Pulmonology

Think positive: An interpretable neural network for image recognition.

The COVID-19 pandemic is an ongoing pandemic and is placing additional burden on healthcare systems around the world. Timely and effectively detecting the virus can help to reduce the spread of the disease. Although, RT-PCR is still a gold standard for COVID-19 testing, deep learning models to identify the virus from medical images can also be helpful in certain circumstances. In particular, in si...

Extraction of low-dimensional features for single-channel common lung sound classification.

In this study, feature extraction methods used in the classification of single-channel lung sounds obtained by automatic identification of respiratory cycles were examined in detail in order to extract distinctive features at the lowest size. In this way, it will be possible to design a system for the detection of lung diseases, completely autonomously. In the study, automatic separation and class...

Deep Learning of Rhabdomyosarcoma Pathology Images for Classification and Survival Outcome Prediction.

Rhabdomyosarcoma (RMS), the most common malignant soft tissue tumor in children, has several histologic subtypes that influence treatment and predict ...

Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning.

Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the ...

A two-stage deep learning architecture for radiographic staging of periodontal bone loss.

BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, i...

Robot-assisted thoracic surgery is effective for right upper lobectomy in cases with a rare variation pattern of the pulmonary veins.

Classification of pleural effusions using deep learning visual models: contrastive-loss.

Blood and fluid analysis is extensively used for classifying the etiology of pleural effusion. However, most studies focused on determining the presen...

Deep learning and non-invasive assessment of significant fibrosis: does adding more toppings improve the flavor of prediction?

DeBoNet: A deep bone suppression model ensemble to improve disease detection in chest radiographs.

Automatic detection of some pulmonary abnormalities using chest X-rays may be impacted adversely due to obscuring by bony structures like the ribs and...

Lightweight YOLOv4 with Multiple Receptive Fields for Detection of Pulmonary Tuberculosis.

The characteristics of pulmonary are complex, and the cost of manual screening is high. The detection model based on convolutional neural network is ...

Automatic detection of pneumonia in chest X-ray images using textural features.

Fast and accurate diagnosis is critical for the triage and management of pneumonia, particularly in the current scenario of a COVID-19 pandemic, where...

Machine Learning with Quantum Seagull Optimization Model for COVID-19 Chest X-Ray Image Classification.

Early and accurate detection of COVID-19 is an essential process to curb the spread of this deadly disease and its mortality rate. Chest radiology sca...

H-SegNet: hybrid segmentation network for lung segmentation in chest radiographs using mask region-based convolutional neural network and adaptive closed polyline searching method.

Chest x-ray (CXR) is one of the most commonly used imaging techniques for the detection and diagnosis of pulmonary diseases. One critical component in...

An Efficient and Effective Deep Learning-Based Model for Real-Time Face Mask Detection.

Since December 2019, the COVID-19 pandemic has led to a dramatic loss of human lives and caused severe economic crises worldwide. COVID-19 virus trans...

MR-assisted PET respiratory motion correction using deep-learning based short-scan motion fields.

PURPOSE: We evaluated the impact of PET respiratory motion correction (MoCo) in a phantom and patients. Moreover, we proposed and examined a PET MoCo ...

Effect Evaluation of Electronic Health PDCA Nursing in Treatment of Childhood Asthma with Artificial Intelligence.

Asthma in children has a long duration and is prone to recurring attacks. Children will feel chest tightness, shortness of breath, cough, and difficul...

Ultrasound Lung Image under Artificial Intelligence Algorithm in Diagnosis of Neonatal Respiratory Distress Syndrome.

In order to analyze the application of ultrasonic lung imaging diagnosis model based on artificial intelligence algorithm in neonatal respiratory dist...

Models of Artificial Intelligence-Assisted Diagnosis of Lung Cancer Pathology Based on Deep Learning Algorithms.

In this article, in order to explore the application of a diagnosis system for lung cancer, we use an auxiliary diagnostic system to predict and diagn...

Pre-germinated brown rice alleviates non-alcoholic fatty liver disease induced by high fructose and high fat intake in rat.

In past researches, we had been proved the action mechanism of pre-germinated brown rice (PGBR) to treat metabolic syndrome and diabetes mellitus. Thi...

Research on Lung Ultrasound Image Classification Based on Compressed Sensing.

Pneumothorax is a common injury in disaster rescue, traffic accidents, and war trauma environments and requires early diagnosis and treatment. The com...