Severity prediction markers in dengue: a prospective cohort study using machine learning approach.

Journal: Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals
PMID: 39556525

Abstract

BACKGROUND: Dengue virus causes illnesses with or without warning indicators for severe complications. There are no clear prognostic signs linked to the disease outcomes.

Authors

  • Aashika Raagavi Jean Pierre
    MGM Advanced Research Institute (MGMARI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, India.
  • Siva Ranganathan Green
    Mahatma Gandhi Medical College and Research Institute (MGMCRI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, 607 402, India.
  • Lokeshmaran Anandaraj
    Department of Community Medicine, Mahatma Gandhi Medical College and Research Institute (MGMCRI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, India.
  • Manikandan Sivaprakasam
    MGM Advanced Research Institute (MGMARI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, India.
  • Anand Kasirajan
    MGM Advanced Research Institute (MGMARI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, India.
  • Panneer Devaraju
    Medical Complex, Indian Council of Medical Research Vector Control Research Centre (ICMR-VCRC), Indira Nagar, Puducherry, India.
  • Srilekha Anumulapuri
    Department of Applied Biology, CSIR-Indian Institute of Chemical Technology (CSIR-IICT), India.
  • Srinivasa Rao Mutheneni
    Bioinformatics Group, Department of Applied Biology, CSIR-Indian Institute of Chemical Technology, Hyderabad-500 007, Andhra Pradesh, India.
  • Agieshkumar Balakrishna Pillai
    MGM Advanced Research Institute (MGMARI), Sri Balaji Vidyapeeth (Deemed to be University), Puducherry, India.

Keywords

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