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  1. Article ; Online: Ideas, Concerns, and Expectations for peace in the Middle East.

    Aftab, Rabia

    The British journal of general practice : the journal of the Royal College of General Practitioners

    2023  Volume 73, Issue 737, Page(s) 555

    MeSH term(s) Humans ; Motivation ; Middle East ; Social Conditions
    Language English
    Publishing date 2023-11-30
    Publishing country England
    Document type Journal Article
    ZDB-ID 1043148-2
    ISSN 1478-5242 ; 0035-8797 ; 0960-1643
    ISSN (online) 1478-5242
    ISSN 0035-8797 ; 0960-1643
    DOI 10.3399/bjgp23X735705
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The enigma of empathy.

    Aftab, Rabia

    The British journal of general practice : the journal of the Royal College of General Practitioners

    2021  Volume 71, Issue 711, Page(s) 464

    MeSH term(s) Empathy ; Humans
    Language English
    Publishing date 2021-09-30
    Publishing country England
    Document type Journal Article
    ZDB-ID 1043148-2
    ISSN 1478-5242 ; 0035-8797 ; 0960-1643
    ISSN (online) 1478-5242
    ISSN 0035-8797 ; 0960-1643
    DOI 10.3399/bjgp21X717269
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Coronavirus (COVID-19)

    Aftab, Rabia

    InnovAiT: Education and inspiration for general practice

    2020  Volume 13, Issue 10, Page(s) 622–624

    Keywords covid19
    Language English
    Publisher SAGE Publications
    Publishing country us
    Document type Article ; Online
    ZDB-ID 2416002-7
    ISSN 1755-7399 ; 1755-7380
    ISSN (online) 1755-7399
    ISSN 1755-7380
    DOI 10.1177/1755738020938394
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Caregiver Strain and its Associated Factors in Autism Spectrum Disorder in Karachi, Pakistan.

    Aftab, Rabeeka / Pirani, Shahina / Mansoor, Marium / Nadeem, Tania

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

    2023  Volume 33, Issue 7, Page(s) 784–788

    Abstract: Objective: To determine the frequency of caregiver strain and its associated factors in Autism Spectrum Disorder (ASD) at a tertiary care teaching hospital in Karachi, Pakistan.: Study design: An analytical cross-sectional study. Place and Duration ... ...

    Abstract Objective: To determine the frequency of caregiver strain and its associated factors in Autism Spectrum Disorder (ASD) at a tertiary care teaching hospital in Karachi, Pakistan.
    Study design: An analytical cross-sectional study. Place and Duration of the Study: Psychiatry inpatient and outpatient units at The Aga Khan University Hospital, Karachi, Pakistan, from December 2018 to December 2019.
    Methodology: The study participants were caregivers of ASD. Data were collected from the inpatient and outpatient departments using Caregiver Strain Questionnaire (CGSQ), and a demographic questionnare. Data were analysed using descriptive and inferential analysis.
    Results: A total of 76 caregivers participated in the study. Among them, 61 (80.3%) were females and 15 (19.7%) were males, with mean age of 37.09±6.91 years. The overall caregiver strain (both subjective and objective) was reported to be severe by 11.8%, moderate by 47.4% and low by 40.8%. About 50% of the participants had a low objective strain on CGSQ whereas 59.2% of the participants subjectively felt the strain to be at moderate level. An association was found between the gender of the participants and subjective strain (p=0.016), and gender with internalised subjective strain (p =0.002).
    Conclusion:  Parenting of a child with ASD involves challenges and demands support. This study supports the recommendation that the caregivers need access to appropriate means to channelize their strain and manage their role productively.
    Key words: Autism, ASD, Stress, Burden, Caregiver, CGSQ, Pakistan.
    MeSH term(s) Male ; Child ; Female ; Humans ; Adult ; Autism Spectrum Disorder/epidemiology ; Caregivers ; Pakistan/epidemiology ; Cross-Sectional Studies ; Surveys and Questionnaires
    Language English
    Publishing date 2023-07-04
    Publishing country Pakistan
    Document type Journal Article
    ZDB-ID 2276646-7
    ISSN 1681-7168 ; 1022-386X
    ISSN (online) 1681-7168
    ISSN 1022-386X
    DOI 10.29271/jcpsp.2023.07.784
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Bacterial sensitivity to chlorhexidine and povidone-iodine antiseptics over time: a systematic review and meta-analysis of human-derived data.

