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Journal of Ambient Intelligence and... 2023The success of deep learning over the traditional machine learning techniques in handling artificial intelligence application tasks such as image processing, computer...
UNLABELLED
The success of deep learning over the traditional machine learning techniques in handling artificial intelligence application tasks such as image processing, computer vision, object detection, speech recognition, medical imaging and so on, has made deep learning the buzz word that dominates Artificial Intelligence applications. From the last decade, the applications of deep learning in physiological signals such as electrocardiogram (ECG) have attracted a good number of research. However, previous surveys have not been able to provide a systematic comprehensive review including biometric ECG based systems of the applications of deep learning in ECG with respect to domain of applications. To address this gap, we conducted a systematic literature review on the applications of deep learning in ECG including biometric ECG based systems. The study analyzed systematically, 150 primary studies with evidence of the application of deep learning in ECG. The study shows that the applications of deep learning in ECG have been applied in different domains. We presented a new taxonomy of the domains of application of the deep learning in ECG. The paper also presented discussions on biometric ECG based systems and meta-data analysis of the studies based on the domain, area, task, deep learning models, dataset sources and preprocessing methods. Challenges and potential research opportunities were highlighted to enable novel research. We believe that this study will be useful to both new researchers and expert researchers who are seeking to add knowledge to the already existing body of knowledge in ECG signal processing using deep learning algorithm.
SUPPLEMENTARY INFORMATION
The online version contains supplementary material available at 10.1007/s12652-022-03868-z.
PubMed: 35821879
DOI: 10.1007/s12652-022-03868-z -
JMIR MHealth and UHealth Jun 2020Comprehensive exams such as the Dean-Woodcock Neuropsychological Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia Examination are the...
BACKGROUND
Comprehensive exams such as the Dean-Woodcock Neuropsychological Assessment System, the Global Deterioration Scale, and the Boston Diagnostic Aphasia Examination are the gold standard for doctors and clinicians in the preliminary assessment and monitoring of neurocognitive function in conditions such as neurodegenerative diseases and acquired brain injuries (ABIs). In recent years, there has been an increased focus on implementing these exams on mobile devices to benefit from their configurable built-in sensors, in addition to scoring, interpretation, and storage capabilities. As smartphones become more accepted in health care among both users and clinicians, the ability to use device information (eg, device position, screen interactions, and app usage) for subject monitoring also increases. Sensor-based assessments (eg, functional gait using a mobile device's accelerometer and/or gyroscope or collection of speech samples using recordings from the device's microphone) include the potential for enhanced information for diagnoses of neurological conditions; mapping the development of these conditions over time; and monitoring efficient, evidence-based rehabilitation programs.
OBJECTIVE
This paper provides an overview of neurocognitive conditions and relevant functions of interest, analysis of recent results using smartphone and/or tablet built-in sensor information for the assessment of these different neurocognitive conditions, and how human-device interactions and the assessment and monitoring of these neurocognitive functions can be enhanced for both the patient and health care provider.
METHODS
This survey presents a review of current mobile technological capabilities to enhance the assessment of various neurocognitive conditions, including both neurodegenerative diseases and ABIs. It explores how device features can be configured for assessments as well as the enhanced capability and data monitoring that will arise due to the addition of these features. It also recognizes the challenges that will be apparent with the transfer of these current assessments to mobile devices.
RESULTS
Built-in sensor information on mobile devices is found to provide information that can enhance neurocognitive assessment and monitoring across all functional categories. Configurations of positional sensors (eg, accelerometer, gyroscope, and GPS), media sensors (eg, microphone and camera), inherent sensors (eg, device timer), and participatory user-device interactions (eg, screen interactions, metadata input, app usage, and device lock and unlock) are all helpful for assessing these functions for the purposes of training, monitoring, diagnosis, or rehabilitation.
CONCLUSIONS
This survey discusses some of the many opportunities and challenges of implementing configured built-in sensors on mobile devices to enhance assessments and monitoring of neurocognitive functions as well as disease progression across neurodegenerative and acquired neurological conditions.
Topics: Computers, Handheld; Delivery of Health Care; Humans; Smartphone; Surveys and Questionnaires
PubMed: 32442150
DOI: 10.2196/15517 -
Theoretical Biology & Medical Modelling Jan 2013During the very early stage of the 2009 pandemic, mass chemoprophylaxis was implemented as part of containment measure. The purposes of the present study were to... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
During the very early stage of the 2009 pandemic, mass chemoprophylaxis was implemented as part of containment measure. The purposes of the present study were to systematically review the retrospective studies that investigated the effectiveness of antiviral prophylaxis during the 2009 pandemic, and to explicitly estimate the effectiveness by employing a mathematical model.
