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  1. Article ; Online: Neurology at Sanjay Gandhi PGI

    Usha Kant Misra / Jayantee Kalita

    Neurology India, Vol 64, Iss 5, Pp 1010-

    Beginning, progress and hope

    2016  Volume 1015

    Abstract: High quality publications, patient care and educational standard have made Sanjay Gandhi ...

    Abstract High quality publications, patient care and educational standard have made Sanjay Gandhi Postgraduate Institute of Medical Sciences (SGPGIMS), Lucknow, India a favored destination for the patients and medical students, for getting treatment and education, respectively. The current article traces the history and milestone of the Department of Neurology, SGPGIMS, Lucknow and summarizes its achievements and facilities. The uniqueness of the department lies in being sensitive to the expectation of the patients, students and its faculty's own aspirations in research, keeping the patient as the center of focus.
    Keywords History ; Lucknow ; milestones ; neurology ; research ; SGPGIMS ; teaching ; training ; Neurology. Diseases of the nervous system ; RC346-429 ; Neurosciences. Biological psychiatry. Neuropsychiatry ; RC321-571 ; Internal medicine ; RC31-1245 ; Medicine ; R
    Language English
    Publishing date 2016-01-01T00:00:00Z
    Publisher Medknow Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: Neurology at Sanjay Gandhi PGI: Beginning, progress and hope.

    Misra, Usha Kant / Kalita, Jayantee

    Neurology India

    2016  Volume 64, Issue 5, Page(s) 1010–1015

    Abstract: High quality publications, patient care and educational standard have made Sanjay Gandhi ...

    Abstract High quality publications, patient care and educational standard have made Sanjay Gandhi Postgraduate Institute of Medical Sciences (SGPGIMS), Lucknow, India a favored destination for the patients and medical students, for getting treatment and education, respectively. The current article traces the history and milestone of the Department of Neurology, SGPGIMS, Lucknow and summarizes its achievements and facilities. The uniqueness of the department lies in being sensitive to the expectation of the patients, students and its faculty's own aspirations in research, keeping the patient as the center of focus.
    MeSH term(s) India ; Neurology
    Language English
    Publishing date 2016-09-14
    Publishing country India
    Document type Journal Article
    ZDB-ID 415522-1
    ISSN 1998-4022 ; 0028-3886
    ISSN (online) 1998-4022
    ISSN 0028-3886
    DOI 10.4103/0028-3886.190247
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 698: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  3. Article: The Time Is Now.

    Misra, Sanjay

    Seminars in interventional radiology

    2023  Volume 40, Issue 2, Page(s) 117–118

    Language English
    Publishing date 2023-06-16
    Publishing country United States
    Document type Editorial
    ZDB-ID 848341-3
    ISSN 1098-8963 ; 0739-9529
    ISSN (online) 1098-8963
    ISSN 0739-9529
    DOI 10.1055/s-0043-57256
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Se 916: Show issues Location:
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  4. Article: The Time Is Now

    Misra, Sanjay

    Seminars in Interventional Radiology

    (Peripheral Arterial Disease)

    2023  Volume 40, Issue 02, Page(s) 117–118

    Series title Peripheral Arterial Disease
    Language English
    Publishing date 2023-04-01
    Publisher Thieme Medical Publishers, Inc.
    Publishing place Stuttgart ; New York
    Document type Article
    ZDB-ID 848341-3
    ISSN 1098-8963 ; 0739-9529
    ISSN (online) 1098-8963
    ISSN 0739-9529
    DOI 10.1055/s-0043-57256
    Database Thieme publisher's database

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    In stock of ZB MED Cologne/Königswinter

    Se 916: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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  5. Article ; Online: Analysis of customer reviews with an improved VADER lexicon classifier

    Kousik Barik / Sanjay Misra

    Journal of Big Data, Vol 11, Iss 1, Pp 1-

    2024  Volume 29

    Abstract: Abstract Background The importance of customer reviews in determining satisfaction has significantly increased in the digital marketplace. Using sentiment analysis in customer reviews has immense potential but encounters challenges owing to domain ... ...

