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  1. AU="Nazrul Islam"
  2. AU="Qadir, Syed Saeed"
  3. AU="Koutsoukos, Marguerite"
  4. AU="Webster, Kara"
  5. AU=Tremoulet Adriana H.
  6. AU="Foggia, Maria"
  7. AU=Eccles Michael R
  8. AU="Karrison, Theodore"
  9. AU="Espigado, I"
  10. AU="Dean, Andrew"

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  1. Buch ; Online ; E-Book: Chinese medicine and transnational transition during the modern era

    Islam, Md. Nazrul

    commodification, hybridity, and segregation

    2021  

    Verfasserangabe Md. Nazrul Islam editor
    Schlagwörter Medicine—History ; Sociology ; World history ; Health care management ; Health services administration ; Medical education
    Thema/Rubrik (Code) 616.009
    Sprache Englisch
    Umfang 1 Online-Ressource (xxi, 222 Seiten), Illustrationen
    Verlag Palgrave Macmillan
    Erscheinungsort Singapore
    Erscheinungsland Singapur
    Dokumenttyp Buch ; Online ; E-Book
    Bemerkung Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT020973878
    ISBN 978-981-15-9949-1 ; 9789811599484 ; 981-15-9949-1 ; 9811599483
    DOI 10.1007/978-981-15-9949-1
    Datenquelle ZB MED Katalog Medizin, Gesundheit, Ernährung, Umwelt, Agrar

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  2. Artikel ; Online: A blockchain based medicine production and distribution framework to prevent medicine counterfeit

    Iyolita Islam / Muhammad Nazrul Islam

    Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 1, Pp 101851- (2024)

    1481  

    Abstract: Medicine counterfeiting has raised significant concern in recent years. Falsified and counterfeit drug production and distribution are illegal and a public health concern. The intensity of this problem varies significantly among different countries, ... ...

    Abstract Medicine counterfeiting has raised significant concern in recent years. Falsified and counterfeit drug production and distribution are illegal and a public health concern. The intensity of this problem varies significantly among different countries, depending on how strongly a country’s laws and procedures are followed. Preventing counterfeit medicines has thus become a critical concern, especially in developing and underdeveloped countries. This research aims, firstly, to outline the possible factors of medicine counterfeiting; secondly, to propose a blockchain-based framework to prevent medicine counterfeiting; and thirdly, to evaluate the proposed framework. A content analysis and a semi-structured interview with the key personnel related to the medicine manufacturing and distribution system in Bangladesh were carried out to derive the current scenario of medicine counterfeit. Based on the interviews and content analysis, a set of use cases for preventing medicine counterfeiting in the context of Bangladesh was explored. The required features for developing a digital solution were extracted considering the derived use cases. A blockchain-based framework for preventing medicine counterfeit was proposed by adopting the extracted features. A prototype was developed based on the proposed framework, and an evaluation study was performed to evaluate the prototype. The evaluation study showed that the average block execution time is 201 ms, and the average block time is 482 ms. Again, the proposed framework was found secure, scalable, customer-oriented, and practical compared to other systems.
    Schlagwörter Medicine counterfeit ; Falsified drugs ; Blockchain-based framework ; Digital solution ; Medicine production and distribution ; Electronic computers. Computer science ; QA75.5-76.95
    Thema/Rubrik (Code) 001
    Sprache Englisch
    Erscheinungsdatum 2024-01-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Social and structural determinants associated with the prevalence of sexually transmitted infections among female commercial sex workers in Dhaka City, Bangladesh

    Mahbuba Kawser / Md. Nazrul Islam Khan / Kazi Jahangir Hossain / Sheikh Nazrul Islam

    PLOS Global Public Health, Vol 4, Iss

    2024  Band 1

    Schlagwörter Public aspects of medicine ; RA1-1270
    Sprache Englisch
    Erscheinungsdatum 2024-01-01T00:00:00Z
    Verlag Public Library of Science (PLoS)
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: Antagonistic activity of

    Afrin, Sadia / Bhuiyan, Mohammad Nazrul Islam

    Current research in microbial sciences

    2023  Band 5, Seite(n) 100206

    Abstract: ... Serratia ... ...