METHODS
A systematic review identified 17 articles that clearly defined the cases and identified exposed individuals based on contact tracing. Analysing a specific school-driven outbreak, we estimated the effectiveness of antiviral prophylaxis using a renewal equation model. Other parameters, including the reproduction number and the effectiveness of antiviral treatment and school closure, were jointly estimated.
RESULTS
Based on the systematic review, median secondary infection risks (SIRs) among exposed individuals with and without prophylaxis were estimated at 2.1% (quartile: 0, 12.2) and 16.6% (quartile: 8.4, 32.4), respectively. A very high heterogeneity in the SIR was identified with an estimated I2 statistic at 71.8%. From the outbreak data in Madagascar, the effectiveness of mass chemoprophylaxis in reducing secondary transmissions was estimated to range from 92.8% to 95.4% according to different model assumptions and likelihood functions, not varying substantially as compared to other parameters.
CONCLUSIONS
Only based on the meta-analysis of retrospective studies with different study designs and exposure settings, it was not feasible to estimate the effectiveness of antiviral prophylaxis in reducing transmission. However, modelling analysis of a single outbreak successfully yielded an estimate of the effectiveness that appeared to be robust to model assumptions. Future studies should fill the data gap that has existed in observational studies and allow mathematical models to be used for the analysis of meta-data.
Topics: Antiviral Agents; Coinfection; Contact Tracing; Disease Outbreaks; Humans; Influenza A Virus, H1N1 Subtype; Influenza, Human; Madagascar; Models, Biological; Post-Exposure Prophylaxis; Risk Factors; Treatment Outcome
PubMed: 23324555
DOI: 10.1186/1742-4682-10-4 -
Stroke Research and Treatment 2021This review aimed at figuring out the risk factors of uncontrolled hypertension in stroke. (Review)
Review
OBJECTIVE
This review aimed at figuring out the risk factors of uncontrolled hypertension in stroke.
METHOD
This study systematically analyzed the hypertension risk factors available in the ProQuest, EBSCO, and PubMed databases published between 2010 and December 2019. The risk factors' pooled odds ratio (POR) included in this research was calculated using both fixed and random-effect models. The meta-data analysis was processed using the Review Manager 5.3 (Rev Man 5.3).
RESULT
Of 1868 articles, seven studies were included in this review searched using specific keywords. Based on the analysis results, there were 7 risk factors of uncontrolled hypertension in stroke: medication nonadherence (POR = 2.23 [95% CI 1.71-2.89], = 0.342; = 6.7%), use of antihypertensive drugs (POR = 1.13 [95% CI 1.19-1.59, = 0.001; = 90.9%), stage of hypertension (POR = 1.14 [95% CI 1.02-1.27], = <0.001; = 97.1%), diabetes mellitus (POR = 0.71 [95% CI 0.52-0.99], = <0.001; = 96.5%), atrial fibrillation (POR = 1.74 [95% CI 1.48-2.04)], = <0.001; = 93.1%), triglycerides (POR = 1.47 [95% CI 1.23-1.75], = 0.879; = 0%), and age (POR = 1.03 [95% CI 0.89-1.18], = <0.001; = 97.5%]. There were no bias publications among studies. Medication nonadherence and triglycerides had homogeneous variations, while the others had heterogeneous variations.
CONCLUSION
Medication nonadherence, triglycerides, stage of hypertension, atrial fibrillation, and use of antihypertensive drugs significantly affect the uncontrolled hypertension in stroke.
PubMed: 33680423
DOI: 10.1155/2021/6683256 -
Journal of Translational Medicine Jul 2019Drug development is currently hampered by high attrition rates; many developed treatments fail during clinical testing. Part of the attrition may be due to low...
BACKGROUND
Drug development is currently hampered by high attrition rates; many developed treatments fail during clinical testing. Part of the attrition may be due to low animal-to-human translational success rates; so-called "translational failure". As far as we know, no systematic overview of published translational success rates exists.
