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Effectiveness of Modern Diagnostic and Therapeutic Interventions for Major Neurological Disorders: A Systematic Literature Review
Srivastava V.. Research Square, 2026-08-12
Topic: Brain imaging, connectivity and assessment
Results From 464 identified records, 30 peer-reviewed primary studies met all eligibility criteria following the exclusion of low-quality sources and unindexed preprints. Machine learning models, particularly deep convolutional neural networks applied to brain MRI and EEG, demonstrated diagnostic accuracies ranging from 91.2% to 96.4% across multi-class neurodegenerative conditions. Repetitive Transcranial Magnetic Stimulation (rTMS) and advanced neurorehabilitation (robotics, vagus nerve stimulation) yielded statistically significant functional recovery in post-stroke motor deficits and treatment-resistant epilepsy.
Key findings
- Results From 464 identified records, 30 peer-reviewed primary studies met all eligibility criteria following the exclusion of low-quality sources and unindexed preprints.
- Machine learning models, particularly deep convolutional neural networks applied to brain MRI and EEG, demonstrated diagnostic accuracies ranging from 91.2% to 96.4% across multi-class neurodegenerative conditions.
- Repetitive Transcranial Magnetic Stimulation (rTMS) and advanced neurorehabilitation (robotics, vagus nerve stimulation) yielded statistically significant functional recovery in post-stroke motor deficits and treatment-resistant epilepsy.
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Study details
- Study designmeta-analysis
- Effect size91.2% to 96.4%
- Evidence strengthHigh
How this study scored 16/100
Preprint — not yet peer-reviewed. It scored 50 on the same rubric, but non-peer-reviewed sources are capped at 16, so it shows as 16. Scored zero for sample size and studied in people because the record does not state it. We have no data on times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 31 of the 62 points we could judge it on, which is 50 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 2 / 10 | Tier 4 — not a peer-reviewed journal (Research Square) |
| Journal's citation record | 0 / 4 | Not a journal article, so the journal's record does not count |
| Study design | 12 / 12 | A meta-analysis pooling many studies |
| Strength of evidence | 5 / 5 | Rated “high” in our summary |
| Peer-review validation | 4 / 10 | Preprint — not yet peer-reviewed. Hosted on a preprint server. |
| 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 | 2 / 3 | Effect reported as a number, without an interval or test |
| 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 | A review of other studies — randomisation is not credited here |
| 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 | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| 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 | 0 / 2 | Behind a paywall — scores zero |
| Points | 31 / 62 | Scored on 12 of 20 parts. We have no data for the rest, so they are left out: 31 of the 62 points we could judge it on is 50 out of 100. |
| Total | 50 / 100 | Capped to 16 because this is not a peer-reviewed article. |
What each of these 20 components measures, and what this score is not →
Read the original
Free copy unknown: no free-copy check has an answer for this record yet. That does not mean it is paywalled.
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
Srivastava, V. (2026). Effectiveness of Modern Diagnostic and Therapeutic Interventions for Major Neurological Disorders: A Systematic Literature Review. Research Square. https://doi.org/10.21203/rs.3.rs-10630206/v1
Vancouver
Srivastava V. Effectiveness of Modern Diagnostic and Therapeutic Interventions for Major Neurological Disorders: A Systematic Literature Review. Research Square. 2026. doi:10.21203/rs.3.rs-10630206/v1.
BibTeX
@article{srivastava2026-440c4088,
author = {Srivastava, V.},
title = {{Effectiveness of Modern Diagnostic and Therapeutic Interventions for Major Neurological Disorders: A Systematic Literature Review}},
journal = {Research Square},
year = {2026},
doi = {10.21203/rs.3.rs-10630206/v1},
url = {https://doi.org/10.21203/rs.3.rs-10630206/v1}
}
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