    Abstract Abstract Background The importance of customer reviews in determining satisfaction has significantly increased in the digital marketplace. Using sentiment analysis in customer reviews has immense potential but encounters challenges owing to domain heterogeneity. The sentiment orientation of words varies by domain; however, comprehending domain-specific sentiment reviews remains a significant constraint. Aim This study proposes an Improved VADER (IVADER) lexicon-based classification model to evaluate customer sentiment in multiple domains. The model involves constructing a domain-specific dictionary based on the VADER lexicon and classifying doeviews using the constructed dictionary. Methodology The proposed IVADER model uses data preprocessing, Vectorizer transformation, WordnetLemmatizer-based feature selection, and enhanced VADER Lexicon classifier. Result Compared to existing studies, the IVVADER model accomplished outcomes of accuracy of 98.64%, precision of 97%, recall of 94%, f1-measure of 92%, and less training time of 44 s for classification. Outcome Product designers and business organizations can benefit from the IVADER model to evaluate multi-domain customer sentiment and introduce new products in the competitive online marketplace.
    Keywords Multi-domain sentiment analysis ; Improved VADER (IVADER) ; Customer reviews ; Lexicon-based dictionary ; Computer engineering. Computer hardware ; TK7885-7895 ; Information technology ; T58.5-58.64 ; Electronic computers. Computer science ; QA75.5-76.95
    Subject code 006
    Language English
    Publishing date 2024-01-01T00:00:00Z
    Publisher SpringerOpen
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: The Role of Artificial Intelligence of Things in Achieving Sustainable Development Goals: State of the Art.

    Lampropoulos, Georgios / Garzón, Juan / Misra, Sanjay / Siakas, Kerstin

    Sensors (Basel, Switzerland)

    2024  Volume 24, Issue 4

    Abstract: With the environmental and societal changes, the achievement of sustainable development goals (SDGs) and the realization of sustainability in general is now more important than ever. Through a bibliometric analysis and scientific mapping analysis, this ... ...

    Abstract With the environmental and societal changes, the achievement of sustainable development goals (SDGs) and the realization of sustainability in general is now more important than ever. Through a bibliometric analysis and scientific mapping analysis, this study aims to explore and provide a review regarding the role of artificial intelligence (AI), the Internet of Things (IoT), and artificial intelligence of things (AIoT) in realizing sustainable development and achieving SDGs. AIoT can be defined as the combination of AI with IoT to create more efficient and data-driven interconnected, intelligent, and autonomous IoT systems and infrastructure that use AI methods and algorithms. The analysis involved 9182 documents from Scopus and Web of Science (WoS) from 1989 to 2022. Descriptive statistics of the related documents and the annual scientific production were explored. The most relevant and impactful authors, articles, outlets, affiliations, countries, and keywords were identified. The most popular topics and research directions throughout the years and the advancement of the field and the research focus were also examined. The study examines the results, discusses the main findings, presents open issues, and suggests new research directions. Based on the results of this study, AIoT emerged as an important contributor in ensuring sustainability and in achieving SDGs.
    Language English
    Publishing date 2024-02-07
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2052857-7
    ISSN 1424-8220 ; 1424-8220
    ISSN (online) 1424-8220
    ISSN 1424-8220
    DOI 10.3390/s24041091
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: Guest Editorial: Intelligence for systems and software engineering.

    Hinchey, Mike / Jain, Amit / Kaushik, Manju / Misra, Sanjay

    Innovations in systems and software engineering

    2023  Volume 19, Issue 1, Page(s) 1–4

    Language English
    Publishing date 2023-01-30
    Publishing country England
    Document type News
    ZDB-ID 2195084-2
    ISSN 1614-5054 ; 1614-5046
    ISSN (online) 1614-5054
    ISSN 1614-5046
    DOI 10.1007/s11334-023-00526-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Best Endovascular versus Best Surgical Therapy in Patients with CLI (BEST-CLI) Trial: A Misleading Trial Name.

