AIMC Topic: Pneumonia

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A machine learning model for predicting 28-day mortality in ICU patients with community-acquired pneumonia and acute kidney injury.

Scientific reports
Acute kidney injury is a common and critical complication in patients with community-acquired pneumonia who are admitted to intensive care units, substantially increasing their risk of short-term mortality. To enhance early clinical decision-making, ...

Development and validation of a machine learning model for critical progression risk in pediatric severe community-acquired pneumonia.

Scientific reports
This study aimed to utilize various machine learning algorithms to develop a predictive model for the progression of severe community-acquired pneumonia (SCAP) in children to critical severe community-acquired pneumonia (cSCAP). Retrospective analysi...

An interpretable machine learning approach to prognosis of melioidosis pneumonia via computed tomography quantification and clinical data.

Scientific reports
This study aimed to develop a dataset comprising computed tomography (CT) images and clinical data for melioidosis pneumonia and to utilize machine learning for assisting in prognosis prediction of the disease. We retrospectively analyzed multicenter...

Comparing ChatGPT-3.5, Gemini 2.0, and DeepSeek V3 for pediatric pneumonia learning in medical students.

Scientific reports
Pediatric pneumonia (PP) remains an important topic in undergraduate medical education and offers a suitable framework for evaluating large language models (LLMs) in AI-assisted learning. We developed a 27 open-ended survey including five core domain...

Development and internal validation of a preoperative prediction model for postoperative pneumonia in lung cancer patients: a retrospective study.

BMC surgery
PURPOSE: To evaluate the postoperative pneumonia (POP) risk of patients with non-small cell lung cancer (NSCLC), identify influencing factors, develop a LASSO regression-based model to predict POP risk and identify critical influencing factors.

TL-PneuNet: a transfer learning-based pneumonia classification framework.

Scientific reports
Pneumonia is a severe respiratory ailment that may be caused by viruses, fungus, and bacteria. Pneumonia causes the accumulation of water, purulent material, or other fluids in the air sacs (alveoli) of the lungs. A delay in the identification of pne...

Trustworthy pneumonia detection in chest X-ray imaging through attention-guided deep learning.

Scientific reports
Pneumonia remains a significant global health threat, especially among children, the elderly, and immunocompromised individuals. Chest X-ray (CXR) imaging is commonly used for diagnosis, but manual interpretation is prone to errors and variability. T...

A machine learning model including pentraxin-3 as predictor of outcomes in community-acquired pneumonia.

Journal of translational medicine
BACKGROUND: The clinical diagnosis, severity assessment, and outcome prognostication of community-acquired pneumonia (CAP) remain challenging due to the complex disease pathophysiology. Accurate outcome prediction is crucial for optimizing patient ma...

Metagenomic next-generation sequencing unraveled the characteristic of lung microbiota in patients with checkpoint inhibitor pneumonitis: results from a prospective cohort study.

Journal for immunotherapy of cancer
BACKGROUND: Checkpoint inhibitor pneumonitis (CIP) is among the most lethal immune-related adverse events in patients with cancer receiving immunotherapy. This study aims to characterize the lung microbiome in patients with CIP and evaluate its diagn...

A hybrid dense convolutional network and fuzzy inference system for pneumonia diagnosis with dynamic symptom tracking.

PloS one
BACKGROUND: Pneumonia is a major cause of mortality among children under five and adults over 65, especially in low-resource settings where access to skilled radiologists is limited. Accurate and early diagnosis is essential, but is often hindered by...