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  1. Book ; Online ; E-Book: Diffuse Cystic Lung Diseases

    Gupta, Nishant / Wikenheiser-Brokamp, Kathryn A. / McCormack, Francis X.

    (Respiratory Medicine,)

    2021  

    Abstract: This book is a comprehensive reference on diffuse cystic lung diseases (DCLDs). DCLDs are a group of pathophysiologically heterogenous processes that are characterized by the presence of multiple spherical or irregularly shaped, thin-walled, air-filled ... ...

    Author's details edited by Nishant Gupta, Kathryn A. Wikenheiser-Brokamp, Francis X. McCormack
    Series title Respiratory Medicine,
    Abstract This book is a comprehensive reference on diffuse cystic lung diseases (DCLDs). DCLDs are a group of pathophysiologically heterogenous processes that are characterized by the presence of multiple spherical or irregularly shaped, thin-walled, air-filled spaces within the pulmonary parenchyma. In recent years, tremendous advancements have been made in these diseases leading to improved understanding of the underlying pathophysiology, and improved outcomes with targeted therapies. The authors, who are leading experts in the field, delineate DCLDs as a separate category distinct from other interstitial lung diseases, and have created this textbook specifically dedicated to this disease group. This book begins with a chapter introducing the definition and classification of DCLDs. Subsequent chapters address the pathogenic mechanisms underlying pulmonary cyst formation and provide a detailed overview of the radiological and pathological features of DCLDs. The common as well as uncommon causes of DCLDs are comprehensively reviewed in individual chapters, as are the varied clinical presentations and extrapulmonary manifestations, and approaches to management and treatment. The book culminates in a final chapter that presents a practical algorithmic approach to diagnosis that progresses from least invasive to most invasive approaches. This textbook provides a one-stop, comprehensive and integrated, clinical, radiologic, and pathologic overview of DCLDs that will be as useful to the practicing clinician as it is to the clinical investigator. .
    Keywords Respiratory organs/Diseases ; Pneumology
    Subject code 616.24
    Language English
    Size 1 online resource (XIII, 380 p. 119 illus., 57 illus. in color.)
    Edition 1st ed. 2021.
    Publisher Springer International Publishing ; Imprint: Humana
    Publishing place Cham
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 3-030-63365-9 ; 3-030-63364-0 ; 978-3-030-63365-3 ; 978-3-030-63364-6
    DOI 10.1007/978-3-030-63365-3
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: Lymphangioleiomyomatosis: No Longer Ultra-rare.

    Gupta, Nishant / Johnson, Simon R

    American journal of respiratory and critical care medicine

    2024  Volume 209, Issue 4, Page(s) 358–359

    MeSH term(s) Humans ; Lymphangioleiomyomatosis/diagnostic imaging ; Lung ; Lung Neoplasms/diagnostic imaging
    Language English
    Publishing date 2024-01-08
    Publishing country United States
    Document type Editorial
    ZDB-ID 1180953-x
    ISSN 1535-4970 ; 0003-0805 ; 1073-449X
    ISSN (online) 1535-4970
    ISSN 0003-0805 ; 1073-449X
    DOI 10.1164/rccm.202312-2254ED
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Artificial Intelligence in Primary Healthcare

    Nishant Gupta / Rajeev Gupta

    RUHS Journal of Health Sciences (2023)

    Listening, Learning and Talking Computers

    2023  

    Abstract: ... Not ... ...

    Abstract Not Available
    Keywords Not Available ; Medicine ; R
    Language English
    Publishing date 2023-07-01T00:00:00Z
    Publisher Sonali Sharma on behalf of Rajasthan University of Health Sciences
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Recommendations for the diagnosis and management of LAM: Looking towards the future.

    Gupta, Nishant / McCarthy, Cormac

    Respiratory medicine and research

    2023  Volume 83, Page(s) 101016

    MeSH term(s) Humans ; Sirolimus ; Lymphangioleiomyomatosis
    Chemical Substances Sirolimus (W36ZG6FT64)
    Language English
    Publishing date 2023-04-21
    Publishing country France
    Document type Editorial
    ISSN 2590-0412
    ISSN (online) 2590-0412
    DOI 10.1016/j.resmer.2023.101016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Segmentation-Based Fusion of CT and MR Images.

    Gupta, Pragya / Jain, Nishant

    Journal of imaging informatics in medicine

    2024  

    Abstract: In this paper, a segmentation-based image fusion method is proposed for the fusion of MR and CT images to obtain a high contrast fused image that contains complementary information from both input images. The proposed method uses the fuzzy C-mean method ... ...

