Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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Development of a diagnostic support system for the fibrosis of nonalcoholic fatty liver disease using artificial intelligence and deep learning.

Liver fibrosis is a pathological condition characterized by the abnormal proliferation of liver tiss...

Machine Learning Identifies Key Proteins in Primary Sclerosing Cholangitis Progression and Links High CCL24 to Cirrhosis.

Primary sclerosing cholangitis (PSC) is a rare, progressive disease, characterized by inflammation a...

Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach.

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including...

The application of impulse oscillometry system based on machine learning algorithm in the diagnosis of chronic obstructive pulmonary disease.

. Diagnosing chronic obstructive pulmonary disease (COPD) using impulse oscillometry (IOS) is challe...

Identification of biological indicators for human exposure toxicology in smart cities based on public health data and deep learning.

With the acceleration of urbanization, the risk of urban population exposure to environmental pollut...

Forecasting fish mortality from water and air quality data using deep learning models.

The high rate of aquatic mortality incidents recorded in Taiwan and worldwide is creating an urgent ...

Artificial Intelligence: Can It Save Lives, Hospitals, and Lung Screening?

BACKGROUND: Early detection is essential in lung cancer survival. Lung screening or incidental detec...

Value of CT-Based Deep Learning Model in Differentiating Benign and Malignant Solid Pulmonary Nodules ≤ 8 mm.

RATIONALE AND OBJECTIVES: We examined the effectiveness of computed tomography (CT)-based deep learn...

Federated-learning-based prognosis assessment model for acute pulmonary thromboembolism.

BACKGROUND: Acute pulmonary thromboembolism (PTE) is a common cardiovascular disease and recognizing...

A machine learning-based model analysis for serum markers of liver fibrosis in chronic hepatitis B patients.

Early assessment and accurate staging of liver fibrosis may be of great help for clinical diagnosis ...

Systematic review and meta-analysis of deep learning applications in computed tomography lung cancer segmentation.

BACKGROUND: Accurate segmentation of lung tumors on chest computed tomography (CT) scans is crucial ...

A deep learning-based radiomics model for predicting lymph node status from lung adenocarcinoma.

OBJECTIVES: At present, there are many limitations in the evaluation of lymph node metastasis of lun...

Preoperative evaluation of visceral pleural invasion in peripheral lung cancer utilizing deep learning technology.

PURPOSE: This study aimed to assess the efficiency of artificial intelligence (AI) in the detection ...

A machine learning-based lung ultrasound algorithm for the diagnosis of acute heart failure.

Lung ultrasound (LUS) is an effective tool for diagnosing acute heart failure (AHF). However, severa...

Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.

BACKGROUND: There has been growing interest in using artificial intelligence/deep learning (DL) to h...

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