AIMC Topic: Pneumonia

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Predictive value of machine learning for radiation pneumonitis and checkpoint inhibitor pneumonitis in lung cancer patients: a systematic review and meta-analysis.

Scientific reports
Some studies have developed machine learning (ML) models for the prediction of pneumonitis following immunotherapy and radiotherapy for patients with lung cancer (LC). However, the prediction accuracy of these models remains a topic of debate. Thus, ...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Scientific reports
Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elevate mortality rates. Consequently, early prevention and identification of this condition are crucial...

Gradual poisoning of a chest x-ray convolutional neural network with an adversarial attack and AI explainability methods.

Scientific reports
Given artificial intelligence's transformative effects, studying safety is important to ensure it is implemented in a beneficial way. Convolutional neural networks are used in radiology research for prediction but can be corrupted through adversarial...

Predicting 14-day readmission in middle-aged and elderly patients with pneumonia using emergency department data: a multicentre retrospective cohort study with a survival machine learning approach.

BMJ open
OBJECTIVES: Unplanned pneumonia readmissions increase patient morbidity, mortality and healthcare costs. Among pneumonia patients, the middle-aged and elderly (≥45 years old) have a significantly higher risk of readmission compared with the young. Gi...

Development and validation of a nomogram for differentiating immune checkpoint inhibitor-related pneumonitis from pneumonia in patients undergoing immunochemotherapy: a multicenter, real-world, retrospective study.

Frontiers in immunology
BACKGROUND: Immune Checkpoint Inhibitor-related Pneumonitis (CIP) exhibits high morbidity and mortality rates in the real world, often coexisting with pneumonia, particularly after immunochemotherapy. We aimed to develop and validate a non-invasive n...

Data-driven machine learning algorithm model for pneumonia prediction and determinant factor stratification among children aged 6-23 months in Ethiopia.

BMC infectious diseases
INTRODUCTION: Pneumonia is the leading cause of child morbidity and mortality and accounts for 5.6 million under-five child deaths. Pneumonia has a significant impact on the quality of life, the country's economy, and the survival of children. Theref...

Effect of pregnancy and infancy exposure to outdoor particulate matter (PM, PM, PM) and SO on childhood pneumonia in preschool children in Taiyuan City, China.

Environmental pollution (Barking, Essex : 1987)
There is currently a paucity of research on the effects of early life exposure to particulate matter (PM) of various size fractions on pneumonia in preschool-aged children. We explored the connections between antenatal and postnatal exposure to atmos...

Comparing large scale and selected feature learning for community acquired pneumonia prognosis prediction using clinical data: a stacked ensemble approach.

Scientific reports
This study investigated and validated all-cause in-hospital death prediction models for hospitalized pneumonia patients based on large-scale clinical data, including diagnoses, medication prescriptions, and laboratory test codes. Feature selection wa...

Evaluating a large language model's accuracy in chest X-ray interpretation for acute thoracic conditions.

The American journal of emergency medicine
BACKGROUND: The rapid advancement of artificial intelligence (AI) has great ability to impact healthcare. Chest X-rays are essential for diagnosing acute thoracic conditions in the emergency department (ED), but interpretation delays due to radiologi...

Machine learning-based model for predicting all-cause mortality in severe pneumonia.

BMJ open respiratory research
BACKGROUND: Severe pneumonia has a poor prognosis and high mortality. Current severity scores such as Acute Physiology and Chronic Health Evaluation (APACHE-II) and Sequential Organ Failure Assessment (SOFA), have limited ability to help clinicians i...