Displaying publications 1 - 20 of 27 in total

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  1. Shamsul,Fadzil,S,S,, Ahmad,Khalil,A,I,, Noviaranny,I,Y,, Abdullah,Al-Jaf,N,M,, Kazi,J,A,
    Compendium of Oral Science, 2020;7(1):21-29.
    MyJurnal
    Abstract
    Objectives: The aims of this study were to evaluate patient’s satisfaction regarding the orthodontic treatment
    provided by the Faculty of Dentistry Universiti Teknologi MARA (UiTM) and to determine the factors that
    affected their satisfaction level.
    Methods: : A cross-sectional study was conducted among the patients treated with full fixed appliances in the
    faculty’s orthodontic clinic using a validated questionnaire.
    Results: : The final sample consisted of 105 subjects (response rate 76%) which comprises of 26 males and 79
    females were chose with 97% of the respondents are Malay. Most subjects had orthodontic treatment duration
    of more than 1.5 years (100%) and were still wearing fixed appliances (89%). Items included in the
    questionnaire: reasons for seeking orthodontic treatment, questions relevant to satisfaction with orthodontic
    treatment, doctor-patient relationship and pain experience during orthodontic treatment. Concerning the doctor
    patient relationship, 91% of the respondents were contented with their orthodontist. Respondents answered
    ‘Yes’ to the treatment plan explained prior to the procedure (91.4%), questions answered promptly (94.3%),
    gentleness of the orthodontist (91.4%) and dental assistant (88.6%), orthodontist honesty about treatment
    duration (90.5%) and cost (97.1%), and recommendation to others (90.5%).
    Conclusion: Generally, patients who had received orthodontic treatment from the orthodontic clinic in Faculty
    of Dentistry UiTM were satisfied with the overall treatment outcomes. However, there were still some aspects of
    the service that can be improved in the future in order to provide a better healthcare services specifically in
    orthodontic treatment.
  2. Rahimi A, Khalil A, Faisal A, Lai KW
    Curr Med Imaging, 2021;18(1):61-66.
    PMID: 34433403 DOI: 10.2174/1573405617666210825155659
    BACKGROUND: Early diagnosis of liver cancer may increase life expectancy. Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) play a vital role in diagnosing liver cancer. Together, both modalities offer significant individual and specific diagnosis data to physicians; however, they lack the integration of both types of information. To address this concern, a registration process has to be utilized for the purpose, as multimodal details are crucial in providing the physician with complete information.

    OBJECTIVE: The aim was to present a model of CT-MRI registration used to diagnose liver cancer, specifically for improving the quality of the liver images and provide all the required information for earlier detection of the tumors. This method should concurrently address the issues of imaging procedures for liver cancer to fasten the detection of the tumor from both modalities.

    METHODS: In this work, a registration scheme for fusing the CT and MRI liver images is studied. A feature point-based method with normalized cross-correlation has been utilized to aid in the diagnosis of liver cancer and provide multimodal information to physicians. Data on ten patients from an online database were obtained. For each dataset, three planar views from both modalities were interpolated and registered using feature point-based methods. The registration of algorithms was carried out by MATLAB (vR2019b, Mathworks, Natick, USA) on an Intel (R) Core (TM) i5-5200U CPU @ 2.20 GHz computer. The accuracy of the registered image is being validated qualitatively and quantitatively.

    RESULTS: The results show that an accurate registration is obtained with minimal distance errors by which CT and MRI were accurately registered based on the validation of the experts. The RMSE ranges from 0.02 to 1.01 for translation, which is equivalent in magnitude to approximately 0 to 5 pixels for CT and registered image resolution.

    CONCLUSION: The CT-MRI registration scheme can provide complementary information on liver cancer to physicians, thus improving the diagnosis and treatment planning process.

