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  1. Artikel ; Online: Dismantling the anti-vaxx industry.

    Ahmed, Imran

    Nature medicine

    2021  Band 27, Heft 3, Seite(n) 366

    Mesh-Begriff(e) Attitude to Health ; COVID-19/epidemiology ; COVID-19/prevention & control ; COVID-19/virology ; COVID-19 Vaccines/administration & dosage ; Humans ; SARS-CoV-2/isolation & purification
    Chemische Substanzen COVID-19 Vaccines
    Sprache Englisch
    Erscheinungsdatum 2021-03-15
    Erscheinungsland United States
    Dokumenttyp News
    ZDB-ID 1220066-9
    ISSN 1546-170X ; 1078-8956
    ISSN (online) 1546-170X
    ISSN 1078-8956
    DOI 10.1038/s41591-021-01260-6
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  2. Artikel ; Online: A Case of False Positive Macro-prolactin.

    Siddiqi, Ahmed Imran

    Journal of the College of Physicians and Surgeons--Pakistan : JCPSP

    2021  Band 31, Heft 6, Seite(n) 749

    Mesh-Begriff(e) Humans ; Prolactin ; Protein Binding
    Chemische Substanzen Prolactin (9002-62-4)
    Sprache Englisch
    Erscheinungsdatum 2021-06-02
    Erscheinungsland Pakistan
    Dokumenttyp Case Reports ; Journal Article
    ZDB-ID 2276646-7
    ISSN 1681-7168 ; 1022-386X
    ISSN (online) 1681-7168
    ISSN 1022-386X
    DOI 10.29271/jcpsp.2021.06.749
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Parental Perception of Children’s Online Behaviour

    Ahmed Imran / Nilufa Khanom / Azizur Rahman

    International Journal of Environmental Research and Public Health, Vol 20, Iss 5342, p

    A Study on Ethnic Communities in Australia

    2023  Band 5342

    Abstract: The overwhelming growth of the Internet in all spheres of life poses new challenges for young children growing up in the digital age, with potential short- and long-term ramifications. Parents have an essential role in the development of the attitudes ... ...

    Abstract The overwhelming growth of the Internet in all spheres of life poses new challenges for young children growing up in the digital age, with potential short- and long-term ramifications. Parents have an essential role in the development of the attitudes and behaviour of their children. However, studies indicate that adults are not adequately mitigating the range of cyber risks that children face and that parent-oriented solutions are simply inadequate. This study attempts to fill research gaps in the status and nature of parents’ perceptions of the online use of their children in Australia based on their ethnic background. This study adopted a mixed-method approach, surveying 204 parents from different ethnic communities in Australia followed by 16 in-depth interviews and three focus-group discussions. The results indicate that parents’ perceptions of online risk for children differ based on their ethnicity, cultural adaptation, gender, and age. Parents from multicultural societies are less equipped to deal with cyber threats that their children face and are ill-equipped to monitor and mitigate the risks posed. The results of this study have important policy implications, from deepening our understanding of the nature of the problems to facilitating the development of short- and long-term strategies, appropriate information systems, policy guidelines, and interventions.
    Schlagwörter parental perception ; children cyber safety ; cyber risk ; ethnic communities ; children online ; multi-cultural ; Medicine ; R
    Thema/Rubrik (Code) 360
    Sprache Englisch
    Erscheinungsdatum 2023-03-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel: A Smart-Anomaly-Detection System for Industrial Machines Based on Feature Autoencoder and Deep Learning.

    Ahmed, Imran / Ahmad, Misbah / Chehri, Abdellah / Jeon, Gwanggil

    Micromachines

    2023  Band 14, Heft 1

    Abstract: Machine-health-surveillance systems are gaining popularity in industrial manufacturing systems due to the widespread availability of low-cost devices, sensors, and internet connectivity. In this regard, artificial intelligence provides valuable ... ...

