Artificial Intelligence in Chronic Obstructive Pulmonary Disease: Research Status, Trends, and Future Directions--A Bibliometric Analysis from 2009 to 2023
H Bian, S Zhu, Y Zhang, Q Fei, X Peng… - … Journal of Chronic …, 2024 - Taylor & Francis
Objective A bibliometric analysis was conducted using VOSviewer and CiteSpace to
examine studies published between 2009 and 2023 on the utilization of artificial intelligence …
examine studies published between 2009 and 2023 on the utilization of artificial intelligence …
Looking Beyond What You See: An Empirical Analysis on Subgroup Intersectional Fairness for Multi-label Chest X-ray Classification Using Social Determinants of …
D Moukheiber, S Mahindre, L Moukheiber… - arXiv preprint arXiv …, 2024 - arxiv.org
There has been significant progress in implementing deep learning models in disease
diagnosis using chest X-rays. Despite these advancements, inherent biases in these models …
diagnosis using chest X-rays. Despite these advancements, inherent biases in these models …
Development and Validation of a Deep Learning Classifier Using Chest Radiographs to Predict Extubation Success in Patients Undergoing Invasive Mechanical …
The decision to extubate patients on invasive mechanical ventilation is critical; however,
clinician performance in identifying patients to liberate from the ventilator is poor. Machine …
clinician performance in identifying patients to liberate from the ventilator is poor. Machine …
A Machine Learning Approach for the Detection of Thoracic Disease using Chest X-ray reports
Today, several chest diseases are on the rise and these are often diagnosed through the
use of chest X-rays, a common and economical clinical test to perform. This work uses a …
use of chest X-rays, a common and economical clinical test to perform. This work uses a …
Multimodal Deep Dilated Convolutional Learning for Lung Disease Diagnosis
KA Varunkumar, M Zymbler, S Kumar - Brazilian Archives of Biology …, 2024 - SciELO Brasil
Accurate and timely identification of pulmonary disease is critical for effective therapeutic
intervention. Computed tomography (CT), chest radiography (x-ray) and positron emission …
intervention. Computed tomography (CT), chest radiography (x-ray) and positron emission …
[HTML][HTML] CAD-Chest: Comprehensive Annotation of Diseases based on MIMIC-CXR Radiology Report
Several extant chest X-ray (CXR) datasets predominantly comprise binary disease labels
and exhibit a deficiency in providing comprehensive disease-related information. Crucial …
and exhibit a deficiency in providing comprehensive disease-related information. Crucial …
[HTML][HTML] RaDialog Instruct Dataset
Conversational AI tools that can generate and discuss clinically correct radiology reports for
a given medical image have the potential to transform radiology. Such a human-in-the-loop …
a given medical image have the potential to transform radiology. Such a human-in-the-loop …
[HTML][HTML] CheXmask Database: a large-scale dataset of anatomical segmentation masks for chest x-ray images
N Gaggion, C Mosquera, M Aineseder, L Mansilla… - physionet.org
Abstract The CheXmask Database presents a comprehensive, uniformly annotated
collection of chest radiographs, constructed from six public databases: CANDID-PTX …
collection of chest radiographs, constructed from six public databases: CANDID-PTX …