  3. Rahimi AM, Nurdin I, Ismail S, Khalil A
    Radiol Res Pract, 2021;2021:5566654.
    PMID: 34394988 DOI: 10.1155/2021/5566654
    Radiology is a vital diagnostic tool for multiple disorders that plays an essential role in the healthcare sector. Nurses are majorly involved in a healthcare setting by accompanying patients during the examination. Thus, nurses tend to be exposed during inward X-ray examination, requiring them to keep up with radiation use safety. However, nurses' competence in radiation is still a concept that has not been well studied in Malaysia. The study aimed to define the level of usage understanding and radiation protection among Malaysian nurses. In this research, a cross-sectional survey was conducted among 395 nurses working in hospitals, clinics, and other healthcare sectors in Malaysia. The survey is based on the developed Healthcare Professional Knowledge of Radiation Protection (HPKRP) scale, distributed via the online Google Forms. SPSS version 25.0 (IBM Corporation) was used to analyze the data in this study. Malaysian nurses reported the highest knowledge level in radiation protection with a mean of 6.03 ± 2.59. The second highest is safe ionizing radiation guidelines with 5.83 ± 2.77, but low knowledge levels in radiation physics and radiation usage principle (4.69 ± 2.49). Therefore, healthcare facilities should strengthen the training standards for all nurses working with or exposed to radiation.
  4. Latha S, Muthu P, Lai KW, Khalil A, Dhanalakshmi S
    Front Aging Neurosci, 2021;13:828214.
    PMID: 35153728 DOI: 10.3389/fnagi.2021.828214
    Atherosclerotic plaque deposit in the carotid artery is used as an early estimate to identify the presence of cardiovascular diseases. Ultrasound images of the carotid artery are used to provide the extent of stenosis by examining the intima-media thickness and plaque diameter. A total of 361 images were classified using machine learning and deep learning approaches to recognize whether the person is symptomatic or asymptomatic. CART decision tree, random forest, and logistic regression machine learning algorithms, convolutional neural network (CNN), Mobilenet, and Capsulenet deep learning algorithms were applied in 202 normal images and 159 images with carotid plaque. Random forest provided a competitive accuracy of 91.41% and Capsulenet transfer learning approach gave 96.7% accuracy in classifying the carotid artery ultrasound image database.
  5. Khalil A, Faisal A, Ng SC, Liew YM, Lai KW
    J Med Imaging (Bellingham), 2017 Jul;4(3):037001.
    PMID: 28840172 DOI: 10.1117/1.JMI.4.3.037001
    A registration method to fuse two-dimensional (2-D) echocardiography images with cardiac computed tomography (CT) volume is presented. The method consists of two major procedures: temporal and spatial registrations. In temporal registration, the echocardiography frames at similar cardiac phases as the CT volume were interpolated based on electrocardiogram signal information, and the noise of the echocardiography image was reduced using the speckle reducing anisotropic diffusion technique. For spatial registration, an intensity-based normalized mutual information method was applied with a pattern search optimization algorithm to produce an interpolated cardiac CT image. The proposed registration framework does not require optical tracking information. Dice coefficient and Hausdorff distance for the left atrium assessments were [Formula: see text] and [Formula: see text], respectively; for left ventricle, they were [Formula: see text] and [Formula: see text], respectively. There was no significant difference in the mitral valve annulus diameter measurement between the manually and automatically registered CT images. The transformation parameters showed small deviations ([Formula: see text] deviation in translation and [Formula: see text] for rotation) between manual and automatic registrations. The proposed method aids the physician in diagnosing mitral valve disease as well as provides surgical guidance during the treatment procedure.
  6. Khalil A, Faisal A, Lai KW, Ng SC, Liew YM
    Med Biol Eng Comput, 2017 Aug;55(8):1317-1326.
    PMID: 27830464 DOI: 10.1007/s11517-016-1594-6
    This study proposed a registration framework to fuse 2D echocardiography images of the aortic valve with preoperative cardiac CT volume. The registration facilitates the fusion of CT and echocardiography to aid the diagnosis of aortic valve diseases and provide surgical guidance during transcatheter aortic valve replacement and implantation. The image registration framework consists of two major steps: temporal synchronization and spatial registration. Temporal synchronization allows time stamping of echocardiography time series data to identify frames that are at similar cardiac phase as the CT volume. Spatial registration is an intensity-based normalized mutual information method applied with pattern search optimization algorithm to produce an interpolated cardiac CT image that matches the echocardiography image. Our proposed registration method has been applied on the short-axis "Mercedes Benz" sign view of the aortic valve and long-axis parasternal view of echocardiography images from ten patients. The accuracy of our fully automated registration method was 0.81 ± 0.08 and 1.30 ± 0.13 mm in terms of Dice coefficient and Hausdorff distance for short-axis aortic valve view registration, whereas for long-axis parasternal view registration it was 0.79 ± 0.02 and 1.19 ± 0.11 mm, respectively. This accuracy is comparable to gold standard manual registration by expert. There was no significant difference in aortic annulus diameter measurement between the automatically and manually registered CT images. Without the use of optical tracking, we have shown the applicability of this technique for effective fusion of echocardiography with preoperative CT volume to potentially facilitate catheter-based surgery.
