AIMC Topic: Pneumonia
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[Surveillance for pneumonia of unknown etiology: current status, challenges, and implementation ways].
Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
May 10, 2025
The prevention and control of emerging and reemerging infectious diseases are crucial for national biosecurity, and surveillance and reporting of pneumonia of unknown etiology are main ways for the early detection of these diseases and mitigation of ...
Clinical characteristics, outcomes, and predictive modeling of patients diagnosed with immune checkpoint inhibitor therapy-related pneumonitis.
Cancer immunology, immunotherapy : CII
May 9, 2025
PURPOSE: The aim of this study is to better characterize the clinical characteristics and outcomes of patients diagnosed with Immune checkpoint Inhibitor (ICI) pneumonitis and propose predictive models.
FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets.
Current medical imaging
Jan 1, 2025
BACKGROUND: Pneumonia is an acute respiratory infection that has emerged as the predominant catalyst for escalating mortality rates worldwide. In the pursuit of the prevention and prediction of pneumonia, this work employs the development of an advan...
Machine Learning to Predict the Risk of Malnutrition in Hospitalized Patients with Pneumonia and Analysis of Related Prognostic Factor.
Studies in health technology and informatics
Aug 22, 2024
This study explored machine learning's potential in predicting the nutritional status and outcomes for pneumonia patients. It focused on 4,368 patients in a Taiwan medical center from Jan 2016 to Feb 2022, excluding ICU cases. The average age was 77....
Leveraging Vision Transformers for Enhanced Accuracy in Pneumonia Detection from Medical Imaging Data.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Medical image analysis has witnessed a paradigm shift with the advent of artificial intelligence, particularly the application of Vision Transformers (ViTs). In this study, we leverage the unique attention mechanisms of ViTs to enhance the representa...
[Prediction of risk of in-hospital death in patients with chronic heart failure complicated by lung infections using interpretable machine learning].
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Jun 20, 2024
OBJECTIVE: To predict the risk of in-hospital death in patients with chronic heart failure (CHF) complicated by lung infections using interpretable machine learning.
Predicting Immune Checkpoint Inhibitor-Related Pneumonitis via Computed Tomography and Whole-Lung Analysis Deep Learning.
Current medical imaging
Jan 1, 2024
BACKGROUND: Immune checkpoint inhibitor-related pneumonitis (ICI-P) is a fatal adverse event of immunotherapy. However, there is a lack of methods to identify patients who have a high risk of developing ICI-P in immunotherapy.
Pneumonia detection on chest X-rays from Xception-based transfer learning and logistic regression.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2024
Pneumonia is a dangerous disease that kills millions of children and elderly patients worldwide every year. The detection of pneumonia from a chest x-ray is perpetrated by expert radiologists. The chest x-ray is cheaper and is most often used to diag...
Enhancing Organizing Pneumonia Diagnosis: A Novel Super-token Transformer Approach for Masson Body Segmentation.
In vivo (Athens, Greece)
Jan 1, 2024
BACKGROUND/AIM: In this study, we introduce an innovative deep-learning model architecture aimed at enhancing the accuracy of detecting and classifying organizing pneumonia (OP), a condition characterized by the presence of Masson bodies within the a...
Classification of Pneumonia via a Hybrid ZFNet-Quantum Neural Network Using a Chest X-ray Dataset.
Current medical imaging
Jan 1, 2024
INTRODUCTION: Deep neural networks (DNNs) have made significant contributions to diagnosing pneumonia from chest X-ray imaging. However, certain aspects of diagnosis and planning can be further enhanced through the implementation of a quantum deep ne...
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