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Neurocapsule : Alzheimer Risk Predictor and Digital Memory Vault
Rucha Gharve, Pratik Surwade, Shejal Ambre, Pareenita Shirsath, Suresh B. Pingale. Zenodo (CERN European Organization for Nuclear Research), 2026-04-07
Topic: Amyloid, tau and blood-test diagnosis
Alzheimer's disease is a progressive neurodegenerative disorder that significantly impacts memory, cognition, and daily functioning. Early diagnosis plays a crucial role in slowing disease progression and improving patient care. This paper presents NeuroCapsule, an intelligent system designed for early detection of Alzheimer's disease using brain MRI images combined with artificial intelligence techniques. The proposed approach employs convolutional neural networks (CNNs) for automated feature extraction and classification of MRI scans into multiple cognitive stages, including Non-Demented, Very Mild Dementia, Mild Dementia, and Moderate Dementia. To address class imbalance and computational constraints, balanced sampling strategies and image downsampling techniques are applied. The system is evaluated on the OASIS MRI dataset, demonstrating high classification accuracy and efficient performance across both binary and multiclass tasks. Unlike traditional convolutional neural networks, NeuroCapsule extends beyond prediction by integrating a secure Digital Memory Vault that enables users to store reminders, notes, and personal records, supporting continuous cognitive management. Experimental results indicate that the proposed system achieves a favorable trade-off between accuracy and computational efficiency, making it suitable for real-world deployment. The integration of predictive analytics with memory assistance enhances both clinical relevance and patient-centered care, positioning NeuroCapsule as a comprehensive solution for Alzheimer's disease detection and management.
Key findings
- Alzheimer's disease is a progressive neurodegenerative disorder that significantly impacts memory, cognition, and daily functioning.
- Experimental results indicate that the proposed system achieves a favorable trade-off between accuracy and computational efficiency, making it suitable for real-world deployment.
Why it matters
This paper presents NeuroCapsule, a system using convolutional neural networks on MRI scans to classify cognitive stages, plus a Digital Memory Vault for storing reminders and personal records. It reports a favorable trade-off between accuracy and computational efficiency on the OASIS dataset, but it is a detection and management tool, not a treatment, cure or prevention.
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Study details
- Evidence strengthLow
How this study scored 41/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 26 of the 64 points we could judge it on, which is 41 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Zenodo (CERN European Organization for Nuclear Research)) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 1 / 2 | Not in PubMed, but has a DOI |
| Free to read | 2 / 2 | Free to read |
| Points | 26 / 64 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 26 of the 64 points we could judge it on is 41 out of 100. |
| Total | 41 / 100 | — |
What each of these 20 components measures, and what this score is not →
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
APA 7th
Gharve, R., Surwade, P., Ambre, S., Shirsath, P., & Pingale, S. B. (2026). Neurocapsule : Alzheimer Risk Predictor and Digital Memory Vault. Zenodo (CERN European Organization for Nuclear Research). https://doi.org/10.5281/zenodo.19451715
Vancouver
Gharve R, Surwade P, Ambre S, Shirsath P, Pingale SB. Neurocapsule : Alzheimer Risk Predictor and Digital Memory Vault. Zenodo (CERN European Organization for Nuclear Research). 2026. doi:10.5281/zenodo.19451715.
BibTeX
@article{gharve2026-29e4a3d3,
author = {Gharve, Rucha and Surwade, Pratik and Ambre, Shejal and Shirsath, Pareenita and Pingale, Suresh B.},
title = {{Neurocapsule : Alzheimer Risk Predictor and Digital Memory Vault}},
journal = {Zenodo (CERN European Organization for Nuclear Research)},
year = {2026},
doi = {10.5281/zenodo.19451715},
url = {https://doi.org/10.5281/zenodo.19451715}
}
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