  7. Khalil A, Salem M, Ragab S, Sillanpää M, El Nemr A
    Sci Rep, 2023 Feb 28;13(1):3402.
    PMID: 36854794 DOI: 10.1038/s41598-023-30161-6
    This work prepared a composite of orange peels magnetic activated carbon (MG-OPAC). The prepared composite was categorized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), Brunauer-Emmett-Teller (BET), Energy-dispersive X-ray spectroscopy (EDX), Scanning Electron Microscopy (SEM) and vibrating-sample magnetometer (VSM) analyses. The MG-OPAC composite showed the surface area (155.09 m2/g), the total volume of pores (0.1768 cm3/g), and the mean diameter of pores (4.5604 nm). The saturation magnetization (Ms = 17.283 emu/g), remanence (Mr = 0.28999 emu/g) and coercivity (Hc = 13.714 G) were reported for the prepared MG-OPAC. Likewise, at room temperature, the MG-OPAC was in a super-paramagnetic state, which could be collected within 5 S (
  8. Khalil A, Ng SC, Liew YM, Lai KW
    Cardiol Res Pract, 2018;2018:1437125.
    PMID: 30159169 DOI: 10.1155/2018/1437125
    Image registration has been used for a wide variety of tasks within cardiovascular imaging. This study aims to provide an overview of the existing image registration methods to assist researchers and impart valuable resource for studying the existing methods or developing new methods and evaluation strategies for cardiac image registration. For the cardiac diagnosis and treatment strategy, image registration and fusion can provide complementary information to the physician by using the integrated image from these two modalities. This review also contains a description of various imaging techniques to provide an appreciation of the problems associated with implementing image registration, particularly for cardiac pathology intervention and treatments.
  9. Ullah S, Daud H, Dass SC, Fanaee-T H, Khalil A
    PLoS One, 2018;13(6):e0199176.
    PMID: 29920540 DOI: 10.1371/journal.pone.0199176
    Identifying the abnormally high-risk regions in a spatiotemporal space that contains an unexpected disease count is helpful to conduct surveillance and implement control strategies. The EigenSpot algorithm has been recently proposed for detecting space-time disease clusters of arbitrary shapes with no restriction on the distribution and quality of the data, and has shown some promising advantages over the state-of-the-art methods. However, the main problem with the EigenSpot method is that it cannot be adapted to detect more than one spatiotemporal hotspot. This is an important limitation, since, in reality, we may have multiple hotspots, sometimes at the same level of importance. We propose an extension of the EigenSpot algorithm, called Multi-EigenSpot that is able to handle multiple hotspots by iteratively removing previously detected hotspots and re-running the algorithm until no more hotspots are found. In addition, a visualization tool (heatmap) has been linked to the proposed algorithm to visualize multiple clusters with different colors. We evaluated the proposed method using the monthly data on measles cases in Khyber-Pakhtunkhwa, Pakistan (Jan 2016- Dec 2016), and the efficiency was compared with the state-of-the-art methods: EigenSpot and Space-time scan statistic (SaTScan). The results showed the effectiveness of the proposed method for detecting multiple clusters in a spatiotemporal space.
  10. Manuel AM, Kalimuthu S, Pathmanathan SS, Narayanan P, Zainal Abidin Z, Azmi K, et al.
    Asian J Surg, 2017 Apr;40(2):158-162.
    PMID: 24210537 DOI: 10.1016/j.asjsur.2013.09.011
    Arteriovenous malformations are congenital lesions that may evolve with time and manifest in a plethora of presentations. They can occur as torrential epistaxis when it extensively involves the facial region. Multi-imaging modalities are available to assist in characterizing the structure of the lesion as well as its location and extent. This complex disease requires a multidisciplinary team approach with preoperative embolization and surgery. We present a rare cause of life-threatening epistaxis in a gentleman with a longstanding orbital and hemifacial arteriovenous malformation and discuss the complexities involved in its management.
  11. Bewersdorf JP, Hautmann O, Kofink D, Abdul Khalil A, Zainal Abidin I, Loch A
    Eur J Emerg Med, 2017 Jun;24(3):170-175.
    PMID: 26524675 DOI: 10.1097/MEJ.0000000000000344
    OBJECTIVES: The aim of the study was to identify covariates associated with 28-day mortality in septic patients admitted to the emergency department and derive and validate a score that stratifies mortality risk utilizing parameters that are readily available.

