---
title: "Deep-learning localisation of the seizure onset zone from routine scalp EEG"
id: "biorxiv-3-localising-the-seizure-onset-zone-from-routine-interictal-and-ictal-scalp-eeg"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-3-localising-the-seizure-onset-zone-from-routine-interictal-and-ictal-scalp-eeg"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1?rss=1"
published_at: "2026-10-22T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Deep-learning localisation of the seizure onset zone from routine scalp EEG
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-3-localising-the-seizure-onset-zone-from-routine-interictal-and-ictal-scalp-eeg
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1?rss=1)
- **Published At:** 2026-10-22T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The study developed a deep-learning framework to localise the **seizure onset zone** (SOZ) at lobar level using routine interictal and ictal **scalp EEG**. - Investigators curated 262 sessions totalling over 6,000 hours from 100 patients with unilateral focal epilepsy; they used an internal 28-patient and an external 9-patient dataset for additional evaluation. - The pipeline combined online augmentation (Gaussian noise, amplitude scaling, temporal cropping, hemispheric channel swap), a multi-scale temporal block for 20–200 ms discharge morphologies, a factorised spatiotemporal Transformer decoupling temporal and spatial attention, and a hemispheric mutual exclusivity penalty. - A heterogeneous five-model ensemble was fused via model soup and evaluated on held-out, seizure-free, and cross-institutional cohorts. - Session-level exact match accuracy on internal test data reached 88.46%, versus EEGNet at 50.00%; seizure-free holdout accuracy was 82.76% and cross-institutional accuracy was 84.62%. - The rare occipital class recall improved from 0.500 to 1.000; healthy controls (n=108) produced zero false positives. - Unlabelled random segments produced 66.67% accuracy compared with a 14% chance baseline. - Processing time for a full 24-hour recording was 4.26 minutes, and inference ran in under 8 seconds, facilitating identification of localising windows for targeted expert review. - The authors framed this tool as an adjunct to clinical judgement that might reduce dependence on prolonged monitoring or invasive implantation; the preprint has not undergone peer review.
## Clinical Analysis & Structured Key Points
[Skip to main content](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1?rss=1#main-content) [![bioRxiv](https://www.biorxiv.org/sites/default/files/biorxiv_article_logo.jpg)](https://www.biorxiv.org/) * [Home](https://www.biorxiv.org/) * [Submit](https://www.biorxiv.org/submit-a-manuscript) * [FAQ](https://www.biorxiv.org/about/FAQ) * [Blog](https://connect.biorxiv.org/news/) * [ALERTS / RSS](https://www.biorxiv.org/content/alertsrss) * [Resources](https://connect.biorxiv.org/resources/) * [About](https://www.biorxiv.org/content/about-biorxiv) * [Channels](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1?rss=1) * [4D Nucleome](https://connect.biorxiv.org/relate/content/66) * [Academia Sinica](https://connect.biorxiv.org/group/content/38) * [Advances in Genome Biology and Technology (AGBT) General Meeting 2016 #AGBT16](https://connect.biorxiv.org/relate/content/10) * [Albert Einstein College of Medicine](https://connect.biorxiv.org/group/content/4) * [Aligning Science Across Parkinson's (ASAP)](https://connect.biorxiv.org/relate/content/195) * [Allen Institute for Cell Science](https://connect.biorxiv.org/relate/content/71) * [Arc Institute](https://connect.biorxiv.org/relate/content/224) * [Babraham Institute](https://connect.biorxiv.org/relate/content/197) * [BICCN/BICAN](https://connect.biorxiv.org/relate/content/208) * [BioImaging North America](https://connect.biorxiv.org/relate/content/194) * [Biology of Genomes 2016 #BOG16](https://connect.biorxiv.org/relate/content/19) * [Breakthrough Discoveries for Thriving with Bipolar Disorder](https://connect.biorxiv.org/relate/content/236) * [Brown University](https://connect.biorxiv.org/group/content/9) * [California Institute of Technology](https://connect.biorxiv.org/group/content/32) * [Carnegie Mellon University](https://connect.biorxiv.org/group/content/19) * [Case Western Reserve University](https://connect.biorxiv.org/group/content/36) * [Central Oxford Structural Microscopy and Imaging](https://connect.biorxiv.org/relate/content/143) * [Centre for Microbiology and Environmental Systems Science](https://connect.biorxiv.org/relate/content/190) * [Chan