Displaying publications 121 - 140 of 365 in total

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  1. Fulltext Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA)
    Salimi N, Loh KH, Kaur Dhillon S, Chong VC
    PeerJ, 2016;4:e1664.
    PMID: 26925315 DOI: 10.7717/peerj.1664
    Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.
    Matched MeSH terms: Data Collection
  2. Development of Low-Cost Microcontroller-Based Interface for Data Acquisition and Control of Microbioreactor Operation
    Husain AR, Hadad Y, Zainal Alam MN
    J Lab Autom, 2016 Oct;21(5):660-70.
    PMID: 26185253 DOI: 10.1177/2211068215594770
    This article presents the development of a low-cost microcontroller-based interface for a microbioreactor operation. An Arduino MEGA 2560 board with 54 digital input/outputs, including 15 pulse-width-modulation outputs, has been chosen to perform the acquisition and control of the microbioreactor. The microbioreactor (volume = 800 µL) was made of poly(dimethylsiloxane) and poly(methylmethacrylate) polymers. The reactor was built to be equipped with sensors and actuators for the control of reactor temperature and the mixing speed. The article discusses the circuit of the microcontroller-based platform, describes the signal conditioning steps, and evaluates the capacity of the proposed low-cost microcontroller-based interface in terms of control accuracy and system responses. It is demonstrated that the proposed microcontroller-based platform is able to operate parallel microbioreactor operation with satisfactory performances. Control accuracy at a deviation less than 5% of the set-point values and responses in the range of few seconds have been recorded.
    Matched MeSH terms: Data Collection
  3. Is input on Complementary and Alternative Medicine (CAM) necessary in our medical curriculum? A perspective from a survey on medical practitioners
    Nabilla AS, Safura J, Karina R, Noran H, Norizan M, Sabariah M, et al.
    Med J Malaysia, 2002 Dec;57 Suppl E:37-43.
    PMID: 12733192
    A cross-sectional study was carried out through a postal survey of a random sample of registered medical practitioners in Malaysia to explore the pursuit and practice of CAM among them. A response rate of 42% was acquired. 27.1% of the medical practitioners are currently using CAM on themselves or their own families and 22.2% actually have referred patients to CAM practitioners. Analysis showed that only 14.9% of the medical practitioners who responded were exposed to CAM during their undergraduate days. Out of 28 respondents graduated from USM, 15 (53.6%) were exposed while out of the 80 graduates of UM, only 6 (7.5%) were exposed and out of 58 respondents graduates of UKM, only 5 (8.6%) were exposed to CAM during their undergraduate teaching. These differences are statistically different (p < 0.001). Analysis also showed that more (72.6%) medical practitioners are for having training in CAM during the medical undergraduate studies. Only 9.1% of the respondents have attended any training in CAM post graduation and 36.8% would like further training on CAM postgraduate and would pay for it. The findings illustrate the need for training in CAM in medical undergraduate education especially in this new age where alternative therapy is in demand by the consumers.
    Matched MeSH terms: Data Collection
  4. Mammographic image quality and exposure in South East Asia
    Ng KH, DeWerd LA, Schmidt RC
    Australas Phys Eng Sci Med, 2000 Dec;23(4):135-7.
