Neuro-Fuzzy Framework for Community-Acquired Pneumonia Severity Diagnosis

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@article{1702616,
      author = {Olukemi Victoria Olatunde, Olumide Sunday Adewale, Oladunni Abosede Daramola},
      title = {Neuro-Fuzzy Framework for Community-Acquired Pneumonia Severity Diagnosis},
      journal = {Iconic Research And Engineering Journals},
      year = {2021},
      volume = {4},
      number = {9},
      pages = {34-39},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702616.pdf},
      abstract = {Community-Acquired Pneumonia (CAP) is one of the major life threatening diseases, a syndrome in which acute infection of the lungs develops in a patient within 14 days before the onset of the symptoms. It is one of the most common infectious diseases and a significant cause of mortality and morbidity worldwide before COVID-19 outbreak and often misdiagnosed and inappropriately treated, which also contribute to economic backwardness, mostly within developing nations. Timely and accurate diagnosis of CAP is required to reduce mortality and morbidity rate. Major contributors to high prevalence of mortality of CAP are late diagnosis, insufficient medical personnel and exorbitant treatment cost. This paper presented a proposed neuro-fuzzy framework for diagnosis of CAP severity level, this will aid medical personnel in determining the urgency and type of treatment needed and consequently reduce if not totally eradicate mortality and morbidity rates as a result of CAP.},
      keywords = {Community-Acquired Pneumonia, Neuro-fuzzy, diagnosis, Severity Level},
      month = {March},
      doi = {https://doi.org/10.64388/IREV4I9-1702616}
  }