مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

video

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

sound

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Persian Version

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

View:

50
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Download:

24
مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Cites:

Information Journal Paper

Title

Applications of machine learning for hemodialysis nursing cares based on a machine learning algorithm

Pages

  4-9

Abstract

 Nursing Care during Dialysis involves managing symptoms and preventing complications among patients undergoing hemoDialysis or peritoneal Dialysis. In this regard, to improve the quality of Nursing Care during Dialysis, several approaches were developed to enhance hemoDialysis adequacy and prevent complications,however, Machine Learning (ML) emerged as a methodological approach for eval-uating hemoDialysis adequacy and complications. The current study aims to analyze ML approach in predicting and managing hemo-Dialysis by R programming language analysis to provide a therapeutic concept for hemoDialysis management in critical Nursing Care. An R programming language was used to perform the logical analysis of the data. ML algorithms based on usage rate included logistic regression (LR), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Random Forest (RF), Complement Naive Bayes (CNB), Takagi-Sugeno-Kang fuzzy system (G-TSK-FS), k-nearest neighbors' classifier (KNN), Stochastic gradient descent (SGD), Linear Discriminant Analysis (LDA), and Multi-adaptive neural-fuzzy system (MANFIS). Also, the use of ML in Nursing Care during hemoDialysis is categorized into three indications for predicting hemoDialysis adequacy, complications, and vascular access performance. Using ML in hemoDialysis Nursing Care is a growing research interest. The main application areas are the prediction of hemoDialysis adequacy, complications, and vascular access performance. LR and SVM are practical ML algorithms for constructing AI tools to improve hemoDialysis management.

Cites

  • No record.

    • References

  • No record.

    • Cite

    APA: Copy

    ZABIHI, MOHAMMAD REZA, Rashtiani, Samira, Mashayekhi, Yasaman, Amirinia, Fateme, Gholamkar, Vahid, Kor, Samira, & Akhoondian, Mohammad. (2023). Applications of machine learning for hemodialysis nursing cares based on a machine learning algorithm. JOURNAL OF NURSING REPORTS IN CLINICAL PRACTICE, 1(1), 4-9. SID. https://sid.ir/paper/1056506/en

    Vancouver: Copy

    ZABIHI MOHAMMAD REZA, Rashtiani Samira, Mashayekhi Yasaman, Amirinia Fateme, Gholamkar Vahid, Kor Samira, Akhoondian Mohammad. Applications of machine learning for hemodialysis nursing cares based on a machine learning algorithm. JOURNAL OF NURSING REPORTS IN CLINICAL PRACTICE[Internet]. 2023;1(1):4-9. Available from: https://sid.ir/paper/1056506/en

    IEEE: Copy

    MOHAMMAD REZA ZABIHI, Samira Rashtiani, Yasaman Mashayekhi, Fateme Amirinia, Vahid Gholamkar, Samira Kor, and Mohammad Akhoondian, “Applications of machine learning for hemodialysis nursing cares based on a machine learning algorithm,” JOURNAL OF NURSING REPORTS IN CLINICAL PRACTICE, vol. 1, no. 1, pp. 4–9, 2023, [Online]. Available: https://sid.ir/paper/1056506/en

    Related Journal Papers

  • No record.

    • Related Seminar Papers

  • No record.

    • Related Plans

  • No record.

    • Recommended Workshops






    Move to top
    telegram sharing button
    whatsapp sharing button
    linkedin sharing button
    twitter sharing button
    email sharing button
    email sharing button
    email sharing button
    sharethis sharing button