    METHODS: Patients with an admission diagnosis of suspected or confirmed infection and fulfilling at least two criteria for severe inflammatory response syndrome were included in this study. Patients' characteristics, vital signs, and laboratory values were used to identify prognostic factors for mortality. A scoring system was derived and validated. The primary outcome was the 28-day mortality rate.

    RESULTS: A total of 440 patients were included in the study. The 28-day hospital mortality rate was 32.4 and 25.2% for the derivation (293 patients) and validation (147 patients) sets, respectively. Factors associated with a higher mortality were immune-suppressed state (odds ratio 4.7; 95% confidence interval 2.0-11.4), systolic blood pressure on arrival less than 90 mmHg (3.8; 1.7-8.3), body temperature less than 36.0°C (4.1; 1.3-12.9), oxygen saturation less than 90% (2.3; 1.1-4.8), hematocrit less than 0.38 (3.1; 1.6-5.9), blood pH less than 7.35 (2.0; 1.04-3.9), lactate level more than 2.4 mmol/l (2.27; 1.2-4.2), and pneumonia as the source of infection (2.7; 1.5-5.0). The area under the receiver operating characteristic curve was 0.81 (0.75-0.86) in the derivation and 0.81 (0.73-0.90) in the validation set. The SPEED (sepsis patient evaluation in the emergency department) score performed better (P=0.02) than the Mortality in Emergency Department Sepsis score when applied to the complete study population with an area under the curve of 0.81 (0.76-0.85) as compared with 0.74 (0.70-0.79).

    CONCLUSION: The SPEED score predicts 28-day mortality in septic patients. It is simple and its predictive value is comparable to that of other scoring systems.