    Abstract In this paper, a segmentation-based image fusion method is proposed for the fusion of MR and CT images to obtain a high contrast fused image that contains complementary information from both input images. The proposed method uses the fuzzy C-mean method to extract information about the skull from the CT image. This skull information is used to extract soft tissue information from the MR image. Both the skull information and the soft tissue information are then fused using the fusion rule. The efficiency of the proposed method over other state-of-the-art fusion methods is analyzed and compared using qualitative and quantitative analysis methods. Qualitative analysis shows the improvement in the contrast between the bone and the soft tissue using the proposed method over other state-of-the-art methods without introducing any artifacts or distortions. Classical and gradient-based quantitative analysis also show significant improvement in the fused image obtained using the proposed method over the five state-of-the-art methods. The percentage improvement in the standard deviation, average gradient, entropy, spatial frequency, QABF, and LABF of the proposed method over the best value obtained by the five state-of-the-art methods is 27.11%, 12.06%, 23.64%, 11.30%, 5.59%, and 13.70% respectively.
    Language English
    Publishing date 2024-03-25
    Publishing country Switzerland
    Document type Journal Article
    ISSN 2948-2933
    ISSN (online) 2948-2933
    DOI 10.1007/s10278-024-01078-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Analyzing the Concatenation Between Ethics and Knowledge Culture in Indian IT Sector

    Nishant Gaur / Vikas Gupta

    SAGE Open, Vol

    2023  Volume 13

    Abstract: In this globally competitive environment, ethics has become the major area of concern for organizations to eliminate the issues that arise in knowledge sharing. Knowledge is considered to provide a competitive edge to individuals and organizations. This ... ...

    Abstract In this globally competitive environment, ethics has become the major area of concern for organizations to eliminate the issues that arise in knowledge sharing. Knowledge is considered to provide a competitive edge to individuals and organizations. This is especially true for industries engaged in the Information and Technology sector. In accordance with the above notion, the current study aims at assessing the role of ethics as a catalyst in affecting knowledge sharing in Indian IT organizations. For this purpose, the study adopted a self-developed questionnaire that was addressed to employees engaged in the IT sector of India. The study utilized SPSS and AMOS to outline the relationship between Ethics and Knowledge Sharing. The findings of the study revealed that the PRIMES model has a direct impact on knowledge creation culture, knowledge-sharing culture, and knowledge storage and knowledge application culture. Moreover, it was also revealed that ethical issues have a negative impact on the three constructs of knowledge sharing that is, knowledge creation culture; knowledge sharing culture; and knowledge storage and knowledge application culture. Personality traits and other constructs of the PRIMES model cannot be controlled by the organization. However, ethical issues can be curbed to enhance the knowledge sharing culture. Prior research has not empirically tested the role of PRIMES model and ethics on knowledge sharing culture.
    Keywords History of scholarship and learning. The humanities ; AZ20-999 ; Social Sciences ; H
    Subject code 306
    Language English
    Publishing date 2023-12-01T00:00:00Z
    Publisher SAGE Publishing
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Typhoid Conjugate Vaccine: A Boon for Endemic Regions.

    Agarwal, Nitesh / Gupta, Naveen / Nishant / H S, Surendra / Dutta, Trayambak / Mahajan, Manish

    Cureus

    2024  Volume 16, Issue 3, Page(s) e56454

    Abstract: Typhoid fever has the highest disease burden in countries in low- and middle-income countries, primarily located in Asia and Sub-Saharan Africa. Previous typhoid vaccines such as the live attenuated typhoid (Ty21a) vaccine and Vi (virulence) capsular ... ...

    Abstract Typhoid fever has the highest disease burden in countries in low- and middle-income countries, primarily located in Asia and Sub-Saharan Africa. Previous typhoid vaccines such as the live attenuated typhoid (Ty21a) vaccine and Vi (virulence) capsular polysaccharide vaccine had the limitation that they could not be administered with other standard childhood immunizations and were ineffective in children under two years of age. To address these shortcomings of the previous vaccines, typhoid conjugate vaccines (TCVs) were developed and prequalified by the World Health Organization. Cross-reacting material and tetanus toxoid are widely used as carrier proteins in TCVs. According to various studies, TCV has higher efficacy, has a more extended protection period, and is safe and immunogenic in infants as young as six months. This review article aims to comprehensively appraise the data available on TCVs' efficacy, duration of protection, safety, and immunogenicity in endemic regions.
    Language English
    Publishing date 2024-03-19
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.56454
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Implementation of the deep learning method for signal detection in massive-MIMO-NOMA systems.

