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Related Concept Videos

COPD: Pathogenesis and Clinical Features01:20

COPD: Pathogenesis and Clinical Features

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Chronic obstructive pulmonary disease (COPD) is a group of lung conditions that progressively worsen over time, including chronic bronchitis and emphysema. This cluster of diseases collectively leads to a gradual and irreversible decline in lung function over time.
The primary cause for the onset of COPD is cigarette smoking and exposure to air pollution. These hazardous factors initiate a chain reaction within the lungs, resulting in chronic inflammation, damage to the airways, and a...
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Acute Respiratory Failure-IV01:23

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Respiratory failure can manifest suddenly or gradually, characterized by a rapid decline in PaO2 and a rapid rise in PaCO2. This situation indicates a severe respiratory problem that may quickly become a life-threatening emergency. One of the early signs of hypoxemic Acute Respiratory Failure (ARF) is a change in mental status due to the brain's sensitivity to oxygen levels and changes in acid-base balance. Symptoms such as restlessness, confusion, and agitation suggest inadequate oxygen...
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Pneumonia III: Complications and Assessment01:30

Pneumonia III: Complications and Assessment

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Pneumonia poses the potential for numerous complications that warrant consideration. These complications include the following:
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Pneumonia I: Introduction01:30

Pneumonia I: Introduction

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Pneumonia is an acute respiratory infection that targets the lungs, specifically the alveoli. These tiny air sacs, essential for oxygen exchange, become engorged with pus and fluid, severely hindering breathing, decreasing oxygen absorption, and causing significant pain and discomfort during respiration.
Risk Factors
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Factors Affecting the Risk of Infection01:26

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The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
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Pneumonia II: Pathophysiology01:29

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The pathophysiology of pneumonia involves the following steps:
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Related Experiment Video

Updated: Jun 27, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
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Clinical Features Predicting COVID-19 Severity Risk at the Time of Hospitalization.

Dikshant Sagar1,2, Tanima Dwivedi3, Anubha Gupta4

  • 1Computer Science, Indraprastha Institute of Information Technology - Delhi, Delhi, IND.

Cureus
|May 1, 2024
PubMed
Summary
This summary is machine-generated.

An interpretable artificial intelligence (AI) model, CoSP, accurately predicts COVID-19 severity using patient clinical data upon hospital admission. This tool aids in early intervention and resource allocation for better patient outcomes.

Keywords:
artificial intelligencecovid-19feature selectionimputationlaboratory featuresmachine learningsars-cov-2severity

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Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Epidemiology

Background:

  • The COVID-19 pandemic caused significant global mortality and morbidity.
  • Early identification of high-risk patients is crucial for effective management and resource allocation.
  • Predicting disease severity at hospitalization aids in timely treatment decisions.

Purpose of the Study:

  • To develop an interpretable AI model for predicting COVID-19 severity.
  • To utilize clinical features at hospital admission for severity risk assessment.
  • To categorize patients into asymptomatic, mild, moderate, and severe risk groups.

Main Methods:

  • A dataset of 64 demographic and laboratory features from 7,416 COVID-19 patients was used.
  • A hierarchical AI model, CoSP (COVID-19 severity predictor), was developed.
  • Shapley analysis was employed for model interpretability.

Main Results:

  • CoSP achieved an AUC-ROC of 0.95, AUPRC of 0.91, and weighted F1-score of 0.83.
  • The model identified 19 key features predictive of COVID-19 severity.
  • CoSP demonstrated superior performance and interpretability compared to other ML methods.

Conclusions:

  • The AI-driven CoSP model effectively predicts COVID-19 severity.
  • This tool can facilitate early intervention and personalized treatment strategies.
  • CoSP assists in optimizing hospital resource allocation during pandemics.