SYSTEMATIC SCOPING REVIEW
The following research question was examined: "What is the observed range of the animal-to-human translational success (and failure) rates within the currently available empirical evidence?". We searched PubMed and Embase on 16 October 2017. We included reviews and all other types of "umbrella"-studies of meta-data quantitatively comparing the translational results of studies including at least two species with one being human. We supplemented our database searches with additional strategies. All abstracts and full-text papers were screened by two independent reviewers. Our scoping review comprises 121 references, with various units of measurement: compound or intervention (k = 104), study/experiment (k = 10), and symptom or event (k = 7). Diagnostic statistics corresponded with binary and continuous definitions of successful translation. Binary definitions comprise percentages below twofold error, percentages accurately predicted, and predictive values. Quantitative definitions comprise correlation/regression (r) and meta-analyses (percentage overlap of 95% confidence intervals). Translational success rates ranged from 0 to 100%.
CONCLUSION
The wide range of translational success rates observed in our study might indicate that translational success is unpredictable; i.e. it might be unclear upfront if the results of primary animal studies will contribute to translational knowledge. However, the risk of bias of the included studies was high, and much of the included evidence is old, while newer models have become available. Therefore, the reliability of the cumulative evidence from current papers on this topic is insufficient. Further in-depth "umbrella"-studies of translational success rates are still warranted. These are needed to evaluate the probabilistic evidence for predictivity of animal studies for the human situation more reliably, and to determine which factors affect this process.
Topics: Animals; Humans; Periodicals as Topic; Publication Bias; Risk; Translational Research, Biomedical
PubMed: 31307492
DOI: 10.1186/s12967-019-1976-2 -
ANZ Journal of Surgery Sep 2022Recurrent Testicular Torsion (RTT) is a rarely reported event after previous testicular torsion (TT) repair. Both conditions have similar signs and symptoms. Various... (Review)
Review
BACKGROUND
Recurrent Testicular Torsion (RTT) is a rarely reported event after previous testicular torsion (TT) repair. Both conditions have similar signs and symptoms. Various techniques have been attempted to reduce the incidence of retorsion. This review assesses the presentation, diagnosis, risk factors, management and outcomes associated with RTT.
METHODS
After PROSPERO Registration (CRD42021258997), a systematic search of PubMed, Google Scholar, Embase, Scopus, Web of Science, Cochrane Database of Systematic Reviews, Global Index Medicus and Cumulative Index to Nursing and Allied Health Literature (CIANHL) was performed using specific search terms. Study metadata including patient demographics, orchidopexy techniques, RTT rates and RTT timing were extracted.
RESULTS
Twenty-six articles, comprising 12 case series and 14 case reports, with a total of 46 patients were included. Overall, the median (IQR) age of the pooled cohort was 18 (15-26) years, the median (IQR) time to presentation was 6 (3-36) hours from the onset of testicular pain. The most common presenting features were testicular pain (100%), testicular swelling (60.9%) and a high riding testicle (34.8%). The left testicle was most commonly affected (63.0%), RTT was on the ipsilateral side in relation to the primary episode of TT in 52.2% of cases, the median (IQR) interval between torsion and retorsion events was 4 (1.3-10.0) years, non-absorbable sutures were the most common suture material used during orchidopexy after RTT (88.9%).
CONCLUSION
RTT is a rare presentation to the Emergency Department. Even with a prior history of TT, RTT should be considered in patients presenting with classic symptoms.
Topics: Adolescent; Adult; Humans; Male; Orchiopexy; Pain; Retrospective Studies; Spermatic Cord Torsion; Testicular Diseases; Young Adult
PubMed: 35257473
DOI: 10.1111/ans.17592 -
Epidemiology (Cambridge, Mass.) Nov 2018Seasonality in tuberculosis incidence has been widely observed across countries and populations; however, its drivers are poorly understood. We conducted a systematic...
BACKGROUND
Seasonality in tuberculosis incidence has been widely observed across countries and populations; however, its drivers are poorly understood. We conducted a systematic review of studies reporting seasonal patterns in tuberculosis to identify demographic and ecologic factors associated with timing and magnitude of seasonal variation.
METHODS
We identified studies reporting seasonal variation in tuberculosis incidence through PubMed and EMBASE and extracted incidence data and population metadata. We described key factors relating to seasonality and, when data permitted, quantified seasonal variation and its association with metadata. We developed a dynamic tuberculosis natural history and transmission model incorporating seasonal differences in disease progression and/or transmission rates to examine magnitude of variation required to produce observed seasonality in incidence.
