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  1. Article ; Online: Impact of Analytics Applying Artificial Intelligence and Machine Learning on Enhancing Intensive Care Unit

    Gopal Singh Charan / Ashok Singh Charan / Mandeep Singh Khurana / Gursharn Singh Narang

    Galician Medical Journal, Vol 30, Iss

    A Narrative Review

    2023  Volume 4

    Abstract: Introduction. The intensive care unit (ICU) plays a pivotal role in providing specialized care to patients with severe illnesses or injuries. As a critical aspect of healthcare, ICU admissions demand immediate attention and skilled care from healthcare ... ...

    Abstract Introduction. The intensive care unit (ICU) plays a pivotal role in providing specialized care to patients with severe illnesses or injuries. As a critical aspect of healthcare, ICU admissions demand immediate attention and skilled care from healthcare professionals. However, the intricacies involved in this process necessitate analytical solutions to ensure effective management and optimal patient outcomes. Aim. The aim of this review was to highlight the enhancement of the ICUs through the application of analytics, artificial intelligence, and machine learning. Methods. The review approach was carried out through databases such as MEDLINE, Embase, Web of Science, Scopus, Taylor & Francis, Sage, ProQuest, Science Direct, CINAHL, and Google Scholar. These databases were chosen due to their potential to offer pertinent and comprehensive coverage of the topic while reducing the likelihood of overlooking certain publications. The studies for this review involved the period from 2016 to 2023. Results. Artificial intelligence and machine learning have been instrumental in benchmarking and identifying effective practices to enhance ICU care. These advanced technologies have demonstrated significant improvements in various aspects. Conclusions. Artificial intelligence, machine learning, and data analysis techniques significantly improved critical care, patient outcomes, and healthcare delivery.
    Keywords artificial intelligence ; machine learning ; resource allocation ; icu admission ; clinical decision processes ; analytics ; Medicine ; R
    Subject code 401
    Language English
    Publishing date 2023-11-01T00:00:00Z
    Publisher Ivano-Frankivsk National Medical University
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Clinical Tools and Biochemical Markers to Assess Short-Term Mortality in Acute Exacerbation of Chronic Obstructive Pulmonary Disease (COPD)

    Govind Narayan Srivastava / Manoj Meena / Ankit Patel / Ashok Singh Charan / Mukesh Goyal / Piyush Arora / Ramniwas Meena

    Journal of Clinical and Diagnostic Research, Vol 12, Iss 7, Pp OC16-OC

    2018  Volume 19

    Abstract: Introduction: Acute exacerbation of COPD is one of the leading causes of death worldwide. Aim: This study was aimed to study the role of clinical tools and biochemical markers which have significant impact on short-term mortality in COPD patients ... ...

    Abstract Introduction: Acute exacerbation of COPD is one of the leading causes of death worldwide. Aim: This study was aimed to study the role of clinical tools and biochemical markers which have significant impact on short-term mortality in COPD patients presenting with acute exacerbation. Material and Methods: A total of 50 patients were studied. Patients of age >40 years having COPD exacerbation and presenting with two of the three cardinal features of exacerbation: increase in amount of cough, increase in purulence of cough, increase in baseline dyspnoea which were severe enough to necessitate a hospital admission, were evaluated after admission. A thorough history taking and clinical examination was performed. Along with this, all necessary laboratory parameters were studied. Study population was followed for 30 days. Data were analysed using Chi-square test and multivariate regression analysis using SPSS version 16.0. Results: Out of 50 patients, 30% (15/50) did not survive despite treatment. Parameters such as, history of mechanical ventilation in past one year, low GCS (Glasgow Coma Scale), raised JVP (Juglar Venous Pressure), low pH and raised IL-6 levels were significantly associated with mortality in multivariate analysis (p-value <0.05). Conclusion: Severity of disease as well as severity of present exacerbation was related with short-term mortality. Interleukin-6 is an independent predictor of mortality. Parameters like past history of mechanical ventilation and raised JVP point towards the need of overall better management of COPD patients not only during exacerbations.
    Keywords 30- day mortality ; c- reactive protein ; interleukin- 6 ; Medicine ; R
    Subject code 610
    Language English
    Publishing date 2018-07-01T00:00:00Z
    Publisher JCDR Research and Publications Private Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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