    PMID: 11376538
    Generally there is a significant delay before optimized performance of mammography is fully realized in the developing countries. To evaluate the status of mammographic performance, a survey of mammographic image quality and exposure was performed in nine hospitals from four selected South East Asian countries. The entrance exposure on the surface of the American College of Radiology (ACR) mammographic phantom (ACR-RMI model 156) was made using both thermoluminescent dosimeters (TLDs) and an ionization chamber. The TLDs were mailed from the University of Wisconsin Radiation Calibration Laboratory (UWRCL) to the cooperating hospitals. The surveyed hospitals processed the images and returned them to the UWRCL for subsequent evaluation of the image quality of the mammographic phantom. Machine-specific data, technique factors and sensitometric data were also obtained. At 28 kVp, the mean entrance exposure is 0.91 R (0.46 to 2.6 R), mean glandular dose is 1.61 mGy (0.90 to 4.15 mGy), mean optical density is 1.37 (0.66 to 2.30), mean total phantom image score is 9.1(4-12). Only three of the nine hospitals tested achieved an acceptable score above the minimum 10. Results for 25 and 30 kVp showed similar trend. The variation between the ion chamber measurements and TLD measurements ranged from 4 to 24%. There is a wide variation in the image quality and entrance exposure among hospitals in South East Asia. There is a need for a quality assurance program. The factors that cause low score in the phantom images must be corrected. Calibration and the use of appropriate ionization chambers for mammography is important.
    Matched MeSH terms: Data Collection
  5. Fulltext How good are doctors as drug prescribers?
    Rahman AR, Noor AR, Hassan Y
    Med J Malaysia, 1994 Dec;49(4):364-8.
    PMID: 7674972
    The training of doctors in therapeutics has created interesting discussions internationally. A survey of senior hospital pharmacists currently practising throughout West Malaysia was embarked on during a recent postgraduate seminar. About sixty per cent said prescribing errors were common amongst doctors. Sixteen per cent of the prescribing errors were potentially serious. Most of the time errors were due to carelessness, lack of knowledge on drug action or a combination of both. Nearly 35% of prescribing errors were not acknowledged by doctors. Most doctors did not give reasons for not acknowledging pharmacists' intervention. About half (46.5%) of the respondents thought that doctors were not adequately trained in the use of drugs.
    Matched MeSH terms: Data Collection
  6. Fulltext Breeding of Aedes aegypti (L.) and Aedes albopictus (Skuse) in urban housing of Sibu town, Sarawak
    Chang MS, Jute N
    Southeast Asian J. Trop. Med. Public Health, 1994 Sep;25(3):543-8.
    PMID: 7777923
    An Aedes survey using various larval survey methods was conducted in 12 urban housing areas and 29 vacant lands in Sibu town proper. Aedes albopictus larvae were found in all areas surveyed while Aedes aegypti larvae were present in 10 localities and 4 vacant lands. There were no significant difference in the house index, breteau and larval density index of these two Aedes (Stegomyia) species from the survey areas. The proportion of containers positive with Ae. aegypti and Ae. albopictus in area outside the house compound and near the house fencing were 3.2 times higher than outdoor compound. The indoor/outdoor breeding ratio for Ae. aegypti alone is 1.6:1. The most preferred breeding habitats outdoor were plastic cups and used tires while indoor habitats were ant traps and flower vases. In the vacant lands, the average number of larvae per containers was significantly higher than in houses and over 51% of the containers inspected were positive. Shared breeding between Ae. aegypti and Ae. albopictus larvae accounted for 9% in house surveys and 4.5% in vacant land survey. The use of various methods in Aedes larval survey may provide essential information in the study of vector epidemiology in dengue and dengue hemorrhagic fever transmission.
    Matched MeSH terms: Data Collection
  7. Assessment of periodontal diseases in epidemiological investigations: a critical review
    Abdul-Kadir R
    Singapore Dent J, 1989 Dec;14(1):6-12.
    PMID: 2487478
    Like dental caries, epidemiological assessment of periodontal disease is important for purposes of recognizing the extent of the disease in the population as well as a basis for planning and evaluating preventive and treatment programmes. while present day measurement methods for dental caries are excellent such is not true for periodontal diseases. This paper reviews the development and usefulness of different indices for the assessment of periodontal disease and treatment needs in epidemiological investigations.
    Matched MeSH terms: Data Collection
  8. Hospital service quality: a managerial challenge
    Rose RC, Uli J, Abdul M, Ng KL
    Int J Health Care Qual Assur Inc Leadersh Health Serv, 2004;17(2-3):146-59.
