To develop an acoustic-based framework for automated extraction of interpretable speech markers for assessing and phenotyping progressive communication disorders in neurodegenerative diseases, thereby enhancing personalized care.
Key Findings:
Markers detected subtle subclinical changes prior to significant declines in communication, indicating early intervention potential.
Markers differentiated disease-specific communicative impairment patterns with high accuracy (multiclass AUC > 0.90), suggesting their utility in clinical settings.
Distinct speech profiles were identified within each disease group, highlighting the variability in communication impairment.
Interpretation:
The framework shows promise as a clinically translatable tool for early detection, differential diagnosis, and phenotyping of communication disorders, enhancing personalized care in neurodegenerative diseases.
Limitations:
The study's sample size may limit generalizability.
Further validation in larger, diverse populations is needed.
Potential biases in participant selection or data collection methods should be considered.
Conclusion:
The proposed framework could facilitate timely interventions and improve quality of life for individuals with neurodegenerative diseases by enabling objective assessment of communication impairments, while further research is needed to validate these findings.