    Aftab, Raiyyan / Dodhia, Vikash H / Jeanes, Christopher / Wade, Ryckie G

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 347

    Abstract: Surgical site infection (SSI) is the most common complication of surgery, increasing healthcare costs and hospital stay. Chlorhexidine (CHX) and povidone-iodine (PVI) are used for skin antisepsis, minimising SSIs. There is concern that  resistance to ... ...

    Abstract Surgical site infection (SSI) is the most common complication of surgery, increasing healthcare costs and hospital stay. Chlorhexidine (CHX) and povidone-iodine (PVI) are used for skin antisepsis, minimising SSIs. There is concern that  resistance to topical biocides may be emergeing, although the potential clinical implications remain unclear. The objective of this systematic review was to determine whether the minimum bactericidal concentration (MBC) of topical preparations of CHX or PVI have changed over time, in microbes relevant to SSI. We included studies reporting the MBC of laboratory and clinical isolates of common microbes to CHX and PVI. We excluded studies using non-human samples and antimicrobial solvents or mixtures with other active substances. MBC was pooled in random effects meta-analyses and the change in MBC over time was explored using meta-regression. Seventy-nine studies were included, analysing 6218 microbes over 45 years. Most studies investigated CHX (93%), with insufficient data for meta-analysis of PVI. There was no change in the MBC of CHX to Staphylococci or Streptococci over time. Overall, we find no evidence of reduced susceptibility of common SSI-causing microbes to CHX over time. This provides reassurance and confidence in the worldwide guidance that CHX should remain the first-choice agent for surgical skin antisepsis.
    MeSH term(s) Humans ; Anti-Infective Agents, Local/pharmacology ; Povidone-Iodine/pharmacology ; Chlorhexidine/pharmacology ; Preoperative Care ; Surgical Wound Infection/prevention & control
    Chemical Substances Anti-Infective Agents, Local ; Povidone-Iodine (85H0HZU99M) ; Chlorhexidine (R4KO0DY52L)
    Language English
    Publishing date 2023-01-07
    Publishing country England
    Document type Meta-Analysis ; Systematic Review ; Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-022-26658-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Graph Neural Network for representation learning of lung cancer.

    Aftab, Rukhma / Qiang, Yan / Zhao, Juanjuan / Urrehman, Zia / Zhao, Zijuan

    BMC cancer

    2023  Volume 23, Issue 1, Page(s) 1037

    Abstract: The emergence of image-based systems to improve diagnostic pathology precision, involving the intent to label sets or bags of instances, greatly hinges on Multiple Instance Learning for Whole Slide Images(WSIs). Contemporary works have shown excellent ... ...

    Abstract The emergence of image-based systems to improve diagnostic pathology precision, involving the intent to label sets or bags of instances, greatly hinges on Multiple Instance Learning for Whole Slide Images(WSIs). Contemporary works have shown excellent performance for a neural network in MIL settings. Here, we examine a graph-based model to facilitate end-to-end learning and sample suitable patches using a tile-based approach. We propose MIL-GNN to employ a graph-based Variational Auto-encoder with a Gaussian mixture model to discover relations between sample patches for the purposes to aggregate patch details into an individual vector representation. Using the classical MIL dataset MUSK and distinguishing two lung cancer sub-types, lung cancer called adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), we exhibit the efficacy of our technique. We achieved a 97.42% accuracy on the MUSK dataset and a 94.3% AUC on the classification of lung cancer sub-types utilizing features.
    MeSH term(s) Humans ; Lung Neoplasms/diagnosis ; Carcinoma, Non-Small-Cell Lung ; Adenocarcinoma ; Carcinoma, Squamous Cell ; Neural Networks, Computer
    Language English
    Publishing date 2023-10-26
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041352-X
    ISSN 1471-2407 ; 1471-2407
    ISSN (online) 1471-2407
    ISSN 1471-2407
    DOI 10.1186/s12885-023-11516-8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Study on the Prediction Method of Long-term Benign and Malignant Pulmonary Lesions Based on LSTM.

