  
Manual Search ◽  
Ethical Approval ◽  
Randomised Controlled

IntroductionRepetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation approach, might be a promising technique in the management of insomnia. A systematic review of the available literature on this topic is warranted. The systematic review described in this protocol aims to investigate the efficacy of rTMS as a physical therapy in patients with insomnia.Methods and analysisThis protocol was developed in accordance with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. We will retrieve relevant literatures across the following electronic bibliographic databases: CENTRAL, PubMed, EMBASE, PsycINFO, CINAHL, PEDro, CBM, CNKI, WANFANG and VIP. A manual search of the reference lists of all relevant articles will be performed for any additional studies. We will include randomised controlled trials published in English and Chinese examining efficacy of rTMS on patients with insomnia. Two reviewers will independently complete the article selection, data extraction and rating. PEDro scale will be used to assess the methodological quality of the included studies. Narrative and quantitative synthesis will be done accordingly.Ethics and disseminationEthical approval will not be required for this review. The results of this review will be disseminated in a peer-review journal.PROSPERO registration numberCRD42018115033.

scholarly journals How defensive medicine is defined and understood in European medical literature: protocol for a systematic review

BMJ Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. e034300
Author(s):  
Nathalie Baungaard ◽  
Pia Skovvang ◽  
Elisabeth Assing Hvidt ◽  
Helle Gerbild ◽  
Merethe Kirstine Andersen ◽  
...  
Keyword(s):  
Systematic Review ◽  
Medical Research ◽  
Systematic Reviews ◽  
Research Literature ◽  
Defensive Medicine ◽  
Primary Data ◽  
The Us ◽  
Registration Number ◽  
The Usa ◽  
Meta Analyses

IntroductionThe term defensive medicine, referring to actions motivated primarily by litigious concerns, originates from the USA and has been used in medical research literature since the late 1960s. Differences in medical legal systems between the US and most European countries with no tort legislation raise the question whether the US definition of defensive medicine holds true in Europe.AimTo present the protocol of a systematic review investigating variations in definitions and understandings of the term ‘defensive medicine’ in European research articles.Methods and analysisIn concordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic review of all medical research literature that investigate defensive medicine will be performed by two independent reviewers. The databases PubMed, Embase and Cochrane will be systematically searched on the basis of predetermined criteria. Data from all included European studies will systematically be extracted including the studies’ definitions and understandings of defensive medicine, especially the motives for doing medical actions that the study regards as ‘defensive’.Ethics and disseminationNo ethics clearance is required as no primary data will be collected. The results of the systematic review will be published in a peer-reviewed, international journal.PROSPERO registration numberThis review has been submitted to International Prospective Register of Systematic Reviews (PROSPERO) and is awaiting registration.

scholarly journals Systematic review finds that study data not published in full text articles have unclear impact on meta-analyses results in medical research

PLoS ONE ◽  
2017 ◽  
Vol 12 (4) ◽  
pp. e0176210 ◽  
Author(s):  
Christine M. Schmucker ◽  
Anette Blümle ◽  
Lisa K. Schell ◽  
Guido Schwarzer ◽  
Patrick Oeller ◽  
...  
Keyword(s):  
Systematic Review ◽  
Medical Research ◽  
Full Text ◽  
Study Data ◽  
Meta Analyses
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