Pulmonology

Synthetic pulmonary perfusion images from 4DCT for functional avoidance using deep learning.

To develop and evaluate the performance of a deep learning model to generate synthetic pulmonary perfusion images from clinical 4DCT images for patients undergoing radiotherapy for lung cancer.. A clinical data set of 58 pre- and post-radiotherapyTc-labeled MAA-SPECT perfusion studies (32 patients) each with contemporaneous 4DCT studies was collected. Using the inhale and exhale phases of the 4DCT...

A New Optimal Diagnosis System for Coronavirus (COVID-19) Diagnosis Based on Archimedes Optimization Algorithm on Chest X-Ray Images.

The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large group of viruses that can infect animals and humans and cause respiratory distress; these discomforts may be as mild as a cold or as severe as pneumonia. Correct detection of this disease can help to avoid its spreading increasingly. In this paper, a new CAD-based approach is suggested for the optimal ...

Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza.

BACKGROUND: Respiratory virus infections are significant causes of morbidity and mortality, and may induce host metabolite alterations by infecting re...

Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning.

We examined the feasibility of explainable computer-aided detection of cardiomegaly in routine clinical practice using segmentation-based methods. Ove...

A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data.

Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity and mortality in COPD patients. Apart from patients ...

Piezoelectric Smart Patch Operated with Machine-Learning Algorithms for Effective Detection and Elimination of Condensation.

Timely detection and elimination of surface condensation is crucial for diverse applications in agriculture, automotive, oil and gas industries, and r...

Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment, such as extracellular matrix remodeling, recipro...

Machine learning for manually-measured water quality prediction in fish farming.

Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-quality fish farming. Machine learning (ML) techniques...

CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice.

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, serum...

Evaluation of the Effectiveness of Artificial Intelligence Chest CT Lung Nodule Detection Based on Deep Learning.

Lung cancer is one of the most malignant tumors. If it can be detected early and treated actively, it can effectively improve a patient's survival rat...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and tr...

Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmonary nodule detection on computed tomography (CT) im...

Molecular Dynamics Simulations to Explore the Structure and Rheological Properties of Normal and Hyperconcentrated Airway Mucus.

We develop the first molecular dynamics model of airway mucus based on the detailed physical properties and chemical structure of the predominant gel-...

Deep-learning based detection of COVID-19 using lung ultrasound imagery.

BACKGROUND: The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, especially in underdeveloped countries. There is a c...

Interleukin-37 gene polymorphism and susceptibility to pulmonary tuberculosis among Iraqi patients.

BACKGROUND: Control of tuberculosis (TB) depends on a balance between host's immune factors and bacterial evasion strategies. Interleukin-37 (IL-37) i...

Estimated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults.

We aimed to develop an artificial neural network (ANN) model to estimate the maximal oxygen uptake (VOmax) based on a multistage 10 m shuttle run test...

A case of fatal multidrug intoxication involving flualprazolam: distribution in body fluids and solid tissues.

PURPOSE: Designer benzodiazepines (DBZDs) increasingly emerged on the novel psychoactive substance (NPS) market in the last few years. They are usuall...

A Method for Optimal Detection of Lung Cancer Based on Deep Learning Optimized by Marine Predators Algorithm.

Lung cancer is the uncontrolled growth of cells in the lung that are made up of two spongy organs located in the chest. These cells may penetrate outs...

Application of Artificial Intelligence for Diagnosis and Risk Stratification in NAFLD and NASH: The State of the Art.

The diagnosis of nonalcoholic fatty liver disease and associated fibrosis is challenging given the lack of signs, symptoms and nonexistent diagnostic ...

Scalable quorum-based deep neural networks with adversarial learning for automated lung lobe segmentation in fast helical free-breathing CTs.

PURPOSE: Fast helical free-breathing CT (FHFBCT) scans are widely used for 5DCT and 5D Cone Beam imaging protocols. For quantitative analysis of lung ...