  12. Moradi A, Pramanik S, Ataollahi F, Abdul Khalil A, Kamarul T, Pingguan-Murphy B
    Sci Technol Adv Mater, 2014 Dec;15(6):065001.
    PMID: 27877731
    Native cartilage matrix derived (CMD) scaffolds from various animal and human sources have drawn attention in cartilage tissue engineering due to the demonstrable presence of bioactive components. Different chemical and physical treatments have been employed to enhance the micro-architecture of CMD scaffolds. In this study we have assessed the typical effects of physical cross-linking methods, namely ultraviolet (UV) light, dehydrothermal (DHT) treatment, and combinations of them on bovine articular CMD porous scaffolds with three different matrix concentrations (5%, 15% and 30%) to assess the relative strengths of each treatment. Our findings suggest that UV and UV-DHT treatments on 15% CMD scaffolds can yield architecturally optimal scaffolds for cartilage tissue engineering.
  13. Ullah S, Daud H, Dass SC, Fanaee-T H, Kausarian H, Khalil A
    PMID: 32098247 DOI: 10.3390/ijerph17041413
    The number of tuberculosis (TB) cases in Pakistan ranks fifth in the world. The National TB Control Program (NTP) has recently reported more than 462,920 TB patients in Khyber Pakhtunkhwa province, Pakistan from 2002 to 2017. This study aims to identify spatial and space-time clusters of TB cases in Khyber Pakhtunkhwa province Pakistan during 2015-2019 to design effective interventions. The spatial and space-time cluster analyses were conducted at the district-level based on the reported TB cases from January 2015 to April 2019 using space-time scan statistics (SaTScan). The most likely spatial and space-time clusters were detected in the northern rural part of the province. Additionally, two districts in the west were detected as the secondary space-time clusters. The most likely space-time cluster shows a tendency of spread toward the neighboring districts in the central part, and the most likely spatial cluster shows a tendency of spread toward the neighboring districts in the south. Most of the space-time clusters were detected at the start of the study period 2015-2016. The potential TB clusters in the remote rural part might be associated to the dry-cool climate and lack of access to the healthcare centers in the remote areas.
  14. Nizar MHA, Chan CK, Khalil A, Yusof AKM, Lai KW
    Curr Med Imaging, 2020;16(5):584-591.
    PMID: 32484093 DOI: 10.2174/1573405615666190114151255
    BACKGROUND: Valvular heart disease is a serious disease leading to mortality and increasing medical care cost. The aortic valve is the most common valve affected by this disease. Doctors rely on echocardiogram for diagnosing and evaluating valvular heart disease. However, the images from echocardiogram are poor in comparison to Computerized Tomography and Magnetic Resonance Imaging scan. This study proposes the development of Convolutional Neural Networks (CNN) that can function optimally during a live echocardiographic examination for detection of the aortic valve. An automated detection system in an echocardiogram will improve the accuracy of medical diagnosis and can provide further medical analysis from the resulting detection.

    METHODS: Two detection architectures, Single Shot Multibox Detector (SSD) and Faster Regional based Convolutional Neural Network (R-CNN) with various feature extractors were trained on echocardiography images from 33 patients. Thereafter, the models were tested on 10 echocardiography videos.

    RESULTS: Faster R-CNN Inception v2 had shown the highest accuracy (98.6%) followed closely by SSD Mobilenet v2. In terms of speed, SSD Mobilenet v2 resulted in a loss of 46.81% in framesper- second (fps) during real-time detection but managed to perform better than the other neural network models. Additionally, SSD Mobilenet v2 used the least amount of Graphic Processing Unit (GPU) but the Central Processing Unit (CPU) usage was relatively similar throughout all models.

    CONCLUSION: Our findings provide a foundation for implementing a convolutional detection system to echocardiography for medical purposes.

