Pulmonology

A temporal visualization of chronic obstructive pulmonary disease progression using deep learning and unstructured clinical notes.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is classified into stages based on disease severity. We aimed to characterize the time to progression prior to death in patients with COPD and to generate a temporal visualization that describes signs and symptoms during different stages of COPD progression.

Survey on deep learning for pulmonary medical imaging.

As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and diagnosis, deep learning-based approaches have emerged as powerful techniques in medical image areas. In this process, feature representations are lear...

Synthesis and in vitro activity of asymmetric indole-based bisamidine compounds against Gram-positive and Gram-negative pathogens.

A series of new asymmetric bisamidine was designed, synthesized, and tested for their in-vitro antibacterial activity using a range of Gram-positive a...

Flavonoid bioactive compounds of hawthorn extract can promote growth, regulate electrocardiogram waves, and improve cardiac parameters of pulmonary hypertensive chickens.

The effect of orally administered hawthorn flavonoid extract (HFE) on growth, electrocardiographic waves, and cardiac parameters of pulmonary hyperten...

Multi-objective ensemble deep learning using electronic health records to predict outcomes after lung cancer radiotherapy.

Accurately predicting treatment outcome is crucial for creating personalized treatment plans and follow-up schedules. Electronic health records (EHRs)...

Characterization of the complete chloroplast genome of (Cupressaceae), an herb to treat lumbar tuberculosis in China.

belongs to the family Cupressaceae that the branches and leaves is an important Traditional Chinese Medicine in China. In this article, the complete ...

Graphene quantum dots as singlet oxygen producer or radical quencher - The matter of functionalization with urea/thiourea.

Due to their low cost and possible green synthesis, high stability and resistance to photobleaching, graphene quantum dots (GQDs) can be considered as...

Shape and margin-aware lung nodule classification in low-dose CT images via soft activation mapping.

A number of studies on lung nodule classification lack clinical/biological interpretations of the features extracted by convolutional neural network (...

Macrolide combination therapy for patients hospitalised with community-acquired pneumonia? An individualised approach supported by machine learning.

BACKGROUND: The role of macrolide/β-lactam combination therapy in community-acquired pneumonia (CAP) of moderate severity is a matter of debate. Macro...

Artificial intelligence applications for thoracic imaging.

Artificial intelligence is a hot topic in medical imaging. The development of deep learning methods and in particular the use of convolutional neural ...

Machine-learning based patient classification using Hepatitis B virus full-length genome quasispecies from Asian and European cohorts.

Chronic infection with Hepatitis B virus (HBV) is a major risk factor for the development of advanced liver disease including fibrosis, cirrhosis, and...

Artificial intelligence for detecting small FDG-positive lung nodules in digital PET/CT: impact of image reconstructions on diagnostic performance.

OBJECTIVES: To evaluate the diagnostic performance of a deep learning algorithm for automated detection of small F-FDG-avid pulmonary nodules in PET s...

Comparison of machine learning algorithms for the identification of acute exacerbations in chronic obstructive pulmonary disease.

OBJECTIVES: Identifying acute exacerbations in chronic obstructive pulmonary disease (AECOPDs) is of utmost importance for reducing the associated mor...

Natural language processing for populating lung cancer clinical research data.

BACKGROUND: Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential t...

Deep learning enables pathologist-like scoring of NASH models.

Non-alcoholic fatty liver disease (NAFLD) and the progressive form of non-alcoholic steatohepatitis (NASH) are diseases of major importance with a hig...

Soft detection of 5-day BOD with sparse matrix in city harbor water using deep learning techniques.

To better control and manage harbor water quality is an important mission for coastal cities such as New York City (NYC). To achieve this, managers an...

Machine learning approach to single nucleotide polymorphism-based asthma prediction.

Machine learning (ML) is poised as a transformational approach uniquely positioned to discover the hidden biological interactions for better predictio...

Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO),...

Inverse association between infection and childhood asthma in Greece: a case-control study.

INTRODUCTION: infection is a well-established etiological factor for a variety of diseases such as peptic ulcer and gastric cancer. On the other hand...

Decision tree machine learning applied to bovine tuberculosis risk factors to aid disease control decision making.

Identifying and understanding the risk factors for endemic bovine tuberculosis (TB) in cattle herds is critical for the control of this disease. Explo...