Multi-Domain Fake News Detection Exploiting Ensemble Learning Techniques
A Multi-View Ensemble classifier which considers domain knowledge during classification, a critical feature for fake news detection.
Scopri come l’Intelligenza Artificiale sta trasformando il mondo: dalle reti neurali ai modelli predittivi, il futuro dell’innovazione è qui.
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.
Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review
Parkinson’s disease (PD) is a neurodegenerative disorder that produces both motor and non-motor complications, degrading the quality of life of PD patients. Over the past two decades, the use of wearable devices in combination with machine learning algorithms has provided promising methods for more objective and continuous monitoring of PD.
Nuovo traguardo nella segmentazione dei tumori renali: KiTS 2023
SenticLab è nella Top 5 nella competizione KiTS 2023, avendo sviluppato un algoritmo per la segmentazione di immagini dei reni, per identificare cisti e tumori.
Analyzing domain shift when using additional data for the MICCAI KiTS23 Challenge
Using additional training data is known to improve the results, especially for medical image 3D segmentation where there is a lack of training material and the model needs to generalize well from few available data.
Automated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy
Oral capillaroscopy is a critical and non-invasive technique used to evaluate microcirculation. Its ability to observe small vessels in vivo has generated significant interest in the field. Capillaroscopy serves as an essential tool for diagnosing and prognosing various pathologies, with anatomic–pathological lesions playing a crucial role in their progression.
Enhancing video game experience with playtime training and tailoring of virtual opponents: Using Deep Q-Network based Reinforcement Learning on a Multi-Agent Environment
When interacting with fictional environments, the users' sense of immersion can be broken when characters act in mechanical and predictable ways.
Robust and language-independent acoustic features in Parkinson’s disease
The analysis of vocal samples from patients with Parkinson's disease (PDP) can be relevant in supporting early diagnosis and disease monitoring.