  15. Khalil A, Rahimi A, Luthfi A, Azizan MM, Satapathy SC, Hasikin K, et al.
    Front Public Health, 2021;9:752509.
    PMID: 34621723 DOI: 10.3389/fpubh.2021.752509
    A process that involves the registration of two brain Magnetic Resonance Imaging (MRI) acquisitions is proposed for the subtraction between previous and current images at two different follow-up (FU) time points. Brain tumours can be non-cancerous (benign) or cancerous (malignant). Treatment choices for these conditions rely on the type of brain tumour as well as its size and location. Brain cancer is a fast-spreading tumour that must be treated in time. MRI is commonly used in the detection of early signs of abnormality in the brain area because it provides clear details. Abnormalities include the presence of cysts, haematomas or tumour cells. A sequence of images can be used to detect the progression of such abnormalities. A previous study on conventional (CONV) visual reading reported low accuracy and speed in the early detection of abnormalities, specifically in brain images. It can affect the proper diagnosis and treatment of the patient. A digital subtraction technique that involves two images acquired at two interval time points and their subtraction for the detection of the progression of abnormalities in the brain image was proposed in this study. MRI datasets of five patients, including a series of brain images, were retrieved retrospectively in this study. All methods were carried out using the MATLAB programming platform. ROI volume and diameter for both regions were recorded to analyse progression details, location, shape variations and size alteration of tumours. This study promotes the use of digital subtraction techniques on brain MRIs to track any abnormality and achieve early diagnosis and accuracy whilst reducing reading time. Thus, improving the diagnostic information for physicians can enhance the treatment plan for patients.
  16. Nawaz NA, Ishaq K, Farooq U, Khalil A, Rasheed S, Abid A, et al.
    PeerJ Comput Sci, 2023;9:e1143.
    PMID: 37346522 DOI: 10.7717/peerj-cs.1143
    The term "cyber threats" refers to the new category of hazards that have emerged with the rapid development and widespread use of computing technologies, as well as our growing reliance on them. This article presents an in-depth study of a variety of security and privacy threats directed at different types of users of social media sites. Furthermore, it focuses on different risks while sharing multimedia content across social networking platforms, and discusses relevant prevention measures and techniques. It also shares methods, tools, and mechanisms for safer usage of online social media platforms, which have been categorized based on their providers including commercial, open source, and academic solutions.
  17. Ullah S, Mohd Nor NH, Daud H, Zainuddin N, Gandapur MSJ, Ali I, et al.
    Geospat Health, 2021 May 05;16(1).
    PMID: 33969966 DOI: 10.4081/gh.2021.961
    Coronavirus disease 2019 (COVID-19) is the current worldwide pandemic as declared by the World Health Organization (WHO) in March 2020. Being part of the ongoing global pandemic, Malaysia has recorded a total of 8639 COVID-19 cases and 121 deaths as of 30th June 2020. This study aims to detect spatial clusters of COVID-19 in Malaysia using the Spatial Scan Statistic (SaTScan™) to guide control authorities on prioritizing locations for targeted interventions. The spatial analyses were conducted on a monthly basis at the state-level from March to September 2020. The results show that the most likely cluster of COVID-19 occurred in West Malaysia repeatedly from March to June, covering three counties (two federal territories and one neighbouring state) and moved to East Malaysia in July covering two other counties. The most likely cluster shows a tendency of having moved from the western part to the eastern part of the country. These results provide information that can be used for the evidence- based interventions to control the spread of COVID-19 in Malaysia. A Correction has been published: https://doi.org/10.4081/gh.2023.1233
  18. Chear NJ, León F, Sharma A, Kanumuri SRR, Zwolinski G, Abboud KA, et al.
    J Nat Prod, 2021 04 23;84(4):1034-1043.
    PMID: 33635670 DOI: 10.1021/acs.jnatprod.0c01055
    Ten indole and oxindole alkaloids (1-10) were isolated from the freshly collected leaves of Malaysian Mitragyna speciosa (Kratom). The chemical structures of these compounds were established on the basis of extensive 1D and 2D NMR and HRMS data analysis. The spectroscopic data of mitragynine oxindole B (4) are reported herein for the first time. The spatial configuration of mitragynine oxindole B (4) was confirmed by single-crystal X-ray diffraction. Simultaneous quantification of the isolated alkaloids in the M. speciosa leaf specimens collected from different locations in the northern region of Peninsular Malaysia was also performed using UPLC-MS/MS. The oxindole alkaloids (1-4) and the indole alkaloid (10) were assessed for binding affinity at opioid receptors. Corynoxine (1) showed high binding affinity to μ-opioid receptors with a Ki value of 16.4 nM. Further, corynoxine (1) was 1.8-fold more potent than morphine in rats subjected to a nociceptive hot plate assay. These findings have important implications for evaluating the combined effects of the minor oxindole alkaloids in the overall therapeutic activity of M. speciosa.
  19. Muglu J, Rather H, Arroyo-Manzano D, Bhattacharya S, Balchin I, Khalil A, et al.
    PLoS Med, 2019 07;16(7):e1002838.
    PMID: 31265456 DOI: 10.1371/journal.pmed.1002838
    BACKGROUND: Despite advances in healthcare, stillbirth rates remain relatively unchanged. We conducted a systematic review to quantify the risks of stillbirth and neonatal death at term (from 37 weeks gestation) according to gestational age.

