Publication2024
PD-DETECTOR: A sustainable and computationally intelligent mobile application model for Parkinson's disease severity assessment
- Good Health and Well-being
- Partnerships for the Goals
- Empowered Indians
The record
- Type
- Publication
- Date
- 30 July 2024
- Level
- International — held abroad
- Journal
- Heliyon
- Volume
- 10
- Issue
- 14
- Published
- 30 July 2024
- DOI
- 10.1016/j.heliyon.2024.e34593
- Scopus ID
- 85198596473
- ISSN
- 24058440
- Authors
- 4
- Open access
- Yes
- Citations
- 34
- International co-authorship
- Yes
- Co-author countries
- IN, TW
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being
Mobile cloud-based deep learning system for Parkinson's disease severity assessment from voice analysis enabling telemonitoring with 96.2% diagnostic accuracy.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-1 Empowered Indians
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Mobile cloud-based deep learning system for Parkinson's disease severity assessment from voice analysis enabling telemonitoring with 96.2% diagnostic accuracy.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “PD-DETECTOR: A sustainable and computationally intelligent mobile application model for Parkinson's disease severity assessment”. Kortex.