    Abstract Machine-health-surveillance systems are gaining popularity in industrial manufacturing systems due to the widespread availability of low-cost devices, sensors, and internet connectivity. In this regard, artificial intelligence provides valuable assistance in the form of deep learning methods to analyze and process big machine data. In diverse industrial applications, gears are considered a condemning element; many contributing failures occur due to an unexpected breakdown of the gears. In recent research, anomaly-detection and fault-diagnosis systems have been the gears' most contributing content. Thus, in work, we presented a smart deep learning-based system to detect anomalies in an industrial machine. Our system used vibrational analysis methods as a deciding tool for different machinery-maintenance decisions. We will first perform a data analysis of the gearbox data set to analyze the data's insights. By calculating and examining the machine's vibration, we aim to determine the nature and severity of the defect in the machine and hence detect the anomaly. A gearbox's vibration signal holds the fault's signature in the gears, and earlier fault detection of the gearbox is achievable by examining the vibration signal using a deep learning technique. Therefore, we aim to propose a 6-layer autoencoder-based deep learning framework for anomaly detection and fault analysis using a publically available data set of wind-turbine components. The gearbox fault-diagnosis data set is utilized for experimentation, including collecting vibration attributes recorded using SpectraQuest's gearbox fault-diagnostics simulator. Through comprehensive experiments, we have seen that the framework gains good results compared to others, with an overall accuracy of 91%.
    Sprache Englisch
    Erscheinungsdatum 2023-01-07
    Erscheinungsland Switzerland
    Dokumenttyp Journal Article
    ZDB-ID 2620864-7
    ISSN 2072-666X
    ISSN 2072-666X
    DOI 10.3390/mi14010154
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  5. Artikel ; Online: Artificial Intelligence and Blockchain Enabled Smart Healthcare System for Monitoring and Detection of COVID-19 in Biomedical Images.

    Ahmed, Imran / Chehri, Abdellah / Jeon, Gwanggil

    IEEE/ACM transactions on computational biology and bioinformatics

    2023  Band PP

    Abstract: Millions of individuals around the world have been impacted by the ongoing coronavirus outbreak, known as the COVID-19 pandemic. Blockchain, Artificial Intelligence (AI), and other cutting-edge digital and innovative technologies have all offered ... ...

    Abstract Millions of individuals around the world have been impacted by the ongoing coronavirus outbreak, known as the COVID-19 pandemic. Blockchain, Artificial Intelligence (AI), and other cutting-edge digital and innovative technologies have all offered promising solutions in such situations. AI provides advanced and innovative techniques for classifying and detecting symptoms caused by the coronavirus. Additionally, Blockchain may be utilised in healthcare in a variety of ways thanks to its highly open, secure standards, which permit a significant drop in healthcare costs and opens up new ways for patients to access medical services. Likewise, these techniques and solutions facilitate medical experts in the early diagnosis of diseases and later in treatments and sustaining pharmaceutical manufacturing. Therefore, in this work, a smart blockchain and AI-enabled system is presented for the healthcare sector that helps to combat the coronavirus pandemic. To further incorporate Blockchain technology, a new deep learning-based architecture is designed to identify the virus in radiological images. As a result, the developed system may offer reliable data-gathering platforms and promising security solutions, guaranteeing the high quality of COVID-19 data analytics. We created a multi-layer sequential deep learning architecture using a benchmark data set. In order to make the suggested deep learning architecture for the analysis of radiological images more understandable and interpretable, we also implemented the Gradient-weighted Class Activation Mapping (Grad-CAM) based colour visualisation approach to all of the tests. As a result, the architecture achieves a classification accuracy of 96%, thus producing excellent results.
    Sprache Englisch
    Erscheinungsdatum 2023-07-12
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1557-9964
    ISSN (online) 1557-9964
    DOI 10.1109/TCBB.2023.3294333
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel ; Online: Automated Pulmonary Nodule Classification and Detection Using Deep Learning Architectures.

    Ahmed, Imran / Chehri, Abdellah / Jeon, Gwanggil / Piccialli, Francesco

    IEEE/ACM transactions on computational biology and bioinformatics

    2023  Band 20, Heft 4, Seite(n) 2445–2456

    Abstract: Recent advancement in biomedical imaging technologies has contributed to tremendous opportunities for the health care sector and the biomedical community. However, collecting, measuring, and analyzing large volumes of health-related data like images is a ...

