Measurement of Acute Pain in the Pediatric Emergency Department Through Automatic Detection of Behavioral Parameters
We propose a camera-based system to provide an objective, contactless assessment of pain in children aged less than 3 years.
Explore the future of Digital Healthcare: artificial intelligence, big data, and innovative technologies for health and well-being.
Automated 3D cephalometry: A lightweight V-net for landmark localization on CBCT
Automating cephalometric analysis would have huge potential for enhance orthodontic treatment workflow, supporting diagnosis and decision.
Detection of dental restorations and prosthesis devices in panoramic dental X-ray using fast region-based convolutional neural network
Objectives This study aimed to develop and evaluate an artificial intelligence (AI) framework for detecting dental restorations and prosthesis devices on panoramic radiographs (PRs). Detecting these elements is essential for enhancing automated reporting, improving the accuracy of dental assessments, and reducing manual examination…
Development and Evaluation of a Keypoint-Based Video Stabilization Pipeline for Oral Capillaroscopy
A video stabilization pipeline for oral capillaroscopy imaging. The approach offers reliable, efficient stabilization, enhancing the quality of oral videocapillaroscopy.
Integral Bone Age Regression
The paper takes a practical approach to estimating the bone age of children and young adults based on hand radiography, by constructing an end-to-end pipeline that involves bone segmentation, deep regression algorithms and model explainability.
Automatic diagnosis of liver masses in Computed Tomography scans
This paper presents a complete pipeline for automatic diagnosis of various liver masses, consisting of components based on deep learning models for both the automatic segmentation of liver and its lesions, as well as the classification of masses into 5 classes, namely simple cysts, hemangiomas, hepatocellular carcinoma, calcifications and metastases.
Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images
This work proposes a convolutional neural network (CNN) that utilizes different combinations of parametric images computed from cine cardiac magnetic resonance (CMR) images, to classify each slice for possible myocardial scar tissue presence.
Diagnostic performance of an AI algorithm for the detection of appendicular bone fractures in pediatric patients
To evaluate the diagnostic performance of an Artificial Intelligence (AI) algorithm, previously trained using both adult and pediatric patients, for the detection of acute appendicular fractures in the pediatric population on conventional X-ray radiography (CXR).
Comparison of entropy rate measures for the evaluation of time series complexity: Simulations and application to heart rate and respiratory variability
Most real-world systems are characterised by dynamics and correlations emerging at multiple time scales, and are therefore referred to as complex systems. In this work, the complexity of time series produced by complex systems was investigated in the frame of information theory computing the entropy rate via the conditional entropy (CE) measure.
Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department
Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly.