    Abstract Serratia rubidaea
    Sprache Englisch
    Erscheinungsdatum 2023-11-26
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ISSN 2666-5174
    ISSN (online) 2666-5174
    DOI 10.1016/j.crmicr.2023.100206
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel: Characterizations of generalized Robertson-Walker spacetimes concerning gradient solitons.

    De, Krishnendu / Khan, Mohammad Nazrul Islam / De, Uday Chand

    Heliyon

    2024  Band 10, Heft 4, Seite(n) e25702

    Abstract: In this article, we examine gradient type Ricci solitons ... ...

    Abstract In this article, we examine gradient type Ricci solitons and
    Sprache Englisch
    Erscheinungsdatum 2024-02-06
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e25702
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel ; Online: A systematic review and future research agenda on detection of polycystic ovary syndrome (PCOS) with computer-aided techniques

    Sayma Alam Suha / Muhammad Nazrul Islam

    Heliyon, Vol 9, Iss 10, Pp e20524- (2023)

    2023  

    Abstract: Polycystic Ovary Syndrome (PCOS) is among the most prevalent endocrinological abnormalities seen in reproductive female bodies posing serious health hazards. The correctness of interpreting this condition depends heavily on the wide spectrum of ... ...

    Abstract Polycystic Ovary Syndrome (PCOS) is among the most prevalent endocrinological abnormalities seen in reproductive female bodies posing serious health hazards. The correctness of interpreting this condition depends heavily on the wide spectrum of associated symptoms and the doctor's expertise, making real-time clinical detection quite challenging. Thus, investigations on computer-aided PCOS detection systems have recently been explored by several researchers worldwide as a potential replacement for manual assessment. This review study's objective is to analyze the relevant research works on computer-assisted methods for automatically identifying PCOS through a systematic literature review (SLR) methodology as well as investigate the research limitations and explore potential future research scopes in this domain. 28 articles have been selected using the PRISMA approach based on a set of inclusion-exclusion criteria for conducting the review. The data synthesis of the selected articles has been conducted using six data exploration themes. As outcomes, the SLR explored the topical association between the studies; their research profiles; objectives; data size, type, and sources; methodologies applied for the detection of PCOS; and lastly the research outcomes along with their evaluation measures and performances. The study also highlights areas for future research directions examining the study gaps to enhance the current efforts for autonomous PCOS identification; such as integrating advanced techniques with the current methods; developing interactive software systems; exploring deep learning and unsupervised machine learning techniques; enhancing datasets and country context; and investigating more unknown factors behind PCOS. Thus, this SLR provides a state-of-the-art paradigm of autonomous PCOS detection which will support significantly efficient clinical assessment, diagnosis and treatment of PCOS.
    Schlagwörter Polycystic ovary syndrome (PCOS) ; Computer-assisted methods ; Systematic literature review (SLR) ; Data synthesis ; Future research scopes ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Thema/Rubrik (Code) 306
    Sprache Englisch
    Erscheinungsdatum 2023-10-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Exploring the dominant features and data-driven detection of polycystic ovary syndrome through modified stacking ensemble machine learning technique

    Sayma Alam Suha / Muhammad Nazrul Islam

    Heliyon, Vol 9, Iss 3, Pp e14518- (2023)

    2023  

    Abstract: Polycystic ovary syndrome (PCOS) is the most frequent endocrinological anomaly in reproductive women that causes persistent hormonal secretion disruption, leading to the formation of numerous cysts within the ovaries and serious health complications. But ...

