Related Experiment Video
Updated: Jul 8, 2025
Minimally Invasive Murine Laryngoscopy for Close-Up Imaging of Laryngeal Motion During Breathing and Swallowing
Published on: December 1, 2023
Deep learning in voice analysis for diagnosing vocal cord pathologies: a systematic review
Idit Tessler1,2,3, Adi Primov-Fever4,5, Shelly Soffer6,7
1Department of Otolaryngology Head and Neck Surgery, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel. idit.tessler@gmail.com.
Deep learning models show promise for detecting vocal cord pathologies using voice samples from smartphones. While accuracy is high, current studies have limitations and require further development for widespread clinical use.
Area of Science:
- Otolaryngology
- Artificial Intelligence
- Medical Diagnostics
Background:
- Smartphones and wearable devices enable large-scale voice sampling for health monitoring.
- Vocal cord pathologies require accurate and accessible diagnostic methods.
Approach:
- Systematic literature review adhering to PRISMA guidelines.
- Searched MEDLINE and Embase for studies (2002-2022) on deep learning for vocal cord pathology diagnosis.
- Assessed risk of bias using QUADAS-2.
Key Points:
- Analyzed 14 studies with 3037 patients; all were retrospective.
- Deep learning models targeted various pathologies including Reinke's edema, nodules, polyps, cysts, paralysis, and cancer.
- Most pathologies achieved over 90% detection accuracy, but 93% of studies had high bias risk.
Conclusions:
- Deep learning offers a promising technological approach for vocal cord pathology screening and diagnosis.
- Current research provides proof of concept, but limitations necessitate further development for scalable solutions.
Related Concept Videos
01:21Larynx
Anatomy of the Larynx
The larynx consists of various components, including cartilage, muscles, and vocal cords. Its structure includes three large unpaired cartilages—the thyroid, cricoid, and epiglottis—and three smaller paired cartilages—the arytenoids,...
01:31Respiratory System Abnormal Finding II: Palpation and Auscultation
Palpation Findings
During a respiratory assessment, palpation can reveal several vital abnormalities:
01:28Physical Assessment of the Respiratory Tract IV: Auscultation
Breath Sounds
Breath sounds are categorized into vesicular, bronchovesicular, and bronchial.
01:29Assessment of Ventilation II: Respiratory Depth and Rhythm
Respiratory depth measures the volume of air inhaled or exhaled during a breath. It can vary from shallow to deep and typically remains consistent when a person is at rest or asleep. Occasionally, individuals will automatically inhale deeply, known as sighing, which inflates the lungs with more air than normal breathing.
To assess respiratory depth, observe the degree of chest excursion or movement:
01:30Respiratory System Abnormal Finding I: Inspection and Percussion
Inspection Findings
During an inspection, several findings may suggest the presence of respiratory distress or disease. Pursed-lip breathing, where exhalation is slowed by...
01:27Chronic Obstructive Pulmonary Disease-IV: Assessement and Diagnostic Studies
Medical History