Latest AI and machine learning research in pulmonology for healthcare professionals.
BACKGROUND: Early identification of the malignant propensity of pulmonary ground-glass nodules (GGNs...
This systematic review aims to identify the available semi-automatic and fully automatic algorithms ...
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of cor...
Lung cancer is one of the malignant tumors with the highest fatality rate and nearest to our lives. ...
BACKGROUND AND OBJECTIVE: Adequate serum phosphorus levels in patients with chronic kidney disease i...
OBJECTIVES: We aim ed to evaluate a commercial artificial intelligence (AI) solution on a multicente...
AIM: The goal was to use a deep convolutional neural network to measure the radiographic alveolar bo...
OBJECTIVE: To explore the feasibility of using random forest (RF) machine learning algorithm in asse...
The automation in the diagnosis of medical images is currently a challenging task. The use of Comput...
Periodic inspection of false ceilings is mandatory to ensure building and human safety. Generally, f...
Lymph node metastasis also called nodal metastasis (Nmet), is a clinically primary task for physicia...
BACKGROUND: Chest computed tomography (CT) is crucial in the diagnosis of coronavirus disease 2019 (...
The efforts made to prevent the spread of COVID-19 face specific challenges in diagnosing COVID-19 p...
Coronavirus disease 2019 is a global health threat often accompanied with coagulopathy. Despite use...
BACKGROUND: Antibody response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) a...
Cancer subtype classification helps us to understand the pathogenesis of cancer and develop new canc...
Pre-Bötzinger complex (PBC) is a necessary condition for the generation of respiratory rhythm. Due t...
The excessive number of COVID-19 cases reported worldwide so far, supplemented by a high rate of fal...
PURPOSE: Ventilator-associated pneumonia is the most common nosocomial infection in patients with me...
OBJECTIVES: We propose a framework of health outcomes modeling with dynamic decision making and real...
Physiological time series are affected by many factors, making them highly nonlinear and nonstationa...