Pulmonology

Dual Skip Connections Minimize the False Positive Rate of Lung Nodule Detection in CT images.

Pulmonary cancer is one of the most commonly diagnosed and fatal cancers and is often diagnosed by incidental findings on computed tomography. Automated pulmonary nodule detection is an essential part of computer-aided diagnosis, which is still facing great challenges and difficulties to quickly and accurately locate the exact nodules' positions. This paper proposes a dual skip connection upsampli...

Unsupervised Detection of Lung Nodules in Chest Radiography Using Generative Adversarial Networks.

Lung nodules are commonly missed in chest radiographs. We propose and evaluate P-AnoGAN, an unsupervised anomaly detection approach for lung nodules in radiographs. P-AnoGAN modifies the fast anomaly detection generative adversarial network (f-AnoGAN) by utilizing a progressive GAN and a convolutional encoder-decoder-encoder pipeline. Model training uses only unlabelled healthy lung patches extrac...

Design of Novel End-effectors for Robot-assisted Swab Sampling to Combat Respiratory Infectious Diseases.

The COVID-19 outbreak has caused the mortality worldwide and the use of swab sampling is a common way of screening and diagnosis. To combat respirator...

Predictive Value of Immune Cell Functional Assay for Non-Cytomegalovirus Infection in Lung Transplant Recipients: A Multicenter Prospective Observational Study.

INTRODUCTION: Immune cell functional assay (ImmuKnow®) is a non-invasive method that measures the state of cellular immunity in immunosuppressed patie...

Predicting the Aortic Aneurysm Postoperative Risks Based on Russian Integrated Data.

This article describes the results of feature extraction from unstructured medical records and prediction of postoperative complications for patients ...

Factors determining generalization in deep learning models for scoring COVID-CT images.

The COVID-19 pandemic has inspired unprecedented data collection and computer vision modelling efforts worldwide, focused on the diagnosis of COVID-19...

Computational prediction of the effect of amino acid changes on the binding affinity between SARS-CoV-2 spike RBD and human ACE2.

The association of the receptor binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein with human angioten...

PULMONARY NODULE DETECTION IN CHEST CT USING A DEEP LEARNING-BASED RECONSTRUCTION ALGORITHM.

This study's aim was to assess whether deep learning image reconstruction (DLIR) techniques are non-inferior to ASIR-V for the clinical task of pulmon...

Are small airplanes safe with regards to COVID-19 transmission?

Social distancing is impossible in small aircrafts but there is a specific, highly effective ventilation system. Measurements proved that there is no ...

Accurate segmentation for different types of lung nodules on CT images using improved U-Net convolutional network.

Since lung nodules on computed tomography images can have different shapes, contours, textures or locations and may be attached to neighboring blood v...

Confocal endomicroscopy and robot-assisted bronchoplasty integration to treat an endobronchial tumour.

We present a case of a young man with an endobronchial carcinoid in the left main bronchus, which was treated integrating probe-based confocal laser e...

End-to-End Non-Small-Cell Lung Cancer Prognostication Using Deep Learning Applied to Pretreatment Computed Tomography.

PURPOSE: Clinical TNM staging is a key prognostic factor for patients with lung cancer and is used to inform treatment and monitoring. Computed tomogr...

External and Internal Validation of a Computer Assisted Diagnostic Model for Detecting Multi-Organ Mass Lesions in CT images.

Objective We developed a universal lesion detector (ULDor) which showed good performance in in-lab experiments. The study aims to evaluate the perform...

Deep learning identifies synergistic drug combinations for treating COVID-19.

Effective treatments for COVID-19 are urgently needed. However, discovering single-agent therapies with activity against severe acute respiratory synd...

Application of machine learning in CT images and X-rays of COVID-19 pneumonia.

Coronavirus disease (COVID-19) has spread worldwide. X-ray and computed tomography (CT) are 2 technologies widely used in image acquisition, segmentat...

Identification of active molecules against Mycobacterium tuberculosis through machine learning.

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb) and it has been one of the top 10 causes of death globally. Drug...

Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms.

BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI al...

Robotic Bronchoscopy for Diagnosing Peripheral Lung Lesions: Are We There Yet?

Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.

This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voice...

[Early Assessment of Myocardial Fibrosis of Hypertrophic Cardiomyopathy with Native-T1-Mapping-Based Deep Learning: A Preliminary Study].

OBJECTIVE: To explore the diagnostic performance of deep learning (DL) model in early detection of the interstitial myocardial fibrosis using native T...