    Liu, Xindong / Wang, Mengnan / Aftab, Rukhma

    Frontiers in bioengineering and biotechnology

    2022  Volume 10, Page(s) 791424

    Abstract: In order to more accurately and comprehensively characterize the changes and development rules of lesion characteristics in pulmonary medical images in different periods, the study was conducted to predict the evolution of pulmonary nodules in the ... ...

    Abstract In order to more accurately and comprehensively characterize the changes and development rules of lesion characteristics in pulmonary medical images in different periods, the study was conducted to predict the evolution of pulmonary nodules in the longitudinal dimension of time, and a benign and malignant prediction model of pulmonary lesions in different periods was constructed under multiscale three-dimensional (3D) feature fusion. According to the sequence of computed tomography (CT) images of patients at different stages, 3D interpolation was conducted to generate 3D lung CT images. The 3D features of different size lesions in the lungs were extracted using 3D convolutional neural networks for fusion features. A time-modulated long short-term memory was constructed to predict the benign and malignant lesions by using the improved time-length memory method to learn the feature vectors of lung lesions with temporal and spatial characteristics in different periods. The experiment shows that the area under the curve of the proposed method is 92.71%, which is higher than that of the traditional method.
    Language English
    Publishing date 2022-03-02
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2719493-0
    ISSN 2296-4185
    ISSN 2296-4185
    DOI 10.3389/fbioe.2022.791424
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Preparedness of Undergraduate Medical Students for Online Learning.

    Ansari, Tahir / Aftab, Rabia / Ahmed, Masood

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

    2022  Volume 34, Issue 3, Page(s) 343–347

    Abstract: Objective: To determine the preparedness of the first-year undergraduate medical students toward online learning.: Study design: Descriptive study. Place and Duration of the Study: The study was conducted at the Department of Medical Education, ... ...

    Abstract Objective: To determine the preparedness of the first-year undergraduate medical students toward online learning.
    Study design: Descriptive study. Place and Duration of the Study: The study was conducted at the Department of Medical Education, Fazaia Ruth Pfau Medical College, Air University, Karachi, Pakistan, from September to December 2021.
    Methodology: The study participants were first-year undergraduate medical students. A pre-validated instrument developed by Lesley University in July 2014 named 'The Prospective Online Student Readiness Questionnaire' was used. Permission was taken via email. The questionnaire has two parts. Section A consists of the demographic characteristics. Section B evaluates the student's readiness for online learning.
    Results: Data from 81 respondents were collected through an online questionnaire. The results showed that internet self-efficacy, self directed learning, learner control, and learner style have a positive and significant relationship with students' preparedness for e-learning.
    Conclusion: Students are aware of the use of technology. They could be more comfortable working independently at the beginning of the course. Online environment and communication for learning purposes with peers also appear to be weak areas. Students prefer visual aids for learning, and very few enjoy raising their hands in class to answer questions. They are confident in social communications but need more confidence in using online tools for effective online communication and posting questions on online forums during discussions.
    Key words: Medical students, Online learning, preparedness, Self-efficacy, Self-directed learning.
    MeSH term(s) Humans ; Students, Medical ; Education, Distance/methods ; Prospective Studies ; Education, Medical, Undergraduate/methods ; Learning
    Language English
    Publishing date 2022-09-14
    Publishing country Pakistan
    Document type Journal Article
    ZDB-ID 2276646-7
    ISSN 1681-7168 ; 1022-386X
    ISSN (online) 1681-7168
    ISSN 1022-386X
    DOI 10.29271/jcpsp.2024.03.343
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: Lower Limb Serratia marcescens Necrotizing Fasciitis Complicated by Nosocomial COVID-19.

    Aftab, Raiyyan / Tay, Jing Qin / Sauvé, Philip / Pandya, Ankur / Ng, Zhi Yang

    Cureus

    2023  Volume 15, Issue 1, Page(s) e33453

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

    Abstract Serratia marcescens
    Language English
    Publishing date 2023-01-06
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.33453
    Database MEDical Literature Analysis and Retrieval System OnLINE

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