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  1. Book ; Online ; E-Book: Concept building in fisheries data analysis

    Das, Basant Kumar

    2022  

    Author's details Basant Kumar Das [and five others]
    Keywords Fisheries/Statistical methods ; Fishery management
    Subject code 333.95
    Language English
    Size 1 online resource (278 pages)
    Publisher Springer
    Publishing place Singapore
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 981-19-4411-3 ; 9789811944109 ; 978-981-19-4411-6 ; 9811944105
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: Comment on "An arrested virtuous circle? Higher education and high-technology industries in India", by Rakesh Basant and Partha Mukhopadhyay

    Chandra, Pankaj / Basant, Rakesh / Kumar Mukhopadhyay, Partha

    People, politics, and globalization : Annual World Bank Conference on Development Economics - Global 2009 ; [the 2009 ABCDE ... took place in Cape Town, South Africa, June 9 - 11, 2008] , p. 346-351

    2010  , Page(s) 346–351

    Author's details Pankaj Chandra
    Language English
    Publisher World Bank
    Publishing place Washington, DC
    Document type Article
    ISBN 978-0-8213-7722-2 ; 0-8213-7722-1
    Database ECONomics Information System

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  3. Book ; Online ; E-Book: IoT in Healthcare Systems: Applications, Benefits, Challenges and Case Studies

    Shukla, Piyush Kumar / Patel, Aditya / Shukla, Prashant Kumar / Parashar, Prashant / Tiwari, Basant

    2023  

    Abstract: Implementing new information technologies into the healthcare sector can provide alternatives to managing patients' health records, systems, and improving the quality of care received. This book provides an overview of Internet of Things (IoT) ... ...

    Abstract Implementing new information technologies into the healthcare sector can provide alternatives to managing patients' health records, systems, and improving the quality of care received. This book provides an overview of Internet of Things (IoT) technologies related to the healthcare field and covers the main advantages and disadvantages along with industry case studies.This edited volume covers required standardization and interoperability initiatives, various Artificial Intelligence and Machine Learning algorithms, and discusses how health technology can meet the challenge of improving quality of life regardless of social and financial status, gender, age, and location. The book presents real-time applications and case studies in the fields of engineering, computer science, IoT, and healthcare and provides many examples of successful IoT projects.The target audience for this edited volume includes researchers, practitioners, students, as well as key stakeholders involved in and working on healthcare engineering solutions.
    Keywords Engineering ; Industrial Engineering ; Machine Theory ; Technology & Engineering ; Computers
    Subject code 610.28563
    Language English
    Size 1 online resource (222 p.) , ill
    Publisher CRC Press
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    ISBN 1-000-85886-3 ; 0-367-70215-0 ; 978-1-000-85886-0 ; 978-0-367-70215-1
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  4. Article ; Online: Letter to Editor Regarding "The Current Landscape of Neurosurgical Oncology in Low-Middle-Income Countries (LMIC): Strategies for the Path Forward".

    Misra, Basant Kumar / Ahmadi, Sayedali

    World neurosurgery

    2024  Volume 185, Page(s) 461

    MeSH term(s) Humans ; Developing Countries ; Neurosurgery/trends ; Neurosurgical Procedures/trends ; Medical Oncology ; Brain Neoplasms/surgery ; Surgical Oncology
    Language English
    Publishing date 2024-05-13
    Publishing country United States
    Document type Letter ; Journal Article
    ZDB-ID 2534351-8
    ISSN 1878-8769 ; 1878-8750
    ISSN (online) 1878-8769
    ISSN 1878-8750
    DOI 10.1016/j.wneu.2024.02.054
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Extensive intramural calcification in neonatal ileal atresia: An unusual finding.

    Prasad, Pallavi / Radha, Paturu / Kumar, Basant / Kanneganti, Pujana

    Indian journal of pathology & microbiology

    2023  

    Language English
    Publishing date 2023-07-26
    Publishing country India
    Document type Journal Article
    ZDB-ID 197621-7
    ISSN 0974-5130 ; 0377-4929
    ISSN (online) 0974-5130
    ISSN 0377-4929
    DOI 10.4103/ijpm.ijpm_890_22
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Challenging steroid shift in neuronavigation A clinical study proposal.

    Roy, Amrit / Maschke, Svenja / Warade, Abhijit / Misra, Basant Kumar

    Neurosurgical review

    2023  Volume 47, Issue 1, Page(s) 22

    MeSH term(s) Humans ; Neuronavigation
    Language English
    Publishing date 2023-12-28
    Publishing country Germany
    Document type Letter
    ZDB-ID 6907-3
    ISSN 1437-2320 ; 0344-5607
    ISSN (online) 1437-2320
    ISSN 0344-5607
    DOI 10.1007/s10143-023-02252-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Neurosurgery in Countries with Limited Resources.

    Misra, Basant Kumar

    World neurosurgery

    2018  Volume 114, Page(s) 111–112

    MeSH term(s) Developing Countries ; Health Resources ; Neurosurgeons ; Neurosurgery ; Neurosurgical Procedures
    Language English
    Publishing date 2018
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2534351-8
    ISSN 1878-8769 ; 1878-8750
    ISSN (online) 1878-8769
    ISSN 1878-8750
    DOI 10.1016/j.wneu.2018.03.047
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: A Case Report of High-Risk Percutaneous Coronary Intervention of Left Main Coronary Artery With Cardiogenic Shock.