    Kumar, Arun / Gaur, Nishant / Gupta, Manoj / Nanthaamornphong, Aziz

    Heliyon

    2024  Volume 10, Issue 3, Page(s) e25374

    Abstract: The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple access (O-NOMA) systems that are caused by signals that overlap and interfere with each other. NOMA increases the optical framework's spectrum efficiency, allowing ... ...

    Abstract The deep learning method (DLM) is one way to fix issues in optical nonorthogonal multiple access (O-NOMA) systems that are caused by signals that overlap and interfere with each other. NOMA increases the optical framework's spectrum efficiency, allowing several users to share the same time-frequency resources. However, NOMA-DLM-based detection's complicated interference patterns and variable channel conditions are challenging for conventional detection methods to manage. By utilizing deep neural networks' advantages, these methods are able to overcome these challenges and improve detection performance. An overview of the main features and advantages of DLM detection in massive multiple input and output (M-MIMO) O-NOMA systems is given in this article. It describes the essential elements, such as the training procedure and the network design. In order to process the sent symbols or decode data streams, DLM networks are built to process the incoming signal, power allocation coefficients, and extra information. Gradient descent optimization is used to update the network parameters iteratively while training the network, and a diverse and representative dataset is created. Additionally, the challenges of detecting deep learning in O-NOMA systems are examined. It recognizes that in order to get the best results, significant computational resources, a large amount of training data, and careful model design are required. It looks at and compares the 16 × 16, 32 × 32, and 64 × 64 M-MIMO-NOMA models in terms of bit error rate (BER), complexity, and power spectral density (PSD). The suggested DLM algorithms have been demonstrated to perform better than traditional methods by achieving an excellent BER of 10-3 at 4.1 dB and PSD (-2500) performance with low complexity.
    Language English
    Publishing date 2024-02-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e25374
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Bayesian two-stage modeling of longitudinal and time-to-event data with an integrated fractional Brownian motion covariance structure.

    Palipana, Anushka / Song, Seongho / Gupta, Nishant / Szczesniak, Rhonda

    Biometrics

    2024  Volume 80, Issue 1

    Abstract: It is difficult to characterize complex variations of biological processes, often longitudinally measured using biomarkers that yield noisy data. While joint modeling with a longitudinal submodel for the biomarker measurements and a survival submodel for ...

    Abstract It is difficult to characterize complex variations of biological processes, often longitudinally measured using biomarkers that yield noisy data. While joint modeling with a longitudinal submodel for the biomarker measurements and a survival submodel for assessing the hazard of events can alleviate measurement error issues, the continuous longitudinal submodel often uses random intercepts and slopes to estimate both between- and within-patient heterogeneity in biomarker trajectories. To overcome longitudinal submodel challenges, we replace random slopes with scaled integrated fractional Brownian motion (IFBM). As a more generalized version of integrated Brownian motion, IFBM reasonably depicts noisily measured biological processes. From this longitudinal IFBM model, we derive novel target functions to monitor the risk of rapid disease progression as real-time predictive probabilities. Predicted biomarker values from the IFBM submodel are used as inputs in a Cox submodel to estimate event hazard. This two-stage approach to fit the submodels is performed via Bayesian posterior computation and inference. We use the proposed approach to predict dynamic lung disease progression and mortality in women with a rare disease called lymphangioleiomyomatosis who were followed in a national patient registry. We compare our approach to those using integrated Ornstein-Uhlenbeck or conventional random intercepts-and-slopes terms for the longitudinal submodel. In the comparative analysis, the IFBM model consistently demonstrated superior predictive performance.
    MeSH term(s) Humans ; Female ; Bayes Theorem ; Nonoxynol ; Probability ; Biomarkers ; Disease Progression
    Chemical Substances Nonoxynol (26027-38-3) ; Biomarkers
    Language English
    Publishing date 2024-03-14
    Publishing country England
    Document type Journal Article
    ZDB-ID 213543-7
    ISSN 1541-0420 ; 0099-4987 ; 0006-341X
    ISSN (online) 1541-0420
    ISSN 0099-4987 ; 0006-341X
    DOI 10.1093/biomtc/ujae011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Primary Spontaneous Pneumothorax: Looking Beyond the Usual.

    Gupta, Nishant

    Academic emergency medicine : official journal of the Society for Academic Emergency Medicine

    2018  Volume 25, Issue 4, Page(s) 470–472

    Language English
    Publishing date 2018-01-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1329813-6
    ISSN 1553-2712 ; 1069-6563
    ISSN (online) 1553-2712
    ISSN 1069-6563
    DOI 10.1111/acem.13363
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