Zuckerberg Biohub](https://connect.biorxiv.org/relate/content/121) * [Columbia University](https://connect.biorxiv.org/group/content/27) * [Donders Institute for Brain, Cognition and Behaviour](https://connect.biorxiv.org/relate/content/184) * [DREAM](https://connect.biorxiv.org/relate/content/153) * [Drug Development and Clinical Therapeutics](https://connect.biorxiv.org/relate/content/52) * [ENCODE](https://connect.biorxiv.org/relate/content/177) * [Ernst Strüngmann Institute (ESI) for Neuroscience](https://connect.biorxiv.org/relate/content/211) * [European Molecular Biology Laboratory (EMBL)](https://connect.biorxiv.org/relate/content/159) * [Francis Crick Institute](https://connect.biorxiv.org/relate/content/88) * [Fred Hutchinson Cancer Center](https://connect.biorxiv.org/group/content/28) * [Georgia Institute of Technology](https://connect.biorxiv.org/group/content/20) * [Harvard Program in Therapeutic Sciences](https://connect.biorxiv.org/relate/content/151) * [The Howard Hughes Medical Institute (HHMI)](https://connect.biorxiv.org/relate/content/227) * [Human Cell Atlas](https://connect.biorxiv.org/relate/content/163) * [Human Pangenome Reference Consortium (HPRC)](https://connect.biorxiv.org/relate/content/215) * [IMO Workshop](https://connect.biorxiv.org/relate/content/8) * [Impact of Genomic Variation on Function (IGVF)](https://connect.biorxiv.org/relate/content/214) * [Institut Pasteur](https://connect.biorxiv.org/relate/content/235/channel) * [Institute of Science and Technology Austria](https://connect.biorxiv.org/group/content/12) * [International Human Epigenome Consortium (IHEC)](https://connect.biorxiv.org/relate/content/219) * [International Mouse Phenotyping Consortium (IMPC)](https://connect.biorxiv.org/relate/content/185) * [Iowa State University](https://connect.biorxiv.org/group/content/6) * [Johns Hopkins University](https://connect.biorxiv.org/group/content/47) * [Mathematical Oncology](https://connect.biorxiv.org/relate/content/1) * [Micron Oxford](https://connect.biorxiv.org/relate/content/116) * [Michigan State University](https://connect.biorxiv.org/group/content/7) * [Morgridge Institute](https://connect.biorxiv.org/group/content/57) * [National Taiwan University](https://connect.biorxiv.org/group/content/39) * [NCI Cancer Systems Biology Consortium](https://connect.biorxiv.org/relate/content/210) * [NF Open Science Initiative](https://connect.biorxiv.org/relate/content/213) * [NCI Human Tumor Atlas Network](https://connect.biorxiv.org/relate/content/171) * [Neuromatch Conference](https://connect.biorxiv.org/relate/content/209) * [NeurotechEU](https://connect.biorxiv.org/relate/content/189) * [North Carolina State University](https://connect.biorxiv.org/group/content/37) * [Northeastern University](https://connect.biorxiv.org/group/content/54) * [Oregon Health & Sciences University](https://connect.biorxiv.org/group/content/22) * [RNA Therapeutics Institute at UMass Chan Med School](https://connect.biorxiv.org/relate/content/243) * [Rosetta Commons](https://connect.biorxiv.org/relate/content/191) * [Rutgers University](https://connect.biorxiv.org/group/content/31) * [SeroNet](https://connect.biorxiv.org/relate/content/192) * [Simons Foundation Autism Research Initiative (SFARI)](https://connect.biorxiv.org/relate/content/74) * [Society for Molecular Biology and Evolution #SMBE2016](https://connect.biorxiv.org/relate/content/29) * [Somatic Cell Genome Editing Program](https://connect.biorxiv.org/relate/content/167) * [Somatic Mosaicism across the Human Tissues Network](https://connect.biorxiv.org/relate/content/222) * [SPARC](https://connect.biorxiv.org/relate/content/187) * [Stowers Institute for Medical Research](https://connect.biorxiv.org/group/content/3) * [Stockholm University](https://connect.biorxiv.org/group/content/14) * [Tel Aviv University](https://connect.biorxiv.org/group/content/8) * [The Michael J. Fox Foundation](https://connect.biorxiv.org/relate/content/207) * [The Rockefeller University](https://connect.biorxiv.org/group/content/2) * [The Sainsbury Laboratory](https://connect.biorxiv.org/relate/content/98) * [The Whitehead Institute](https://connect.biorxiv.org/relate/content/212) * [University of Connecticut Health Center](https://connect.biorxiv.org/group/content/16) * [University of California, Berkeley](https://connect.biorxiv.org/group/content/13) * [University of California, San Diego](https://connect.biorxiv.org/group/content/41) * [University of California, San Francisco](https://connect.biorxiv.org/group/content/10) * [University