    Abstract Recent advancement in biomedical imaging technologies has contributed to tremendous opportunities for the health care sector and the biomedical community. However, collecting, measuring, and analyzing large volumes of health-related data like images is a laborious and time-consuming job for medical experts. Thus, in this regard, artificial intelligence applications (including machine and deep learning systems) help in the early diagnosis of various contagious/ cancerous diseases such as lung cancer. As lung or pulmonary cancer may have no apparent or clear initial symptoms, it is essential to develop and promote a Computer Aided Detection (CAD) system that can support medical experts in classifying and detecting lung nodules at early stages. Therefore, in this article, we analyze the problem of lung cancer diagnosis by classification and detecting pulmonary nodules, i.e., benign and malignant, in CT images. To achieve this objective, an automated deep learning based system is introduced for classifying and detecting lung nodules. In addition, we use novel state-of-the-art detection architectures, including, Faster-RCNN, YOLOv3, and SSD, for detection purposes. All deep learning models are evaluated using a publicly available benchmark LIDC-IDRI data set. The experimental outcomes reveal that the False Positive Rate (FPR) is reduced, and the accuracy is enhanced.
    Sprache Englisch
    Erscheinungsdatum 2023-08-09
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ISSN 1557-9964
    ISSN (online) 1557-9964
    DOI 10.1109/TCBB.2022.3192139
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; Online: Clinically Meaningful Achievement in Outcomes After Subacromial Balloon Spacer Implantation: Letter to the Editor.

    Khatri, Chetan / Ridha, Ali / Ahmed, Imran

    The American journal of sports medicine

    2023  Band 51, Heft 12, Seite(n) NP43–NP44

    Mesh-Begriff(e) Humans ; Rotator Cuff Injuries ; Arthroscopy
    Sprache Englisch
    Erscheinungsdatum 2023-09-30
    Erscheinungsland United States
    Dokumenttyp Letter ; Comment
    ZDB-ID 197482-8
    ISSN 1552-3365 ; 0363-5465
    ISSN (online) 1552-3365
    ISSN 0363-5465
    DOI 10.1177/03635465231184386
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  8. Artikel: Pancreaticoduodenectomy with Para-aortic Lymph Node Dissection for Periampullary Cancer.

    Bhatti, Abu Bakar Hafeez / Dar, Faisal Saud / Ahmed, Imran Nazer

    Indian journal of surgical oncology

    2023  Band 15, Heft Suppl 2, Seite(n) 338–343

    Abstract: There is no consensus on the utility of para-aortic lymph node dissection (PALND) in patients undergoing pancreaticoduodenectomy (PD) for periampullary cancer. The objective of this study was to assess survival in patients who underwent PD with PALND for ...

    Abstract There is no consensus on the utility of para-aortic lymph node dissection (PALND) in patients undergoing pancreaticoduodenectomy (PD) for periampullary cancer. The objective of this study was to assess survival in patients who underwent PD with PALND for pancreatic (PAC) and non-pancreatic (non-PAC) adenocarcinoma. All patients who underwent PD and PALND between 2011 and 2019 were reviewed (
    Sprache Englisch
    Erscheinungsdatum 2023-12-20
    Erscheinungsland India
    Dokumenttyp Journal Article
    ZDB-ID 2568289-1
    ISSN 0976-6952 ; 0975-7651
    ISSN (online) 0976-6952
    ISSN 0975-7651
    DOI 10.1007/s13193-023-01866-x
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  9. Artikel ; Online: Analyzing the Anterior Knee Laxity During Passive Flexion

    Ahmed Imran

    Lecture Notes in Engineering and Computer Science, Vol 2218, Iss 1, Pp 1034-

    2015  Band 1037

    Schlagwörter Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q
    Sprache Englisch
    Erscheinungsdatum 2015-07-01T00:00:00Z
    Verlag Newswood and International Association of Engineers
    Dokumenttyp Artikel ; Online
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  10. Artikel ; Online: Analyzing Anterior Knee Laxity with Isolated Fiber Bundles of Anterior Cruciate Ligament

    Ahmed Imran

    Lecture Notes in Engineering and Computer Science, Vol 2224, Iss 1, Pp 869-

    2015  Band 872

    Schlagwörter Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q
    Sprache Englisch
    Erscheinungsdatum 2015-06-01T00:00:00Z
    Verlag Newswood and International Association of Engineers
    Dokumenttyp Artikel ; Online
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