    Abstract Polycystic ovary syndrome (PCOS) is the most frequent endocrinological anomaly in reproductive women that causes persistent hormonal secretion disruption, leading to the formation of numerous cysts within the ovaries and serious health complications. But the real-world clinical detection technique for PCOS is very critical since the accuracy of interpretations being substantially dependent on the physician's expertise. Thus, an artificially intelligent PCOS prediction model might be a feasible additional technique to the error prone and time-consuming diagnostic technique. In this study, a modified ensemble machine learning (ML) classification approach is proposed utilizing state-of-the-art stacking technique for PCOS identification with patients' symptom data; employing five traditional ML models as base learners and then one bagging or boosting ensemble ML model as the meta-learner of the stacked model. Furthermore, three distinct types of feature selection strategies are applied to pick different sets of features with varied numbers and combinations of attributes. To evaluate and explore the dominant features necessary for predicting PCOS, the proposed technique with five variety of models and other ten types of classifiers is trained, tested and assessed utilizing different feature sets. As outcomes, the proposed stacking ensemble technique significantly enhances the accuracy in comparison to the other existing ML based techniques in case of all varieties of feature sets. However, among various models investigated to categorize PCOS and non-PCOS patients, the stacking ensemble model with ‘Gradient Boosting’ classifier as meta learner outperforms others with 95.7% accuracy while utilizing the top 25 features selected using Principal Component Analysis (PCA) feature selection technique.
    Schlagwörter Polycystic ovary syndrome (PCOS) ; Dominant features ; Machine learning classification ; Stacking ensemble technique ; Science (General) ; Q1-390 ; Social sciences (General) ; H1-99
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2023-03-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Artikel ; Online: COVID-19 and black fungus: Analysis of the public perceptions through machine learning.

    Imtiaz Khan, Nafiz / Mahmud, Tahasin / Nazrul Islam, Muhammad

    Engineering reports : open access

    2021  Band 4, Heft 4, Seite(n) e12475

    Abstract: While COVID-19 is ravaging the lives of millions of people across the globe, a second pandemic "black fungus" has surfaced robbing people of their lives especially people who are recovering from coronavirus. Thus, the objective of this article is to ... ...

    Abstract While COVID-19 is ravaging the lives of millions of people across the globe, a second pandemic "black fungus" has surfaced robbing people of their lives especially people who are recovering from coronavirus. Thus, the objective of this article is to analyze public perceptions through sentiment analysis regarding black fungus during the COVID-19 pandemic. To attain the objective, first, a support vector machine (SVM) model, with an average AUC of 82.75%, was developed to classify user sentiments in terms of anger, fear, joy, and sad. Next, this SVM model was used to predict the class labels of the public tweets (
    Sprache Englisch
    Erscheinungsdatum 2021-11-14
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 2577-8196
    ISSN (online) 2577-8196
    DOI 10.1002/eng2.12475
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel ; Online: Social and structural determinants associated with the prevalence of sexually transmitted infections among female commercial sex workers in Dhaka City, Bangladesh.

    Kawser, Mahbuba / Khan, Md Nazrul Islam / Hossain, Kazi Jahangir / Islam, Sheikh Nazrul

    PLOS global public health

    2024  Band 4, Heft 1, Seite(n) e0002797

    Abstract: Female commercial sex workers (FCSWs) bear higher rates of sexually transmitted infections (STIs) among key populations. The association of structural determinants and STIs among FCSWs was not at the forefront of research earlier in Bangladesh. This ... ...

