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  • 1
    Online Resource
    Online Resource
    Ficus cunia Buch.-Ham. ex Roxb. (leaves): An experimental evaluation of the cytotoxicity, thrombolytic, analgesic and neuropharmacological activities of its methanol extract
    Walter de Gruyter GmbH ; 2019
    In:  Journal of Basic and Clinical Physiology and Pharmacology Vol. 30, No. 4 ( 2019-07-26)
    Details
    In: Journal of Basic and Clinical Physiology and Pharmacology, Walter de Gruyter GmbH, Vol. 30, No. 4 ( 2019-07-26)
    Abstract: The aim of this experiment was to evaluate the cytotoxic, thrombolytic, analgesic, sedative-hypnotic and anxiolytic activities of the methanolic extract of Ficus cunia leaves. Methods Primary phytochemical screening was accomplished by using established methods. Cytotoxicity was studied by brine shrimp lethality test, and the thrombolytic assay was conducted through clot lysis method with human blood. The in vivo action was done using mice of both sexes. The analgesic activity was evaluated by acetic acid-induced writhing test and formalin-induced paw licking test. Open field, hole cross and thiopental Na-induced sleeping time test were used to examine the sedative-hypnotic activity, and elevated plus maze (EPM) and hole board test were used to identify the anxiolytic activity. Results The results elicited that the extract contained several phytochemicals such as alkaloid, flavonoid, and tannin. The extract was found to have a median lethal concentration (LC 50 ) value of 55.48 μg/mL in the brine shrimp lethality bioassay. It was also assessed for antithrombotic activity when compared with streptokinase; it has significant (p 〈 0.001) thrombolytic effect (34.72 ± 1.74%) contrasted with standard streptokinase (67 ± 1.56%). The extract at doses of 200 and 400 mg/kg produced inhibition of 32.58% and 46.63% in acetic acid-induced pain and 45.88 and 61.18% in formalin-induced pain. The sedative and hypnotic activities on the central nervous system of the methanol extract of F. cunia (MEFC) leaves were evaluated. The extract delivered critical sedative impact at the doses of 200 and 400 mg/kg (by oral route) treated with reference to the substance diazepam, and the hypnotic impact was also observed in the case of mice. MEFC at its maximum dose (400 mg/kg) significantly (p 〈 0.01) increased the time spent in the open arms of the EPM. In the hole board test, there was a dose-dependent (at 200 and 400 mg/kg) and a significant (p 〈 0.05 and p 〈 0.01) increase in the number of head pokes in comparison to control. Conclusions The results of the present study gave a helpful baseline in progression for the possible use of MEFC as a cytotoxic, thrombolytic, analgesic, sedative-hypnotic and anxiolytic drug.
    Type of Medium: Online Resource
    ISSN: 2191-0286 , 0792-6855
    URL: Article
    DOI: 10.1515/jbcpp-2016-0140
    Language: English
    Publisher: Walter de Gruyter GmbH
    Publication Date: 2019
    detail.hit.zdb_id: 2602428-7
    SSG: 15,3
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  • 2
    Online Resource
    Online Resource
    Review of Researches on Arabic Social Media Text Mining
    Technova Publications ; 2021
    In:  Journal of Intelligent Systems and Computing Vol. 2, No. 1 ( 2021-3-31), p. 20-33
    Details
    In: Journal of Intelligent Systems and Computing, Technova Publications, Vol. 2, No. 1 ( 2021-3-31), p. 20-33
    Abstract: Social media sites and applications have allowed people to share their comments, opinions, and point of views in different languages on mass scale. Arabic language is one of the languages that has seen huge surge in production of its digital textual content. The Arabic content and its metadata are a goldmine of useful information for a wide variety of applications. A large number of researchers are working on Arabic data in various domains of research such as natural language processing, sentiment analysis, event detection, named entity recognition, etc. This article presents a review of number of such studies conducted between 2014 and 2019 using their data sources from social media websites. We found that Twitter was the most used source to contribute data for dataset construction for Arabic text mining researchers. Our study also found that the Sport Vector Machine (SVM) and Naïve Bayesian (NB) classifiers were the most used classifiers in the previous researches. Moreover, the results of the previous studies indicate that SVM classifier provided the best performance compared to other classifiers.