    PMID: 15301271
    While much is known generally about predictions of customer-perceived service quality, their application to health services is rarer. No attempt has been made to examine the impact of social support and patient education on overall service quality perception. Together with six quality dimensions identified from the literature, this study seeks to provide a more holistic comprehension of hospital service quality prediction. Although 79 percent of variation is explained, other than technical quality the impact of the remaining factors on quality perception is far from constant, and socio-economic variables further complicate unpredictability. Contrary to established beliefs, the cost factor was found to be insignificant. Hence, to manage service quality effectively, the test lies in how well healthcare providers know the customers they serve. It is not only crucial in a globalized environment, where trans-national patient mobility is increasingly the norm, but also within homogeneous societies that appear to converge culturally.
    Matched MeSH terms: Data Collection
  9. Reform towards National Health Insurance in Malaysia: the equity implications
    Yu CP, Whynes DK, Sach TH
    Health Policy, 2011 May;100(2-3):256-63.
    PMID: 21129808 DOI: 10.1016/j.healthpol.2010.10.018
    This paper assesses the potential equity impact of Malaysia's projected reform of its current tax financed system towards National Health Insurance (NHI).
    Matched MeSH terms: Data Collection
  10. Fulltext Robust Wavelength Selection Using Filter-Wrapper Method and Input Scaling on Near Infrared Spectral Data
    Silalahi DD, Midi H, Arasan J, Mustafa MS, Caliman JP
    Sensors (Basel), 2020 Sep 03;20(17).
    PMID: 32899292 DOI: 10.3390/s20175001
    The extraction of relevant wavelengths from a large dataset of Near Infrared Spectroscopy (NIRS) is a significant challenge in vibrational spectroscopy research. Nonetheless, this process allows the improvement in the chemical interpretability by emphasizing the chemical entities related to the chemical parameters of samples. With the complexity in the dataset, it may be possible that irrelevant wavelengths are still included in the multivariate calibration. This yields the computational process to become unnecessary complex and decreases the accuracy and robustness of the model. In multivariate analysis, Partial Least Square Regression (PLSR) is a method commonly used to build a predictive model from NIR spectral data. However, in the PLSR method and common commercial chemometrics software, there is no standard wavelength selection procedure applied to screen the irrelevant wavelengths. In this study, a new robust wavelength selection procedure called the modified VIP-MCUVE (mod-VIP-MCUVE) using Filter-Wrapper method and input scaling strategy is introduced. The proposed method combines the modified Variable Importance in Projection (VIP) and modified Monte Carlo Uninformative Variable Elimination (MCUVE) to calculate the scale matrix of the input variable. The modified VIP uses the orthogonal components of Partial Least Square (PLS) in investigating the informative variable in the model by applying the amount of variation both in X and y{SSX,SSY}, simultaneously. The modified MCUVE uses a robust reliability coefficient and a robust tolerance interval in the selection procedure. To evaluate the superiority of the proposed method, the classical VIP, MCUVE, and autoscaling procedure in classical PLSR were also included in the evaluation. Using artificial data with Monte Carlo simulation and NIR spectral data of oil palm (Elaeis guineensis Jacq.) fruit mesocarp, the study shows that the proposed method offers advantages to improve model interpretability, to be computationally extensive, and to produce better model accuracy.
    Matched MeSH terms: Data Collection
  11. Fulltext Effect of Addition of Polyaniline on Polyethylene Oxide and Polyvinyl Alcohol for the Fabrication of Nanorods
    Al-Hazeem NZ, Ahmed NM
    ACS Omega, 2020 Sep 08;5(35):22389-22394.