    Khanal, Suraj / Choudhary, Anil K / Kumar, Basant

    Cureus

    2023  Volume 15, Issue 7, Page(s) e41983

    Abstract: Acute total occlusion of the left main artery is a fatal event and is often accompanied by cardiogenic shock. Patients who experience this event have high mortality rates. Early percutaneous coronary intervention (PCI) with hemodynamic support has proven ...

    Abstract Acute total occlusion of the left main artery is a fatal event and is often accompanied by cardiogenic shock. Patients who experience this event have high mortality rates. Early percutaneous coronary intervention (PCI) with hemodynamic support has proven to improve clinical outcomes for these patients. Here we report a case of a 60-year-old man, who came into our emergency room with an acute anterior wall myocardial infarction accompanied by cardiogenic shock. He had a totally occluded left main artery on coronary angiography, necessitating cardiopulmonary resuscitation, followed by PCI with implantation of a drug-eluting stent along with hemodynamic support. Identification of typical ECG changes is crucial in patients with acute coronary syndrome caused by the occlusion of the left main coronary artery. A quick decision to perform a PCI procedure using early circulatory mechanical devices (intra-aortic balloon pump) is critical to patient survival.
    Language English
    Publishing date 2023-07-16
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.41983
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: A Survey on the Machine Learning Techniques for Automated Diagnosis from Ultrasound Images.

    Mohit, Kumar / Gupta, Rajeev / Kumar, Basant

    Current medical imaging

    2023  

    Abstract: Medical diagnostic systems has recently been very popular and reliable because of possible automatic detections. The machine learning algorithm is evolved as a core tool of computer-aided diagnosis (CAD) for automatic early and accurate disease ... ...

    Abstract Medical diagnostic systems has recently been very popular and reliable because of possible automatic detections. The machine learning algorithm is evolved as a core tool of computer-aided diagnosis (CAD) for automatic early and accurate disease detections. The algorithm follows region of interest (ROI) selection followed by specific feature extractions and selection from medical images. The selected features are then fed to suitable classifiers for disease identification. The machine learning algorithm's performance depends on the features selected and the classifiers employed for the job. This paper reviews different feature extraction selection and classification techniques for CAD from ultrasound images. Ultrasonography (USG), due to its portability and its non-invasive nature, is the prime choice of doctors for prescribing as an imaging test. A survey on the USG imaging based on four major diseases is performed in this paper, whose diagnosis followed by automatic detection. Various techniques applied for feature extraction, selection, and classification by different authors to achieve improved accuracy are tabulated. For medical images, we found texture based gray-level extracted features and SVM (support vector machine) classifiers to be more significant in improving classification accuracy, even achieving 100% accuracy in many research articles. However, many research articles also suggest the importance of student's t-test in improving classification accuracy by selecting significant features from extracted features. The proposed algorithm's accuracy also depends on the quality of medical images, which are frequently degraded by the introduction of noise and artifacts while imaging acquisition. So, challenges in denoising are added in this paper as a separate topic to highlight the role of the machine learning algorithm in removing noise and artifacts from the USG images.
    Language English
    Publishing date 2023-05-29
    Publishing country United Arab Emirates
    Document type Journal Article
    ISSN 1573-4056
    ISSN (online) 1573-4056
    DOI 10.2174/1573405620666230529112655
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Computer-Aided Diagnosis of Various Diseases Using Ultrasonography Images.

    Mohit, Kumar / Gupta, Rajeev / Kumar, Basant

    Current medical imaging

    2023  

    Abstract: This paper is an exhaustive survey of computer-aided diagnosis (CAD) system-based automatic detection of several diseases from ultrasound images. CAD plays a vital role in the automatic and early detection of diseases. Health monitoring, medical database ...

    Abstract This paper is an exhaustive survey of computer-aided diagnosis (CAD) system-based automatic detection of several diseases from ultrasound images. CAD plays a vital role in the automatic and early detection of diseases. Health monitoring, medical database management, and picture archiving systems became very feasible with CAD, assisting radiologists in making decisions over any imaging modality. Imaging modalities mainly rely on machine learning and deep learning algorithms for early and accurate disease detection. CAD approaches are described in this paper in terms of their significant tools; digital image processing (DIP), machine learning (ML), and deep learning (DL). Ultrasonography (USG) already has many advantages over other imaging modalities; therefore, CAD analysis of USG assists radiologists in studying it more clearly, leading to USG application over various body parts. So, in this paper, we have included a review of those major diseases whose detection supports "ML algorithm" based diagnosis from USG images. ML algorithm follows feature extraction, selection, and classification in the required class. The literature survey of these diseases is grouped into the carotid region, transabdominal & pelvic region, musculoskeletal region, and thyroid region. These regions also differ in the types of transducers employed for scanning. Based on the literature survey, we have concluded that texture-based extracted features passed to support vector machine (SVM) classifier results in good classification accuracy. However, the emerging deep learning-based disease classification trend signifies more preciseness and automation for feature extraction and classification. Still, classification accuracy depends on the number of images used for training the model. This motivated us to highlight some of the significant shortcomings of automated disease diagnosis techniques. Research challenges in CAD-based automatic diagnosis system design and limitations in imaging through USG modality are mentioned as separate topics in this paper, indicating future scope or improvement in this field. The success rate of machine learning approaches in USG-based automatic disease detection motivated this review paper to describe different parameters behind machine learning and deep learning algorithms towards improving USG diagnostic performance.
    Language English
    Publishing date 2023-03-06
    Publishing country United Arab Emirates
    Document type Journal Article
    ISSN 1573-4056
    ISSN (online) 1573-4056
    DOI 10.2174/1573405619666230306101012
    Database MEDical Literature Analysis and Retrieval System OnLINE

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