    Type of Medium: Online Resource
    URL: Journal
    URL: Article
    DOI: 10.51682/JISCOM
    DOI: 10.51682/JISCOM.00201005.2021
    Language: Unknown
    Publisher: Technova Publications
    Publication Date: 2021
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  • 3
    Online Resource
    Online Resource
    AIAVRT: 5.0 Transformation in Medical Education with Next Generation AI- 3D Animation and VR Integrated Computer Graphics Imagery
    International Information and Engineering Technology Association ; 2022
    In:  Traitement du Signal Vol. 39, No. 05 ( 2022-11-30), p. 1823-1832
    Details
    In: Traitement du Signal, International Information and Engineering Technology Association, Vol. 39, No. 05 ( 2022-11-30), p. 1823-1832
    Type of Medium: Online Resource
    ISSN: 0765-0019 , 1958-5608
    URL: Issue
    URL: Journal
    URL: Article
    DOI: 10.18280/ts.3905
    DOI: 10.18280/ts
    DOI: 10.18280/ts.390542
    Language: Unknown
    Publisher: International Information and Engineering Technology Association
    Publication Date: 2022
    detail.hit.zdb_id: 2174628-X
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  • 4
    Online Resource
    Online Resource
    Ovarian volume is more closely related to the different manifestations of polycystic ovary syndrome than follicle number per ovary
    The Korean Society for Reproductive Medicine ; 2023
    In:  Clinical and Experimental Reproductive Medicine Vol. 50, No. 3 ( 2023-09-01), p. 200-205
    Details
    In: Clinical and Experimental Reproductive Medicine, The Korean Society for Reproductive Medicine, Vol. 50, No. 3 ( 2023-09-01), p. 200-205
    Abstract: Objective: Polycystic ovary (PCO), a diagnostic component of polycystic ovary syndrome (PCOS), requires either an ovarian volume (OV) criterion or a follicle number per ovary (FNPO) criterion. This study investigated the association of OV and FNPO criteria with various manifestations of PCOS. Methods: This cross-sectional study was conducted at a university hospital among 100 patients newly diagnosed with PCOS (according to the revised Rotterdam criteria). Fasting blood samples were collected to measure glucose, total testosterone (TT), luteinizing hormone (LH), follicle-stimulating hormone (FSH), lipid, insulin, and hemoglobin A1c levels. An oral glucose tolerance test was performed. Transabdominal or transvaginal ultrasound of the ovaries was done, depending on patients’ marital status. All investigations were conducted in the follicular phase of the menstrual cycle. OV 〉 10 mL and/or FNPO ≥12 indicated PCO. A homeostasis model assessment of insulin resistance (IR) value ≥2.6 indicated IR, and metabolic syndrome (MS) was defined according to the international harmonization criteria. Results: Seventy-six participants fulfilled the OV criterion, 70 fulfilled the FNPO criterion, and 89 overall had PCO. Both maximum OV and mean OV had a significant correlation with TT levels ( 〈 italic 〉 r 〈 /italic 〉 =0.239, 〈 italic 〉 p 〈 /italic 〉 =0.017 and 〈 italic 〉 r 〈 /italic 〉 =0.280, 〈 italic 〉 p 〈 /italic 〉 =0.005, respectively) and the LH/FSH ratio ( 〈 italic 〉 r 〈 /italic 〉 =0.212, 〈 italic 〉 p 〈 /italic 〉 =0.034 and 〈 italic 〉 r 〈 /italic 〉 =0.200, 〈 italic 〉 p 〈 /italic 〉 =0.047, respectively). Mean OV also had a significant correlation with fasting insulin levels ( 〈 italic 〉 r 〈 /italic 〉 =0.210, 〈 italic 〉 p 〈 /italic 〉 =0.036). Multivariate binary logistic regression analysis showed that IR (odds ratio [OR], 9.429; 95% confidence interval [CI] , 1.701 to 52.271; 〈 italic 〉 p 〈 /italic 〉 =0.010) and MS (OR, 7.952; 95% CI, 1.821 to 34.731; 〈 italic 〉 p 〈 /italic 〉 =0.006) had significant predictive associations with OV alone, even after adjustment for age and body mass index. Conclusion: OV may be more closely related to the androgenic and metabolic characteristics of PCOS than FNPO.