    Abstract Female commercial sex workers (FCSWs) bear higher rates of sexually transmitted infections (STIs) among key populations. The association of structural determinants and STIs among FCSWs was not at the forefront of research earlier in Bangladesh. This study examined how structural factors correlate with the prevalence of STIs at physical/social/economic/policy levels among FCSWs in Dhaka city. 495 FCSWs were screened for HIV, hepatitis B, and syphilis. Structural variables (Individual risks, high-risk sexual behaviors, work environments) were extracted from the previous multi-level study on FCSWs and analyzed in 2020 to determine whether macro/micro-structural factors were associated with STIs. The prevalence of STIs was 43.6% (95% CI: 39.1%-48). Most (n = 207/495) FCSWs were infected with Syphilis or Hepatitis B, only 1.8% had co-infection, and none was positive for HIV. Multiple logistic regression revealed that 'Individual risk' factors like age (≤18 years, adjusted odds ratio = AOR = .28; 18.1-29.9 years, AOR = .57), years in the sex industry (<1 year AOR = .15; 1-5 years, AOR = .39), and condoms as contraceptives (AOR = 2.7) were significantly associated with STIs. Considering 'High-risk behaviors' like monthly coitus with regular clients (AOR = .33), performing no anal sex ever (AOR = .03), and consistent condom use (AOR = .13) were less likely to be associated with STIs (P<0.05), while the association of ever group sex with STIs reported to double (AOR = 2.1). 'Work environment' like sex on roads/parks/shrines/markets (AOR = 2.6) and ever HIV-testing (AOR = 2.5) were significantly linked with STIs. However, micro-level factors like experiencing forced sex in the past year (AOR = 1.79) and condoms collected from hotel boys (AOR = .34) were significantly associated with STIs in the 'Hierarchical- model' with increasing model-power. 'Micro-structural' determinants predominated over 'Macro/policy-level factors' and profoundly influenced STIs. FCSWs need comprehensive and integrated interventions to promote accurate condom use perception, eliminate risky sexual behaviors, and provide quality reproductive health care. Necessary steps at the policy level are urgently needed to decriminalize commercial sex work.
    Sprache Englisch
    Erscheinungsdatum 2024-01-18
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 2767-3375
    ISSN (online) 2767-3375
    DOI 10.1371/journal.pgph.0002797
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  10. Artikel ; Online: Bioinformatics approach to identify the impacts of microgravity on the development of bone and joint diseases

    Mst Rashida Akhtar / Md Nazrul Islam Mondal / Humayan Kabir Rana

    Informatics in Medicine Unlocked, Vol 38, Iss , Pp 101211- (2023)

    2023  

    Abstract: Background: Experiencing long-term weightlessness during prolonged spaceflight in microgravity environments causes enormous changes in human physiology. Past space missions have revealed that low gravity in space is a serious threat to the development of ...

    Abstract Background: Experiencing long-term weightlessness during prolonged spaceflight in microgravity environments causes enormous changes in human physiology. Past space missions have revealed that low gravity in space is a serious threat to the development of several human diseases, especially bone and joint diseases (BJDs), which have been identified as the major obstacle to long-term space missions. Hence, before sending humans to Mars or long duration spaceflight, it is truly essential to investigate the association of microgravity (MG) on the development of BJDs, however, these are not clearly understood. Methods: To investigate this problem, we developed a computational model to detect the changes in gene expression as potential impacts of MG exposure that may influence the progression of BJDs. We explored gene expression microarray data from tissues affected by MG and BJDs, including Osteoporosis (OP), Osteoarithritis (OA), Osteomalacia (OM), and Osteosarcoma (OS). We constructed gene-disease association networks, identified significant signaling and ontological pathways, and clustered the protein-protein interactions (PPIs) network using neighborhood-based benchmarking and multilayer network topology. We checked the validity of our study using receiver operating characteristic (ROC) and gold benchmark databases, including OMIM, dbGaP, and DisGeNET. Result: We observed that MG exposure altered the expression of many genes, and these genes are also expressed differentially in OP, OA, OM, and OS (21, 19, 19, and 21 respectively). We found five significant biomarker hub proteins (EGFR, CCNB2, Skp2, VDR and SMAD3) from PPIs analysis by evaluating the degree of centrality. The ROC analysis showed an area under the curve (AUC) of 0.844 where the higher value of AUC indicates the result is more significant. Hence, these gene-disease association networks, signaling and ontological pathways, PPIs network of the altered genes and the ROC curve of the findings imply that MG may have significant impacts on the development ...
    Schlagwörter Microgravity ; Osteoporosis ; Osteoarthritis ; Osteomalacia and osteosarcoma ; Computer applications to medicine. Medical informatics ; R858-859.7
    Thema/Rubrik (Code) 570
    Sprache Englisch
    Erscheinungsdatum 2023-01-01T00:00:00Z
    Verlag Elsevier
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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