Invited lecture2025
Enhanced Hybrid AI-Based Framework for Improving the Detection and Diagnosis of Alzheimer’s Disease
The record
- Type
- Invited lecture
- Date
- 14 November 2025
- Level
- International — held in India
- Location
- Faridabad, Haryana, India
- School
- Reporting cycle
- 2025
- Programme
- International Conference on Digital Innovation for Sustainable Solutions (ICDISS 2025)
- Role
- Paper Presenter
- Organiser
- School of Computer Applications, Manav Rachna International Institute of Research and Studies
- People presenting
- 1
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
Tier B rule disease-noncommunicable matched "alzheimer" in the record’s own title. Names a non-communicable disease, which is target 3.4 exactly.
- Certain confidence
- The record states the subject matter explicitly. A reader shown only the title and this goal would agree without hesitation. Example: a workshop titled "Renewable Energy and Smart Grid" against SDG 7.
- 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
- tier-b-lexicon-v2, under kortex-input-v1+rubric@1.1.0#7bc5877481c9+lexicon@tier-b-lexicon-v2#fb739e066356Input template kortex-input-v1; rubric 1.1.0; lexicon tier-b-lexicon-v2. Each can change without the others, which is why the version is a composite.
3 Ensure healthy lives and promote well-being for all at all ages
Tier B rule health-general matched "diagnosis" in the record’s own title. Names a clinical, medical or public-health subject, which the rubric requires for SDG 3 rather than a merely biological one.
- 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.
- Produced by
- tier-b-lexicon-v2, under kortex-input-v1+rubric@1.1.0#7bc5877481c9+lexicon@tier-b-lexicon-v2#fb739e066356Input template kortex-input-v1; rubric 1.1.0; lexicon tier-b-lexicon-v2. Each can change without the others, which is why the version is a composite.
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Tier B rule computing-and-ai matched "ai" in the record’s own title. Names computing, data or artificial intelligence as the method or the subject. Target 9.5 unless an applied domain also fires, in which case the domain takes the primary and this takes the secondary.
- Produced by
- tier-b-lexicon-v2, under kortex-input-v1+rubric@1.1.0#7bc5877481c9+lexicon@tier-b-lexicon-v2#fb739e066356Input template kortex-input-v1; rubric 1.1.0; lexicon tier-b-lexicon-v2. Each can change without the others, which is why the version is a composite.
17.16 Enhance the global partnership for sustainable development, complemented by multi-stakeholder partnerships
Structural signal: an international-level designation with no named counterpart.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- sdg17-structural-v1, under kortex-input-v1+rubric@1.1.0#7bc5877481c9+lexicon@tier-b-lexicon-v2#fb739e066356Input template kortex-input-v1; rubric 1.1.0; lexicon tier-b-lexicon-v2. Each can change without the others, which is why the version is a composite.
Viksit Bharat @2047
vb-1 Empowered Indians
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Tier B rule disease-noncommunicable matched "alzheimer" in the record’s own title. Names a non-communicable disease, which is target 3.4 exactly.
- Produced by
- tier-b-lexicon-v2, under kortex-input-v1+rubric@1.1.0#7bc5877481c9+lexicon@tier-b-lexicon-v2#fb739e066356Input template kortex-input-v1; rubric 1.1.0; lexicon tier-b-lexicon-v2. Each can change without the others, which is why the version is a composite.
Records of this type were classified by a published, versioned rule set, over 5,246 activities. Each label above carries the rubric version it was produced under. How each classification is reached.
Evidence
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Provenance
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- Source rows resolved into this record
- 1
- Source records held
- 1
| Source system | Reference | Last read |
|---|---|---|
| KIIT PBAS reporting workbook (consolidated) | Data - Invited Lecture!1121 |
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
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KIIT Deemed to be University. “Enhanced Hybrid AI-Based Framework for Improving the Detection and Diagnosis of Alzheimer’s Disease”. Kortex. Last read 17 September 2026.