    Type of Medium: Online Resource
    ISSN: 2233-8233 , 2233-8241
    URL: Article
    DOI: 10.5653/cerm.2023.05897
    Language: English
    Publisher: The Korean Society for Reproductive Medicine
    Publication Date: 2023
    detail.hit.zdb_id: 2653899-4
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  • 5
    Online Resource
    Online Resource
    Effects of Exposure to Cotton Dusts on FVC, FEV1, and FEV1/ FVC% in Male Cotton dust Workers
    Bangladesh Academy of Sciences ; 2016
    In:  Journal of Bangladesh Society of Physiologist Vol. 11, No. 1 ( 2016-09-24), p. 35-38
    Details
    In: Journal of Bangladesh Society of Physiologist, Bangladesh Academy of Sciences, Vol. 11, No. 1 ( 2016-09-24), p. 35-38
    Abstract: Background: Workers in environment with cotton dust exposure are at risk of development of occupational pulmonary functional disorder.Objectives: To observe the effects of cotton dust exposure on FVC, FEV1, FEV1/FVC% in male cotton dust worker.Methods: This cross-sectional study was carried out in the department of physiology, Rangpur Medical College, Rangpur from 2014july to 2015July. Total 25 apparently healthy non-smoker male workers aged 20-40 years, exposed to cotton dust for at least 6 months, were selected from different fabric weaving and cotton ginning factories of Rangpur district. Twenty five age & BMI matched apparently healthy male subjects, not exposed to cotton dusts were taken as control. FVC, FEV1 and FEV1 /FVC% of all subjects were recorded by using a digital spirometer. For statistical analysis, unpairedt-test was performed.Results: The mean percentage of predicted value of FVC, FEV1 were significantly lower (p 〈 0.001) in cotton dust exposed workers (CD-EW) than those of control. The mean percentage of predicted value of FEV1 / FVC% in CD-EW is slightly decreased compared to control but it was not statistically significant.Conclusions: From the result of this study it can be concluded that cotton dust (CD) may have harmful effects on some pulmonary function.Bangladesh Soc Physiol. 2016, June; 11(1): 35-38
    Type of Medium: Online Resource
    ISSN: 1995-1213
    URL: Article
    DOI: 10.3329/jbsp.v11i1.29708
    Language: Unknown
    Publisher: Bangladesh Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 2493544-X
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  • 6
    Online Resource
    Online Resource
    Frequency and predictors of hyperglycemia in patients with various thyroid disorders attending a tertiary hospital of Bangladesh
    Sri Lanka Journals Online ; 2019
    In:  Sri Lanka Journal of Diabetes Endocrinology and Metabolism Vol. 9, No. 1 ( 2019-04-05), p. 18-
    Details
    In: Sri Lanka Journal of Diabetes Endocrinology and Metabolism, Sri Lanka Journals Online, Vol. 9, No. 1 ( 2019-04-05), p. 18-
    Type of Medium: Online Resource
    ISSN: 2012-998X
    URL: Article
    DOI: 10.4038/sjdem.v9i1.7366
    Language: Unknown
    Publisher: Sri Lanka Journals Online
    Publication Date: 2019
    detail.hit.zdb_id: 3076456-7
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  • 7
    Online Resource
    Online Resource
    Efficient-ECGNet framework for COVID-19 classification and correlation prediction with the cardio disease through electrocardiogram medical imaging
    Frontiers Media SA ; 2022
    In:  Frontiers in Medicine Vol. 9 ( 2022-11-4)
    Details
    In: Frontiers in Medicine, Frontiers Media SA, Vol. 9 ( 2022-11-4)
    Abstract: In the last 2 years, we have witnessed multiple waves of coronavirus that affected millions of people around the globe. The proper cure for COVID-19 has not been diagnosed as vaccinated people also got infected with this disease. Precise and timely detection of COVID-19 can save human lives and protect them from complicated treatment procedures. Researchers have employed several medical imaging modalities like CT-Scan and X-ray for COVID-19 detection, however, little concentration is invested in the ECG imaging analysis. ECGs are quickly available image modality in comparison to CT-Scan and X-ray, therefore, we use them for diagnosing COVID-19. Efficient and effective detection of COVID-19 from the ECG signal is a complex and time-taking task, as researchers usually convert them into numeric values before applying any method which ultimately increases the computational burden. In this work, we tried to overcome these challenges by directly employing the ECG images in a deep-learning (DL)-based approach. More specifically, we