    METHODS AND FINDINGS: We searched the major electronic databases Medline, Embase, and Google Scholar (January 1990-October 2018) without language restrictions. We included cohort studies on term pregnancies that provided estimates of stillbirths or neonatal deaths by gestation week. We estimated the additional weekly risk of stillbirth in term pregnancies that continued versus delivered at various gestational ages. We compared week-specific neonatal mortality rates by gestational age at delivery. We used mixed-effects logistic regression models with random intercepts, and computed risk ratios (RRs), odds ratios (ORs), and 95% confidence intervals (CIs). Thirteen studies (15 million pregnancies, 17,830 stillbirths) were included. All studies were from high-income countries. Four studies provided the risks of stillbirth in mothers of White and Black race, 2 in mothers of White and Asian race, 5 in mothers of White race only, and 2 in mothers of Black race only. The prospective risk of stillbirth increased with gestational age from 0.11 per 1,000 pregnancies at 37 weeks (95% CI 0.07 to 0.15) to 3.18 per 1,000 at 42 weeks (95% CI 1.84 to 4.35). Neonatal mortality increased when pregnancies continued beyond 41 weeks; the risk increased significantly for deliveries at 42 versus 41 weeks gestation (RR 1.87, 95% CI 1.07 to 2.86, p = 0.012). One additional stillbirth occurred for every 1,449 (95% CI 1,237 to 1,747) pregnancies that advanced from 40 to 41 weeks. Limitations include variations in the definition of low-risk pregnancy, the wide time span of the studies, the use of registry-based data, and potential confounders affecting the outcome.

    CONCLUSIONS: Our findings suggest there is a significant additional risk of stillbirth, with no corresponding reduction in neonatal mortality, when term pregnancies continue to 41 weeks compared to delivery at 40 weeks.

    SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015013785.

  20. Meng LK, Khalil A, Ahmad Nizar MH, Nisham MK, Pingguan-Murphy B, Hum YC, et al.
    Curr Med Imaging Rev, 2019;15(10):983-989.
    PMID: 32008525 DOI: 10.2174/1573405615666190724101600
    BACKGROUND: Bone Age Assessment (BAA) refers to a clinical procedure that aims to identify a discrepancy between biological and chronological age of an individual by assessing the bone age growth. Currently, there are two main methods of executing BAA which are known as Greulich-Pyle and Tanner-Whitehouse techniques. Both techniques involve a manual and qualitative assessment of hand and wrist radiographs, resulting in intra and inter-operator variability accuracy and time-consuming. An automatic segmentation can be applied to the radiographs, providing the physician with more accurate delineation of the carpal bone and accurate quantitative analysis.

    METHODS: In this study, we proposed an image feature extraction technique based on image segmentation with the fully convolutional neural network with eight stride pixel (FCN-8). A total of 290 radiographic images including both female and the male subject of age ranging from 0 to 18 were manually segmented and trained using FCN-8.

    RESULTS AND CONCLUSION: The results exhibit a high training accuracy value of 99.68% and a loss rate of 0.008619 for 50 epochs of training. The experiments compared 58 images against the gold standard ground truth images. The accuracy of our fully automated segmentation technique is 0.78 ± 0.06, 1.56 ±0.30 mm and 98.02% in terms of Dice Coefficient, Hausdorff Distance, and overall qualitative carpal recognition accuracy, respectively.

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