    Takahashi, Edwin A / Lookstein, Robert A / Misra, Sanjay

    Journal of vascular and interventional radiology : JVIR

    2023  Volume 34, Issue 4, Page(s) 718–719

    MeSH term(s) Humans ; Endovascular Procedures/adverse effects ; Peripheral Arterial Disease/surgery ; Ischemia/therapy ; Treatment Outcome ; Risk Factors ; Limb Salvage ; Critical Illness
    Language English
    Publishing date 2023-01-11
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 1137756-2
    ISSN 1535-7732 ; 1051-0443
    ISSN (online) 1535-7732
    ISSN 1051-0443
    DOI 10.1016/j.jvir.2023.01.005
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3720: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  9. Article ; Online: A deep learning framework for non-functional requirement classification.

    Rahman, Kiramat / Ghani, Anwar / Misra, Sanjay / Rahman, Arif Ur

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 3216

    Abstract: Analyzing, identifying, and classifying nonfunctional requirements from requirement documents is time-consuming and challenging. Machine learning-based approaches have been proposed to minimize analysts' efforts, labor, and stress. However, the ... ...

    Abstract Analyzing, identifying, and classifying nonfunctional requirements from requirement documents is time-consuming and challenging. Machine learning-based approaches have been proposed to minimize analysts' efforts, labor, and stress. However, the traditional approach of supervised machine learning necessitates manual feature extraction, which is time-consuming. This study presents a novel deep-learning framework for NFR classification to overcome these limitations. The framework leverages a more profound architecture that naturally captures feature structures, possesses enhanced representational power, and efficiently captures a broader context than shallower structures. To evaluate the effectiveness of the proposed method, an experiment was conducted on two widely-used datasets, encompassing 914 NFR instances. Performance analysis was performed on the applied models, and the results were evaluated using various metrics. Notably, the DReqANN model outperforms the other models in classifying NFR, achieving precision between 81 and 99.8%, recall between 74 and 89%, and F1-score between 83 and 89%. These significant results highlight the exceptional efficacy of the proposed deep learning framework in addressing NFR classification tasks, showcasing its potential for advancing the field of NFR analysis and classification.
    Language English
    Publishing date 2024-02-08
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-52802-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: National Trends in Complications of Vascular Access for Hemodialysis and Analysis of Racial Disparities Among Patients With End-Stage Renal Disease in the Inpatient Setting.

    Wahood, Waseem / Takahashi, Edwin / Rajan, Dheeraj / Misra, Sanjay

    Kidney international reports

    2023  Volume 8, Issue 6, Page(s) 1162–1169

    Abstract: Introduction: The aim of this study is to assess the trends in access-related complications, as well as the impact of race on these complications, among admitted patients with end-stage kidney disease (ESKD) receiving hemodialysis.: Methods: A ... ...

    Abstract Introduction: The aim of this study is to assess the trends in access-related complications, as well as the impact of race on these complications, among admitted patients with end-stage kidney disease (ESKD) receiving hemodialysis.
    Methods: A retrospective cohort study between 2005 and 2018 was performed using the National Inpatient Sample (NIS). Hospitalizations involving ESKD and hemodialysis were identified. There were 9,246,553 total admissions involving ESKD and hemodialysis, of which 1,167,886 (12.6%) had complications. Trends in complications were assessed and compared among races.
    Results: There was a decreasing trend in rates of mechanical (trend: -0.05% per year;
    Conclusion: Although there was an overall decrease in the trends of dialysis-associated complications requiring hospitalization among ESKD patients receiving hemodialysis, non-White patients have higher odds of complications compared to White patients. The findings in this study emphasize the need for more equitable care for hemodialysis patients.
    Language English
    Publishing date 2023-03-20
    Publishing country United States
    Document type Journal Article
    ISSN 2468-0249
    ISSN (online) 2468-0249
    DOI 10.1016/j.ekir.2023.03.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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