introduce an Efficient-ECGNet method that presents an improved version of the EfficientNetV2-B4 model with additional dense layers and is capable of accurately classifying the ECG images into healthy, COVID-19, myocardial infarction (MI), abnormal heartbeats (AHB), and patients with Previous History of Myocardial Infarction (PMI) classes. Moreover, we introduce a module to measure the similarity of COVID-19-affected ECG images with the rest of the diseases. To the best of our knowledge, this is the first effort to approximate the correlation of COVID-19 patients with those having any previous or current history of cardio or respiratory disease. Further, we generate the heatmaps to demonstrate the accurate key-points computation ability of our method. We have performed extensive experimentation on a publicly available dataset to show the robustness of the proposed approach and confirmed that the Efficient-ECGNet framework is reliable to classify the ECG-based COVID-19 samples.
    Type of Medium: Online Resource
    ISSN: 2296-858X
    URL: Article
    DOI: 10.3389/fmed.2022.1005920
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2775999-4
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  • 8
    Online Resource
    Online Resource
    An Efficient MAC Protocol for Blockchain-Enabled Patient Monitoring in a Vehicular Network
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 21 ( 2022-10-28), p. 10957-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 21 ( 2022-10-28), p. 10957-
    Abstract: Blockchain is an emerging computing platform that provides recording and tracking facilities to substantially increase the security issues in healthcare systems. The evolution of wireless body area networks requires the continuous monitoring of the health parameters of traveling patients while traveling on road. The health parameter data of each patient are sent to the Road Side Units (RSUs) for generating the blocks by computing the required hash functions. A major challenge in such a network is to efficiently exchange the data blocks between mining RSUs and vehicles using a medium access protocol with a reduced number of collisions. The medium access problem becomes more challenging due to the vehicle mobility, high vehicle density and the varying nature of the data generated by the vehicles. In this work, a TDMA-based MAC protocol to meet an Adaptive Patients Data traffic for Vehicular Network (TAPDVN) is proposed. TAPDVN is specifically designed for patients in a vehicular network by considering the frequent entry and exit of vehicles in a mining node’s coverage area. It allows mining nodes to adjust time slots according to the sensitive patient’s data and allows the maximum number of patient vehicular nodes by considering their sensitivity to send their data in a session to compute their hash values accordingly. Simulation results verify that the proposed scheme accommodates the maximum number of high-risk patient data and improves bandwidth utilization by 20%.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app122110957
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 9
    Online Resource
    Online Resource
    An Anomaly Detection Framework for Twitter Data
    MDPI AG ; 2022
    In:  Applied Sciences Vol. 12, No. 21 ( 2022-11-01), p. 11059-
    Details
    In: Applied Sciences, MDPI AG, Vol. 12, No. 21 ( 2022-11-01), p. 11059-
    Abstract: An anomaly indicates something unusual, related to detecting a sudden behavior change, and is also helpful in detecting irregular and malicious behavior. Anomaly detection identifies unusual events, suspicious objects, or observations that differ significantly from normal behavior or patterns. Discrepancies in data can be observed in different ways, such as outliers, standard deviation, and noise. Anomaly detection helps us understand the emergence of specific diseases based on health-related tweets. This paper aims to analyze tweets to detect the unusual emergence of healthcare-related tweets, especially pre-COVID-19 and during COVID-19. After pre-processing, this work collected more than 44 thousand tweets and performed topic modeling. Non-negative matrix factorization (NMF) and latent Dirichlet allocation (LDA) were deployed for topic modeling, and a query set was designed based on resultant topics. This query set was used for anomaly detection using a sentence transformer. K-means was also employed for clustering outlier tweets from the cleaned tweets based on similarity. Finally, an unusual cluster was selected to identify pandemic-like healthcare emergencies. Experimental results show that the proposed framework can detect a sudden rise of unusual tweets unrelated to regular tweets. The new framework was employed in two case studies for anomaly detection and performed with 78.57% and 70.19% accuracy.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app122111059