of Chicago](https://connect.biorxiv.org/group/content/42) * [University of Geneva](https://connect.biorxiv.org/group/content/26) * [University of Guelph](https://connect.biorxiv.org/group/content/23) * [University of Hong Kong](https://connect.biorxiv.org/group/content/29) * [University of Illinois Chicago](https://connect.biorxiv.org/group/content/43) * [University of Iowa](https://connect.biorxiv.org/group/content/24) * [University of Kansas](https://connect.biorxiv.org/group/content/33) * [University of Massachusetts Chan Medical School](https://connect.biorxiv.org/group/content/44) * [University of New South Wales](https://connect.biorxiv.org/group/content/25) * [University of Ottawa](https://connect.biorxiv.org/group/content/35) * [University of Sydney](https://connect.biorxiv.org/group/content/50) * [Vanderbilt University](https://connect.biorxiv.org/group/content/30) * [Vienna BioCenter](https://connect.biorxiv.org/relate/content/186) * [Washington University in St. Louis](https://connect.biorxiv.org/group/content/11) * [Weizmann Institute of Science](https://connect.biorxiv.org/group/content/15) * [Yale University](https://connect.biorxiv.org/group/content/53) Search for this keyword [Advanced Search](https://www.biorxiv.org/search) New Results Follow this preprint # Localising the Seizure Onset Zone from Routine Interictal and Ictal Scalp EEG Via a Factorised Spatiotemporal Ensemble Deep Learning Framework Songyuan Shi doi: https://doi.org/10.64898/2026.10.16.759501 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. Songyuan Shi University College London * [Find this author on Google Scholar](https://www.biorxiv.org/lookup/google-scholar?link_type=googlescholar&gs_type=author&author%5B0%5D=Songyuan%2BShi%2B "Open in new tab") * [Find this author on PubMed](https://www.biorxiv.org/lookup/external-ref?access_num=Shi%20S&link_type=AUTHORSEARCH "Open in new tab") * [Search for this author on this site](https://www.biorxiv.org/search/author1%3ASongyuan%2BShi%2B) * For correspondence: vincent.shi.22@ucl.ac.uk * [Abstract](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_art/node:5894172/1) * [Info/History](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1.article-info)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_info/node:5894172/1) * [Metrics](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1.article-metrics)[](https://www.biorxiv.org/panels_ajax_tab/article_tab_metrics/node:5894172/1) * [ Preview PDF](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1.full.pdf+html)[](https://www.biorxiv.org/panels_ajax_tab/biorxiv_tab_pdf/node:5894172/1) ![Loading](https://www.biorxiv.org/sites/all/modules/contrib/panels_ajax_tab/images/loading.gif) ## Abstract Background: Drug-resistant focal epilepsy requires precise localisation of the epileptogenic zone (EZ) for surgical resection. Current practice depends on invasive recordings or spontaneous seizure capture, a costly and risky bottleneck. Interictal scalp EEG can exhibit localising features like spikes, but scalp EEG suffers from volume conduction (the smearing of brain signals across multiple electrodes) and low signal-to-noise ratio (SNR), which obscure subtle spatial dynamics. Neurophysiologist review of long, often multi-day recordings is time-consuming and expertise-dependent, and while computational methods exist, they tend to rely heavily on human-designed features. Deep learning for EEG localisation could therefore help to improve clinical efficiency and sensitivity. Objectives: To develop and validate a non-invasive deep learning approach for lobar-level localisation of the seizure onset zone (SOZ), the primary electrophysiological proxy for the epileptogenic zone (EZ), using interictal and ictal segments from routine scalp EEG. The model is trained on expert-annotated clinical labels and is intended to augment, not supplant, clinical judgement in EZ delineation. Methods: We curated 262 sessions (6,000+ hours) from 100 patients with unilateral focal epilepsy, tested with an extra 28-patient internal and a 9-patient external dataset. The framework integrates: (1) an online augmentation pipeline (Gaussian noise, amplitude scaling, temporal cropping, and hemispheric channel swap) to mitigate overfitting. (2) a multi-scale temporal block for 20-200 ms discharge morphologies; (3) a factorised spatiotemporal Transformer decoupling temporal and spatial attention to counter volume conduction; and (4) a hemispheric mutual exclusivity penalty encoding unilateral priors. A five-model heterogeneous