    PMID: 32923796 DOI: 10.1021/acsomega.0c02802
    For the first time, the fabrication of novel nanorods by the addition of polyaniline (PANI) to polyethylene oxide (PEO) and polyvinyl alcohol (PVA) polymers through electrospinning method is investigated. Field emission scanning electron microscopy observations reveal the formation of nanofibers and nanorods having diameters in the range of 26.87-139.90 nm and 64.11-122.40 nm, respectively, and lengths in the range of 542.10 nm to 1.32 μm. Photoluminescence (PL) analysis shows the presence of peaks which are characteristic of isotactic polymers (363-412, 529-691 nm), 412-529 nm for PVA/PEO and 363-691 nm for PVA/PEO/PANI. PL spectra also show peak bonding at a wavelength of 552 nm. Manufacture of nanorods by electrospinning method gives better options for controlling the diameter and length of nanorods.
    Matched MeSH terms: Data Collection
  12. Fulltext Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques
    Hannan MA, Lipu MSH, Hussain A, Ker PJ, Mahlia TMI, Mansor M, et al.
    Sci Rep, 2020 Mar 13;10(1):4687.
    PMID: 32170100 DOI: 10.1038/s41598-020-61464-7
    State of charge (SOC) is a crucial index used in the assessment of electric vehicle (EV) battery storage systems. Thus, SOC estimation of lithium-ion batteries has been widely investigated because of their fast charging, long-life cycle, and high energy density characteristics. However, precise SOC assessment of lithium-ion batteries remains challenging because of their varying characteristics under different working environments. Machine learning techniques have been widely used to design an advanced SOC estimation method without the information of battery chemical reactions, battery models, internal properties, and additional filters. Here, the capacity of optimized machine learning techniques are presented toward enhanced SOC estimation in terms of learning capability, accuracy, generalization performance, and convergence speed. We validate the proposed method through lithium-ion battery experiments, EV drive cycles, temperature, noise, and aging effects. We show that the proposed method outperforms several state-of-the-art approaches in terms of accuracy, adaptability, and robustness under diverse operating conditions.
    Matched MeSH terms: Data Collection
  13. Fulltext Logic mining in league of legends
    Liew, Ching Kho, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor, Sathasivam, Saratha
    Pertanika Journal of Science & Technology, 2020;28(1):211-225.
    MyJurnal
    Since its debut in 2009, League of Legends (LoL) has been on a rise in becoming an extremely favoured multiplayer online battle arena (MOBA) game. This paper presented a logic mining technique to model the results (Win / Lose) of the LoL games played in 3 regions, namely South Korea, North America and Europe. In this research, a method named k satisfiability based reverse analysis method (kSATRA) was brought forward to obtain the logical relationship among the gameplays and objectives in the game. The logical rule obtained from the LoL games was used to categorize the results of future games. kSATRA made use of the advantages of Hopfield Neural Network and k Satisfiability representation. The data set used in this study included the data of all 10 teams from each region, which composed of all games from Spring Season 2018. The effectiveness of kSATRA in obtaining logical rule in LoL games was tested based on root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and CPU time. Results acquired from the computer simulation showed the robustness of kSATRA in exhibiting the performance of the LoL teams.
    Matched MeSH terms: Data Collection
  14. RERS-CC: Robotic facial recognition system for improving the accuracy of human face identification using HRI
    Jing W, Tao H, Rahman MA, Kabir MN, Yafeng L, Zhang R, et al.
    Work, 2021;68(3):923-934.
    PMID: 33612534 DOI: 10.3233/WOR-203426
    BACKGROUND: Human-Computer Interaction (HCI) is incorporated with a variety of applications for input processing and response actions. Facial recognition systems in workplaces and security systems help to improve the detection and classification of humans based on the vision experienced by the input system.

    OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements.

    RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time.

    CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate.

    Matched MeSH terms: Data Collection
  15. Interaction modeling and classification scheme for augmenting the response accuracy of human-robot interaction systems
    Tao H, Rahman MA, Jing W, Li Y, Li J, Al-Saffar A, et al.
    Work, 2021;68(3):903-912.
