Archives

COPDVD: Automated classification of chronic obstructive pulmonary disease on a new collected and evaluated voice dataset

Abstract Background: Chronic obstructive pulmonary disease (COPD) is a severe condition affectingmillions worldwide, leading to numerous annual deaths. The absence of significant symptomsin its early stages promotes high underdiagnosis rates for the affected people. Besidespulmonary function failure, another harmful problem of COPD is the systemic effects,e.g., heart failure or voice distortion. However, the systemic effects […]

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ELLIIT Annual Workshop 2024

Alper has participated in the ELLIIT Annual Workshop with a poster presentation. The workshop was hosted by Lund University on March 7-8 and the workshop encompassed a breadth of stimulating topics spanning multiple disciplines. Alper’s poster elicited substantial interest, sparking extensive inquiries and discussions from attendees.

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Symposium: Voice and speech research in medicine (Tıpta ses ve konuşma araştırmaları sempozyumu)

Alper was honored with an invitation to participate in a symposium centered on the exploration of voice and speech research within the medical domain, hosted at Gazi University’s Faculty of Medicine in Ankara, Türkiye, on March 06, 2024. The symposium served as a platform for the dissemination of findings from a comprehensive systematic literature review […]

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Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review

Abstract Background:Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic, neurological, and aerodigestive distortion is prone to affect voice production through reduced cognitive, pulmonary, and muscular functionality. This sensitivity inspired using voice as a biomarker to examine disorders that affect the voice. Technological […]

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The DiaVoc project: Diagnosing vocal characteristics to track patients’ health

This project centers on the diagnosis and monitoring of health conditions that impact patients’ vocal characteristics, including Neurocognitive disorders (NCDs) (signifying cognitive decline), pulmonary disorder (COPD), and heart failure conditions (HF). By utilizing longitudinal voice recordings paired with medical data, we aim to create mathematical vocal characteristics, distance metrics, and machine learning methodologies that are […]

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