RESULTS
Fifty-seven studies met inclusion criteria. In the majority of studies (n=49), tuberculosis incidence peaked in spring or summer and reached a trough in late fall or winter. A standardized seasonal amplitude was calculated for 34 of the studies, resulting in a mean of 17.1% (range: 2.7-85.5%) after weighting by sample size. Across multiple studies, stronger seasonality was associated with younger patients, extrapulmonary disease, and latitudes farther from the Equator. The mathematical model was generally able to reproduce observed levels of seasonal case variation; however, substantial variation in transmission or disease progression risk was required to replicate several extreme values.
CONCLUSIONS
We observed seasonal variation in tuberculosis, with consistent peaks occurring in spring, across countries with varying tuberculosis burden. Future research is needed to explore and quantify potential gains from strategically conducting mass screening interventions in the spring.
Topics: Humans; Incidence; Models, Theoretical; Seasons; Tuberculosis, Pulmonary
PubMed: 29870427
DOI: 10.1097/EDE.0000000000000877 -
European Radiology Jul 2012To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of dementia.
METHODS
We systematically reviewed published brain image databanks (print literature and Internet) concerned with normal ageing brain structure.
RESULTS
From nine eligible databanks, there appeared to be 944 normal subjects aged ≥60 years. However, many subjects were in more than one databank and not all were fully representative of normal ageing clinical characteristics. Therefore, there were approximately 343 subjects aged ≥60 years with metadata representative of normal ageing, but only 98 subjects were openly accessible. No databank had the range of MR image sequences, e.g. T2*, fluid-attenuated inversion recovery (FLAIR), required to effectively characterise the features of brain ageing. No databank supported random subject retrieval; therefore, manual selection bias and errors may occur in studies that use these subjects as controls. Finally, no databank stored results from statistical analyses of its brain image and metadata that may be validated with analyses of further data.
CONCLUSION
Brain image databanks require open access, more subjects, metadata, MR image sequences, searchability and statistical results to improve understanding of normal ageing brain structure and diagnoses of dementia.
KEY POINTS
• We reviewed databanks with structural MR brain images of normal older people. • Among these nine databanks, 98 normal subjects ≥60 years were openly accessible. • None had all the required sequences, random subject retrieval or statistical results. • More access, subjects, sequences, metadata, searchability and results are needed. • These may improve understanding of normal brain ageing and diagnoses of dementia.
Topics: Adolescent; Adult; Age Distribution; Aged; Aged, 80 and over; Aging; Brain; Child; Child, Preschool; Databases, Factual; Female; Humans; Infant; Infant, Newborn; Magnetic Resonance Imaging; Male; Middle Aged; Radiology Information Systems; Reference Values; Reproducibility of Results; Sensitivity and Specificity; Young Adult
PubMed: 22354559
DOI: 10.1007/s00330-012-2392-7 -
JMIR Mental Health Aug 2016[This corrects the article DOI: 10.2196/mental.6061.].
[This corrects the article DOI: 10.2196/mental.6061.].
PubMed: 27559849
DOI: 10.2196/mental.6532 -
Frontiers in Artificial Intelligence 2024Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a...
BACKGROUND
Public health policy researchers face a persistent challenge in identifying and integrating relevant data, particularly in the context of the U.S. opioid crisis, where a comprehensive approach is crucial.
PURPOSE
To meet this new workforce demand health policy and health economics programs are increasingly introducing data analysis and data visualization skills. Such skills facilitate data integration and discovery by linking multiple resources. Common linking strategies include individual or aggregate level linking (e.g., patient identifiers) in primary clinical data and conceptual linking (e.g., healthcare workforce, state funding, burnout rates) in secondary data. Often, the combination of primary and secondary datasets is sought, requiring additional skills, for example, understanding metadata and constructing interlinkages.
METHODS
To help improve those skills, we developed a 2-step process using a scoping method to discover data and network visualization to interlink metadata. Results: We show how these new skills enable the discovery of relationships among data sources pertinent to public policy research related to the opioid overdose crisis and facilitate inquiry across heterogeneous data resources. In addition, our interactive network visualization introduces (1) a conceptual approach, drawing from recent systematic review studies and linked by the publications, and (2) an aggregate approach, constructed using publicly available datasets and linked through crosswalks.
CONCLUSIONS
These novel metadata visualization techniques can be used as a teaching tool or a discovery method and can also be extended to other public policy domains.
PubMed: 38646414
DOI: 10.3389/frai.2024.1208874