    PMID: 33720867 DOI: 10.3233/WOR-203424
    BACKGROUND: Human-robot interaction (HRI) is becoming a current research field for providing granular real-time applications and services through physical observation. Robotic systems are designed to handle the roles of humans and assist them through intrinsic sensing and commutative interactions. These systems handle inputs from multiple sources, process them, and deliver reliable responses to the users without delay. Input analysis and processing is the prime concern for the robotic systems to understand and resolve the queries of the users.

    OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.

    RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.

    CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.

    Matched MeSH terms: Data Collection
  16. Fulltext FNG-IE: an improved graph-based method for keyword extraction from scholarly big-data
    Tahir N, Asif M, Ahmad S, Malik MSA, Aljuaid H, Butt MA, et al.
    PeerJ Comput Sci, 2021;7:e389.
    PMID: 33817035 DOI: 10.7717/peerj-cs.389
    Keyword extraction is essential in determining influenced keywords from huge documents as the research repositories are becoming massive in volume day by day. The research community is drowning in data and starving for information. The keywords are the words that describe the theme of the whole document in a precise way by consisting of just a few words. Furthermore, many state-of-the-art approaches are available for keyword extraction from a huge collection of documents and are classified into three types, the statistical approaches, machine learning, and graph-based methods. The machine learning approaches require a large training dataset that needs to be developed manually by domain experts, which sometimes is difficult to produce while determining influenced keywords. However, this research focused on enhancing state-of-the-art graph-based methods to extract keywords when the training dataset is unavailable. This research first converted the handcrafted dataset, collected from impact factor journals into n-grams combinations, ranging from unigram to pentagram and also enhanced traditional graph-based approaches. The experiment was conducted on a handcrafted dataset, and all methods were applied on it. Domain experts performed the user study to evaluate the results. The results were observed from every method and were evaluated with the user study using precision, recall and f-measure as evaluation matrices. The results showed that the proposed method (FNG-IE) performed well and scored near the machine learning approaches score.
    Matched MeSH terms: Data Collection
  17. Fulltext Pharmacist-managed therapeutic drug monitoring service for antiepileptic drugs and improved seizure control
    Chun, Wai Chang, Raman, Sivaraj
    Malaysian Journal of Pharmaceutical Science, 2018;16(1):37-43.
    MyJurnal
    Although therapeutic drug monitoring (TDM) has been used in practice, conflicting data on its usefulness in the management of epilepsy have been reported. These results range from identifying no significant differences in patients’ clinical outcomes to determining TDM to be a cost-effective service. Thus, this study was conducted to evaluate the effectiveness of our pharmacist-managed TDM service in helping patients with epilepsy (PWE) to achieve seizure control. This was a retrospective observational study conducted in the TDM Unit of Hospital Keningau, Sabah. Pharmacist-prepared reports issued for 30 subjects with uncontrolled seizures in 2014 were analysed to determine the effectiveness of their recommendations. Effectiveness was measured based on the number of patients who achieved ≥ 50% reduction in seizure frequency and the number of patients with a threemonth seizure-free period. Overall, 80% of the pharmacists’ TDM recommendations were accepted by prescribers. Based on the data collected, 17 (56.67%) subjects had their seizure frequency decreased at least by half, while 11 (36.67%) subjects achieved total remission. However, there was no significant association between acceptance of recommendations and seizure control; although acceptance of pharmacist recommendations was associated with 1.4 times greater odds of achieving seizure control among PWE, this difference was not statistically significant. In conclusion, a pharmacist-managed TDM service was associated with an improvement in seizure control of more than 50% among PWE with unsatisfactory seizure control.
    Matched MeSH terms: Data Collection
  18. Fulltext PeskAAS: A near-real-time, open-source monitoring and analytics system for small-scale fisheries
    Tilley A, Dos Reis Lopes J, Wilkinson SP
    PLoS One, 2020;15(11):e0234760.
