Pulmonology

Artificial Intelligence and Deep Learning Assisted Rapid Diagnosis of COVID-19 from Chest Radiographical Images: A Survey.

Artificial Intelligence (AI) has been applied successfully in many real-life domains for solving complex problems. With the invention of Machine Learning (ML) paradigms, it becomes convenient for researchers to predict the outcome based on past data. Nowadays, ML is acting as the biggest weapon against the COVID-19 pandemic by detecting symptomatic cases at an early stage and warning people about ...

Automated Diagnosis of COVID-19 Using Deep Supervised Autoencoder With Multi-View Features From CT Images.

Accurate and rapid diagnosis of coronavirus disease 2019 (COVID-19) from chest CT scans is of great importance and urgency during the worldwide outbreak. However, radiologists have to distinguish COVID-19 pneumonia from other pneumonia in a large number of CT scans, which is tedious and inefficient. Thus, it is urgently and clinically needed to develop an efficient and accurate diagnostic tool to ...

Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography.

In this study, the accuracy of the positional relationship of the contact between the inferior alveolar canal and mandibular third molar was evaluated...

Energy Expenditure Estimation in Children, Adolescents and Adults by Using a Respiratory Magnetometer Plethysmography System and a Deep Learning Model.

PURPOSE: Energy expenditure is a key parameter in quantifying physical activity. Traditional methods are limited because they are expensive and cumber...

Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT.

Supervised deep learning has become a standard approach to solving medical image segmentation tasks. However, serious difficulties in attaining pixel-...

Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement.

In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a v...

A VS ultrasound diagnostic system with kidney image evaluation functions.

PURPOSE: An inevitable feature of ultrasound-based diagnoses is that the quality of the ultrasound images produced depends directly on the skill of th...

Biodegradable Smart Face Masks for Machine Learning-Assisted Chronic Respiratory Disease Diagnosis.

Utilizing smart face masks to monitor and analyze respiratory signals is a convenient and effective method to give an early warning for chronic respir...

A Fully Deep Learning Paradigm for Pneumoconiosis Staging on Chest Radiographs.

Pneumoconiosis staging has been a very challenging task, both for certified radiologists and computer-aided detection algorithms. Although deep learni...

GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-Ray Images.

Locating diseases in chest X-ray images with few careful annotations saves large human effort. Recent works approached this task with innovative weakl...

Explanatory classification of CXR images into COVID-19, Pneumonia and Tuberculosis using deep learning and XAI.

Chest X-ray (CXR) images are considered useful to monitor and investigate a variety of pulmonary disorders such as COVID-19, Pneumonia, and Tuberculos...

Design and development of hybrid optimization enabled deep learning model for COVID-19 detection with comparative analysis with DCNN, BIAT-GRU, XGBoost.

The recent investigation has started for evaluating the human respiratory sounds, like voice recorded, cough, and breathing from hospital confirmed Co...

AI-Assisted Tuberculosis Detection and Classification from Chest X-Rays Using a Deep Learning Normalization-Free Network Model.

Tuberculosis (TB) is an airborne disease caused by . It is imperative to detect cases of TB as early as possible because if left untreated, there is a...

Dynamic feature learning for COVID-19 segmentation and classification.

Since December 2019, coronavirus SARS-CoV-2 (COVID-19) has rapidly developed into a global epidemic, with millions of patients affected worldwide. As ...

Application of Visual Recognition Based on BP Neural Network in Architectural Design Optimization.

In order to establish the mapping relationship between architectural design parameters and building performance and optimize architectural design para...

Artificial Intelligence in Lung Imaging.

Recently, interest and advances in artificial intelligence (AI) including deep learning for medical images have surged. As imaging plays a major role ...

Reducing uncertainty in cancer risk estimation for patients with indeterminate pulmonary nodules using an integrated deep learning model.

OBJECTIVE: Patients with indeterminate pulmonary nodules (IPN) with an intermediate to a high probability of lung cancer generally undergo invasive di...

Predicting respiratory motion using a novel patient specific dual deep recurrent neural networks.

Real-time tracking of a target volume is a promising solution for reducing the planning margins and both dosimetric and geometric uncertainties in the...

Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: Application to lung cancer screening in Korean National CT accreditation program.

We propose a deep learning-assisted overscan decision algorithm in chest low-dose computed tomography (LDCT) applicable to the lung cancer screening. ...

Development and validation of a deep learning signature for predicting lymph node metastasis in lung adenocarcinoma: comparison with radiomics signature and clinical-semantic model.

OBJECTIVE: To develop and validate a deep learning (DL) signature for predicting lymph node (LN) metastasis in patients with lung adenocarcinoma.