Pulmonology

Deep-LUMEN assay - human lung epithelial spheroid classification from brightfield images using deep learning.

Three-dimensional (3D) tissue models such as epithelial spheroids or organoids have become popular for pre-clinical drug studies. In contrast to 2D monolayer culture, the characterization of 3D tissue models from non-invasive brightfield images is a significant challenge. To address this issue, here we report a deep-learning uncovered measurement of epithelial networks (Deep-LUMEN) assay. Deep-LUM...

[Artificial intelligence and innovation to optimize the tuberculosis diagnostic process].

Tuberculosis remains an urgent issue on the urban health agenda, especially in low- and middle-income countries. There is a need to develop and implement innovative and effective solutions in the tuberculosis diagnostic process. In this article, We describe the importance of artificial intelligence as a strategy to address tuberculosis control, particularly by providing timely diagnosis. Besides t...

Impact of Confounding Thoracic Tubes and Pleural Dehiscence Extent on Artificial Intelligence Pneumothorax Detection in Chest Radiographs.

OBJECTIVES: We hypothesized that published performances of algorithms for artificial intelligence (AI) pneumothorax (PTX) detection in chest radiograp...

A Case of Dapsone-induced Mild Methemoglobinemia with Dyspnea and Cyanosis.

Dear Editor, Dapsone is a dual-function drug with antimicrobial and antiprotozoal effects and anti-inflammatory features (1). In dermatology, it is a ...

Postural Balance Evaluation in Patients with Chronic Obstructive Pulmonary Disease.

BACKGROUND: The risk of falling in patients with chronic obstructive pulmonary disease (COPD) is higher than healthy people, imposing a great financia...

Robot-assisted cervical esophagectomy: first clinical experiences and review of the literature.

Pulmonary complications, and especially pneumonia, remain one of the most common complications after esophagectomy for esophageal cancer. These compli...

Latent COVID-19 Clusters in Patients with Chronic Respiratory Conditions.

The goal of this paper was to apply unsupervised machine learning techniques towards the discovery of latent COVID-19 clusters in patients with chroni...

Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis.

BACKGROUND: Liver fibrosis (LF) continues to develop and eventually progresses to cirrhosis. However, LF and early-stage cirrhosis (ESC) can be revers...

[Effect of moxa-cone moxibustion at lung's back- points and front- points on Th17/Treg balance in mice with asthma].

OBJECTIVE: To observe the effect of moxa-cone moxibustion at lung's back- points and front- points on the expression of helper T lymphocyte 17 (Th 17)...

[Pathological diagnosis of lung cancer based on deep transfer learning].

To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning. The researchers collected 519 lu...

Machine learning for direct oxygen saturation and hemoglobin concentration assessment using diffuse reflectance spectroscopy.

SIGNIFICANCE: Diffuse reflectance spectroscopy (DRS) is frequently used to assess oxygen saturation and hemoglobin concentration in living tissue. Met...

Deep learning applications to combat the dissemination of COVID-19 disease: a review.

Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by...

Application of machine intelligence technology in the detection of vaccines and medicines for SARS-CoV-2.

Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that re...

[Discrimination of lung cancer and adjacent normal tissues based on permittivity by optimized probabilistic neural network].

OBJECTIVE: To propose a probabilistic neural network classification method optimized by simulated annealing algorithm (SA-PNN) to discriminate lung ca...

Machine Learning Classifier Models Can Identify Acute Respiratory Distress Syndrome Phenotypes Using Readily Available Clinical Data.

Two distinct phenotypes of acute respiratory distress syndrome (ARDS) with differential clinical outcomes and responses to randomly assigned treatmen...

[Artificial intelligence-based algorithms : Decision-making support for computed tomography of the chest].

Artificial intelligence (AI) algorithms are increasingly used in radiology. The main areas of application are, for example, the detection of lung lesi...

Machine intelligence for early targeted precision management and response to outbreaks of respiratory infections.

OBJECTIVES: To evaluate the utility of machine learning (ML) for the management of Medicare beneficiaries at risk of severe respiratory infections in ...

[Risk factors for postoperative intestinal obstruction in patients undergoing robot-assisted laparoscopic radical prostatectomy].

To analyze the risk factors of postoperative intestinal obstruction (POI) in patients undergoing robot-assisted laparoscopic radical prostatectomy (R...

Augmenting Interpretation of Chest Radiographs With Deep Learning Probability Maps.

PURPOSE: Pneumonia is a common clinical diagnosis for which chest radiographs are often an important part of the diagnostic workup. Deep learning has ...

A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019.

The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-1...