    PMID: 33186386 DOI: 10.1371/journal.pone.0234760
    Small-scale fisheries are responsible for landing half of the world's fish catch, yet there are very sparse data on these fishing activities and associated fisheries production in time and space. Fisheries-dependent data underpin scientific guidance of management and conservation of fisheries systems, but it is inherently difficult to generate robust and comprehensive data for small-scale fisheries, particularly given their dispersed and diverse nature. In tackling this challenge, we use open source software components including the Shiny R package to build PeskAAS; an adaptable and scalable digital application that enables the collation, classification, analysis and visualisation of small-scale fisheries catch and effort data. We piloted and refined this system in Timor-Leste; a small island developing nation. The features that make PeskAAS fit for purpose are that it is: (i) fully open-source and free to use (ii) component-based, flexible and able to integrate vessel tracking data with catch records; (iii) able to perform spatial and temporal filtering of fishing productivity by fishing method and habitat; (iv) integrated with species-specific length-weight parameters from FishBase; (v) controlled through a click-button dashboard, that was co-designed with fisheries scientists and government managers, that enables easy to read data summaries and interpretation of context-specific fisheries data. With limited training and code adaptation, the PeskAAS workflow has been used as a framework on which to build and adapt systematic, standardised data collection for small-scale fisheries in other contexts. Automated analytics of these data can provide fishers, managers and researchers with insights into a fisher's experience of fishing efforts, fisheries status, catch rates, economic efficiency and geographic preferences and limits that can potentially guide management and livelihood investments.
    Matched MeSH terms: Data Collection
  19. Observation of Single Top Quark Production in Association with a Z Boson in Proton-Proton Collisions at sqrt[s]=13  TeV
    Sirunyan AM, Tumasyan A, Adam W, Ambrogi F, Asilar E, Bergauer T, et al.
    Phys Rev Lett, 2019 Apr 05;122(13):132003.
    PMID: 31012605 DOI: 10.1103/PhysRevLett.122.132003
    The observation of single top quark production in association with a Z boson and a quark (tZq) is reported. Events from proton-proton collisions at a center-of-mass energy of 13 TeV containing three charged leptons (either electrons or muons) and at least two jets are analyzed. The data were collected with the CMS detector in 2016 and 2017 and correspond to an integrated luminosity of 77.4fb^{-1}. The increased integrated luminosity, a multivariate lepton identification, and a redesigned analysis strategy improve significantly the sensitivity of the analysis compared to previous searches for tZq production. The tZq signal is observed with a significance well over 5 standard deviations. The measured tZq production cross section is σ(pp→tZq→tℓ^{+}ℓ^{-}q)=111±13(stat)_{-9}^{+11}(syst)  fb, for dilepton invariant masses above 30 GeV, in agreement with the standard model expectation.
    Matched MeSH terms: Data Collection
  20. International stroke genetics consortium recommendations for studies of genetics of stroke outcome and recovery
    Lindgren AG, Braun RG, Juhl Majersik J, Clatworthy P, Mainali S, Derdeyn CP, et al.
    Int J Stroke, 2021 Apr 26.
    PMID: 33739214 DOI: 10.1177/17474930211007288
    Numerous biological mechanisms contribute to outcome after stroke, including brain injury, inflammation, and repair mechanisms. Clinical genetic studies have the potential to discover biological mechanisms affecting stroke recovery in humans and identify intervention targets. Large sample sizes are needed to detect commonly occurring genetic variations related to stroke brain injury and recovery. However, this usually requires combining data from multiple studies where consistent terminology, methodology, and data collection timelines are essential. Our group of expert stroke and rehabilitation clinicians and researchers with knowledge in genetics of stroke recovery here present recommendations for harmonizing phenotype data with focus on measures suitable for multicenter genetic studies of ischemic stroke brain injury and recovery. Our recommendations have been endorsed by the International Stroke Genetics Consortium.
    Matched MeSH terms: Data Collection
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