Artificial intelligence-based voice assessment of patients with Parkinson's disease off and on treatment: machine vs. deep-learning comparison

G Costantini, V Cesarini, P Di Leo, F Amato, A Suppa… - Sensors, 2023 - mdpi.com
Parkinson's Disease (PD) is one of the most common non-curable neurodegenerative
diseases. Diagnosis is achieved clinically on the basis of different symptoms with …

Applications to augment patient care for Internal Medicine specialists: a position paper from the EFIM working group on telemedicine, innovative technologies & digital …

F Pietrantonio, M Florczak, S Kuhn, K Kärberg… - Frontiers in Public …, 2024 - frontiersin.org
Telemedicine applications present virtually limitless prospects for innovating and enhancing
established and new models of patient care in the field of Internal Medicine. Although there …

[HTML][HTML] Acoustic analysis and prediction of type 2 diabetes mellitus using smartphone-recorded voice segments

JM Kaufman, A Thommandram, Y Fossat - Mayo Clinic Proceedings: Digital …, 2023 - Elsevier
Objective To investigate the potential of voice analysis as a prescreening or monitoring tool
for type 2 diabetes mellitus (T2DM) by examining the differences in voice recordings …

IoMT: A medical resource management system using edge empowered blockchain federated learning

T Muazu, M Yingchi, AU Muhammad… - … on Network and …, 2023 - ieeexplore.ieee.org
As data sharing on the Internet of Medical Things (IoMT) become more complicated, the
problems of divergent interests, unregulated policies, privacy and security, and the resource …

High-level CNN and machine learning methods for speaker recognition

G Costantini, V Cesarini, E Brenna - Sensors, 2023 - mdpi.com
Speaker Recognition (SR) is a common task in AI-based sound analysis, involving
structurally different methodologies such as Deep Learning or “traditional” Machine …

Mouth sounds: A review of Acoustic Applications and methodologies

NE Naal-Ruiz, EA Gonzalez-Rodriguez… - Applied Sciences, 2023 - mdpi.com
Mouth sounds serve several purposes, from the clinical diagnosis of diseases to emotional
recognition. The following review aims to synthesize and discuss the different methods to …

[HTML][HTML] Voice disorder multi-class classification for the distinction of Parkinson's disease and adductor spasmodic dysphonia

V Cesarini, G Saggio, A Suppa, F Asci, A Pisani… - Applied Sciences, 2023 - mdpi.com
Parkinson's Disease and Adductor-type Spasmodic Dysphonia are two neurological
disorders that greatly decrease the quality of life of millions of patients worldwide. Despite …

Sound as a bell: a deep learning approach for health status classification through speech acoustic biomarkers

Y Wang, H Wang, Z Li, H Zhang, L Yang, J Li, Z Tang… - Chinese Medicine, 2024 - Springer
Background Human health is a complex, dynamic concept encompassing a spectrum of
states influenced by genetic, environmental, physiological, and psychological factors …

A hard knowledge regularization method with probability difference in thorax disease images

Q Guan, Q Chen, Z Zhong, Y Huang, Y Zhao - Knowledge-Based Systems, 2023 - Elsevier
The computer-aided thorax disease diagnosis suffers from the existing noisy labels in large-
scale datasets. Especially, the fine-grained thorax images also show high inter-similarity …

Acoustic analysis in stuttering: a machine-learning study

F Asci, L Marsili, A Suppa, G Saggio, E Michetti… - Frontiers in …, 2023 - frontiersin.org
Background Stuttering is a childhood-onset neurodevelopmental disorder affecting speech
fluency. The diagnosis and clinical management of stuttering is currently based on …