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Related Concept Videos

Types of Fever01:25

Types of Fever

349
Fever can be triggered by several factors, including infections, nervous system disorders, certain cancers, blood diseases like leukemia, embolism, thrombosis, heatstroke, dehydration, surgical trauma, crushing injuries, and allergic reactions.
Here are the different types of fever:
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Methods of Classification and Identification01:28

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
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Increased Body Temperature01:25

Increased Body Temperature

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A body temperature above  38°C  (100.4 °F) is known as fever or pyrexia, and a person with fever is termed 'febrile.' Typically, the hypothalamus, a part of the brain that acts as the body's thermostat, regulates body temperature through a thermoregulatory setpoint. It receives signals from cold and warm thermal receptors throughout the body and adjusts the body's temperature accordingly. Fever occurs when this hypothalamic setpoint is altered, usually in...
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Microbial Classification System01:24

Microbial Classification System

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Classification is the process of organizing organisms into hierarchically inclusive groups based on their phenotypic similarities or evolutionary relationships. A species comprises one or more strains, and closely related species are grouped into genera. Genera are further classified into families, families into orders, orders into classes, and so forth, up to the domain level, which is the broadest taxonomic rank derived from a combination of phenotypic and genotypic data.The nomenclature of...
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Methods of reducing fever01:22

Methods of reducing fever

643
The signs and symptoms of fever include hot and dry skin, flushed face, thirst, muscle aches, anorexia, headache, tachycardia, tachypnea, and fatigue. Elevated body temperature is reduced using two methods: pharmacological and nonpharmacological. Proper identification and treatment of the root cause of a fever is of utmost importance.
Pharmacological Methods of Reducing Fever:
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A Pathological Diagnosis Method for Fever of Unknown Origin Based on Multipath Hierarchical Classification: Model

Jianchao Du1, Junyao Ding1, Yuan Wu2

  • 1School of Telecommunications Engineering, Xidian University, Xi'an, China.

JMIR Formative Research
|December 9, 2024
PubMed
Summary

This study introduces a novel machine learning algorithm for diagnosing fever of unknown origin (FUO). The multipath hierarchical classification model with feature selection achieved high accuracy, aiding physicians in identifying FUO causes.

Keywords:
FUOdiagnosticfeature selectionfever of unknown originhierarchical classificationintelligent diagnosismachine learningmodel designprediction modelvalidation

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Area of Science:

  • Medical informatics
  • Machine learning applications
  • Diagnostic algorithms

Background:

  • Fever of unknown origin (FUO) presents diagnostic challenges due to diverse causes and potential misdiagnosis.
  • Machine learning offers a promising approach to analyze complex patient data for FUO diagnosis.

Purpose of the Study:

  • To develop a multipath hierarchical classification algorithm for diagnosing FUO.
  • To enhance diagnostic performance through an integrated feature selection mechanism.

Main Methods:

  • Utilized a dataset of FUO patients from 2011-2020.
  • Designed a 3-layer hierarchical classification structure based on etiology.
  • Incorporated a feature selection mechanism and conducted ablation and comparison experiments.

Main Results:

  • The optimal model achieved 76.08% accuracy with 3% middle paths and 25% feature selection.
  • The proposed model outperformed existing methods in both feature selection and hierarchical classification.
  • Specific diagnoses like brucellosis (100%), liver abscess, viral infection, and lymphoma (>80%) showed high accuracy.

Conclusions:

  • A novel multipath feature selection and hierarchical classification model for FUO diagnosis was successfully designed and evaluated.
  • This machine learning model aids physicians by improving the accuracy and efficiency of FUO diagnosis.