Journal Article

·2020

Estimation of Parkinson’s disease severity using speech features and extreme gradient boosting

Hünkar Can Tunç , C. Okan Sakar , Hülya Apaydın , Görkem Serbes YTU , Ayşegül Gündüz , Melih Tütüncü , Fikret Gürgen

Medical & Biological Engineering & Computing

No open-access abstract is available for this article. Use the DOI link on the right to read the full text.

Keywords

Feature selection Gradient boosting Boosting (machine learning) Computer science Artificial intelligence Machine learning Decision tree Metric (unit) Feature (linguistics) Speech recognition Random forest Engineering

Subject Areas

Voice and Speech Disorders ·Physiology ·Health Sciences
Dysphagia Assessment and Management ·Speech and Hearing ·Health Sciences
Speech Recognition and Synthesis ·Artificial Intelligence ·Physical Sciences

Citations by Year

OpenAlex SDG Match

SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).

Peace, Justice and strong institutions 44%

Related Articles

Other articles contributing to the same SDGs.

2026

Measurements of $$ \textrm{t}\overline{\textrm{t}}\textrm{W} $$ differential cross sections and the leptonic charge asymmetry at $$ \sqrt{s}=13 $$ TeV

Journal of High Energy Physics

2026 · 1 citations

From Delivery Delays to AI-Mediated Escalation Failures: A BERTopic Analysis of Complaints About Risk and Trust in E-Commerce Marketplaces (2019–2025)

Journal of theoretical and applied electronic commerce research

2026 · 2 citations

Explainable address matching in online geocoding: filter-based feature selection and ensemble classification

GeoInformatica

2026

The Transparency Paradox: How Digital Accountability Can Inflate Public Costs in Low-Trust Environments

Journal of Management in Engineering
All articles