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 10
    Online Resource
    Online Resource
    Role of Ultrasound in the Diagnosis and Management of Gall Bladder Diseases
    Bangladesh Academy of Sciences ; 2019
    In:  Ibrahim Cardiac Medical Journal Vol. 7, No. 1-2 ( 2019-03-04), p. 70-75
    Details
    In: Ibrahim Cardiac Medical Journal, Bangladesh Academy of Sciences, Vol. 7, No. 1-2 ( 2019-03-04), p. 70-75
    Abstract: Background & objective: The majority of published data on the sensitivity and specificity of ultrasound (US) in the diagnosis of gallbladder pathology was conducted over 30 years ago. Since then the quality and resolution of ultrasonography has improved significantly. It is, therefore, essential to asses afresh whether the progression in technology has translated into improved diagnostic accuracy. The present study was undertaken to find the usefulness of US in diagnosing gallbladder diseases with particular reference to cholecystitis and gall bladder carcinoma. Methods: This cross-sectional observational study was conducted at the Department of Radiology and Imaging, Rajshahi Medical College, Rajshahi in collaboration with the Departments of General Surgery and Histopathology of the same Medical College between July 2016 to June 2018. A total of 128 patients were initially included on the basis of signs and symptoms of gallbladder diseases. All these patients were subjected to abdominal US to achieve a ultrasonic diagnosis of gall bladder disease followed by histopathological examination of biopsy material taken from the gall bladder or specimen of the operated gall bladder. The accuracy of ultrasound in the diagnosis of gall bladder diseases was determined by comparing the ultrasound sound diagnosis with that of histopathological diagnosis. In particular, the role of ultrasound was evaluated in the differentiation of benign gall bladder diseases from those of malignant ones. Result: Age distribution of the patients shows that over one-third (35.9%) was ≥50 years old followed by 24.9% 40-50 years, 21.9% 30 - 40 years and 16.4% 20 – 30 years old with mean age of the patients being 43.8(range: 18-80) years. Females outnumbered males by roughly 11:9. In terms of BMI, 6.2% were underweight, 16.4% overweight, and 4.7% obese. The predominant complaints reported by the patients were pain in the right upper abdomen (95.3%), epigastric pain (94.7%), abdominal discomfort (96.9%) followed by nausea (75%), low-grade fever (37.5%), jaundice (26.6%) and vomiting (26.6%). Approximately 44% of the patients exhibited anaemia. Nearly half (46.1%) of the patients exhibited sonographic Murphy’s sign. Hyperechoic echo character was invariably obtained with 12.5% cases having hypoechoeic character as well. Over 90% of the patients had gall-stones, 62.5% cholecystitis (thickened gall-bladder wall). Ultrasound comment on the type of diseases revealed that 112(87.5%) were benign diseases and 16(12.5%) malignant cases. Approximately 55% of the gall bladder diseases diagnosed by histopathology were cholecystitis. Histopathological comment shows that about 90% of the diseases were benign and the rest (10.2%) were malignant. The sensitivity of ultrasound in diagnosing cholecystitis was 85.9%, while the specificity of the test was 60.9% with overall diagnostic accuracy of the test being 73.4%. The US had a optimum sensitivity (84.6%) and high specificity (95.6%) in diagnosing gall-bladder carcinoma. Conclusion: The study concluded that US could be considered as the preferred initial imaging technique for patients who are clinically suspected of having acute calculous cholecystitis. It is also a useful imaging modality for diagnosing gall-bladder malignancy. Thus, US can be dependably used in the primary evaluation of heptobilliary pathology. Ibrahim Card Med J 2017; 7 (1 & 2): 70-75
    Type of Medium: Online Resource
    ISSN: 2223-0971 , 2223-0963
    URL: Article
    DOI: 10.3329/icmj.v7i1-2.53963
    Language: Unknown
    Publisher: Bangladesh Academy of Sciences
    Publication Date: 2019
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