Pulmonology

Diagnostic accuracy of artificial intelligence-based multi-spectrum analysis for molecular fingerprint detection of SARS-CoV-2.

Reverse transcription-polymerase chain reaction (RT-PCR) is the reference standard for COVID-19 diagnosis, but the need for rapid, reproducible, and cost-effective diagnostic tools remains. This study investigated the diagnostic performance of a novel artificial intelligence-based multispectrum analysis (MSA, AP23) technique that detects the biomolecular fingerprint of severe acute respiratory syn...

Predicting and interpreting key features of refractory Mycoplasma pneumoniae pneumonia using multiple machine learning methods.

In recent years, the incidence of refractory Mycoplasma pneumoniae pneumonia (RMPP) has significantly risen, posing severe pulmonary and extrapulmonary complications, making early identification a challenge for clinicians. In this retrospective single-center study, we included patients diagnosed with Mycoplasma pneumoniae pneumonia in 2021, categorizing them into RMPP and non-RMPP groups. Univaria...

Machine learning analysis of factors contributing to hypotension after lumbosacral epidural anaesthesia in dogs undergoing abdominal surgery.

The incidence of hypotension after a lumbosacral epidural in dogs depends on the volume of local anaesthetic administered. So far, there are no report...

Temporal Differential Fields for 4D Motion Modeling via Image-to-Video Synthesis

Temporal modeling on regular respiration-induced motions is crucial to image-guided clinical applications. Existing methods cannot simulate temporal...

Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.

BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevent...

Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction.

The advancement of the Internet of Medical Things (IoMT) has revolutionized data acquisition and processing in critical care settings. Given the pivot...

Comprehensive Lung Disease Detection Using Deep Learning Models and Hybrid Chest X-ray Data with Explainable AI

Advanced diagnostic instruments are crucial for the accurate detection and treatment of lung diseases, which affect millions of individuals globally...

Lung Nodule-SSM: Self-Supervised Lung Nodule Detection and Classification in Thoracic CT Images

Lung cancer remains among the deadliest types of cancer in recent decades, and early lung nodule detection is crucial for improving patient outcomes...

Prediction of Spontaneous Breathing Trial Outcome in Critically Ill-Ventilated Patients Using Deep Learning: Development and Verification Study.

BACKGROUND: Long-term ventilator-dependent patients often face problems such as decreased quality of life, increased mortality, and increased medical ...

Federated learning in low-resource settings: A chest imaging study in Africa -- Challenges and lessons learned

This study explores the use of Federated Learning (FL) for tuberculosis (TB) diagnosis using chest X-rays in low-resource settings across Africa. FL...

Bronchovascular Tree-Guided Weakly Supervised Learning Method for Pulmonary Segment Segmentation

Pulmonary segment segmentation is crucial for cancer localization and surgical planning. However, the pixel-wise annotation of pulmonary segments is...

[Development and validation of risk assessment models for abnormal lung function in coal workers based on machine learning].

To analyze the factors influencing the lung function of coal miners, identify the optimal combination of indicators for evaluating lung function, dev...

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity

Respiratory viral infections pose a global health burden, yet the cellular immune responses driving protection or pathology remain unclear. Natural ...

Activation of the Carotid Body by Kappa Opioid Receptors Mitigates Fentanyl-Induced Respiratory Depression.

Previous studies reported that opioids depress breathing by inhibiting respiratory neural networks in the brainstem. The effects of opioids on sensory...

Assessing artificial intelligence ability in predicting hospitalization duration for pleural empyema patients managed with uniportal video-assisted thoracoscopic surgery: a retrospective observational study.

BACKGROUND: This retrospective observational research evaluates the potential applicability of artificial intelligence models to predict the length of...

Attention-Enhanced U-Net for Accurate Segmentation of COVID-19 Infected Lung Regions in CT Scans

In this study, we propose a robust methodology for automatic segmentation of infected lung regions in COVID-19 CT scans using convolutional neural n...

Integrating bioinformatics and machine learning to unravel shared mechanisms and biomarkers in chronic obstructive pulmonary disease and type 2 diabetes.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) are on the rise. While there is evidence of a link betwee...

Explainable Machine Learning for Oxygen Diffusion in Perovskites and Pyrochlores

Explainable machine learning can help to discover new physical relationships for material properties. To understand the material properties that gov...

Pretrained hybrid transformer for generalizable cardiac substructures segmentation from contrast and non-contrast CTs in lung and breast cancers

AI automated segmentations for radiation treatment planning (RTP) can deteriorate when applied in clinical cases with different characteristics than...

Assessing fetal lung maturity: Integration of ultrasound radiomics and deep learning.

This study built a model to forecast the maturity of lungs by blending radiomics and deep learning methods. We examined ultrasound images from 263 pre...