ensemble, fused via model soup, was evaluated on held-out, seizure-free, and cross-institutional cohorts. Results: The ensemble achieved 88.46% session-level exact match on internal test data, outperforming EEGNet (50.00%). Performance generalised to the seizure-free holdout set (82.76%) and to cross-institutional data (84.62%). Rare occipital class (RO) recall rose from 0.500 to 1.000, with zero false positives on healthy controls (n=108). On unlabelled random segments, accuracy was 66.67% (vs. 14% chance). A full 24-hour recording was processed in 4.26 minutes, with inference under 8 seconds, highlighting localising windows for targeted expert clinical review Conclusion: Clinically actionable SOZ spatial information is encoded in routine interictal scalp EEG. Our factorised ensemble provides a safe, interpretable, and efficient tool to expedite presurgical evaluation, potentially reducing reliance on prolonged monitoring and invasive implantation. ### Competing Interest Statement The authors have declared no competing interest. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a [CC-BY 4.0 International license](http://creativecommons.org/licenses/by/4.0/). bioRxiv and medRxiv thank the following for their generous financial support: > The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam. [Donate to openRxiv ](https://www.zeffy.com/en-US/donation-form/donate-to-make-a-difference-10981) [ Back to top](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1?rss=1#page) [ Previous](https://www.biorxiv.org/content/10.64898/2026.10.16.759478v1 "Computational modeling of breast cancer metastases predicts response to dual checkpoint inhibition and reveals spatially-informed treatments")[Next ](https://www.biorxiv.org/content/10.64898/2026.10.16.759774v1 "Differential Protection against Acetaminophen-induced Liver and Kidney Injury by N-Acetylcysteine and Fomepizole in Female Mice") Posted October 22, 2026. [ Download PDF](https://www.biorxiv.org/content/10.64898/2026.10.16.759501v1.full.pdf) Print/Save Options [Download PDF](https://www.biorxiv.org/content/biorxiv/early/2026/10/22/2026.10.16.759501.full.pdf)Full Text & In-line FiguresXML [More Info](https://www.biorxiv.org/about/FAQ#PrintOptions "More Information on Print/Save Options") [ Email](https://www.biorxiv.org/ "Email this Article") [ Share](https://www.biorxiv.org/) Localising the Seizure Onset Zone from Routine Interictal and Ictal Scalp EEG Via a Factorised Spatiotemporal Ensemble Deep Learning Framework Songyuan Shi bioRxiv 2026.10.16.759501; doi: https://doi.org/10.64898/2026.10.16.759501 This article is a preprint and has not been certified by peer review [[what does this mean?](https://www.biorxiv.org/about/FAQ#unrefereed)]. Share This Article: Copy [![Twitter logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/twitter.png)](https://www.biorxiv.org/highwire_log/share/twitter?link=http%3A%2F%2Ftwitter.com%2Fshare%3Furl%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.10.16.759501v1%26text%3DLocalising%2520the%2520Seizure%2520Onset%2520Zone%2520from%2520Routine%2520Interictal%2520and%2520Ictal%2520Scalp%2520EEG%2520Via%2520a%2520Factorised%2520Spatiotemporal%2520Ensemble%2520Deep%2520Learning%2520Framework "Share this on Twitter") [![Facebook logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/fb-blue.png)](https://www.biorxiv.org/highwire_log/share/facebook?link=http%3A%2F%2Fwww.facebook.com%2Fsharer.php%3Fu%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.10.16.759501v1%26t%3DLocalising%2520the%2520Seizure%2520Onset%2520Zone%2520from%2520Routine%2520Interictal%2520and%2520Ictal%2520Scalp%2520EEG%2520Via%2520a%2520Factorised%2520Spatiotemporal%2520Ensemble%2520Deep%2520Learning%2520Framework "Share on Facebook") [![LinkedIn logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/linkedin-32px.png)](https://www.biorxiv.org/highwire_log/share/linkedin?link=http%3A%2F%2Fwww.linkedin.com%2FshareArticle%3Fmini%3Dtrue%26url%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.10.16.759501v1%26title%3DLocalising%2520the%2520Seizure%2520Onset%2520Zone%2520from%2520Routine%2520Interictal%2520and%2520Ictal%2520Scalp%2520EEG%2520Via%2520a%2520Factorised%2520Spatiotemporal%2520Ensemble%2520Deep%2520Learning%2520Framework%26summary%3D%26source%3DbioRxiv "Publish this post to LinkedIn") [![Mendeley logo](https://www.biorxiv.org/sites/all/modules/highwire/highwire/images/mendeley.png)](https://www.biorxiv.org/highwire_log/share/mendeley?link=http%3A%2F%2Fwww.mendeley.com%2Fimport%2F%3Furl%3Dhttps%253A%2F%2Fwww.biorxiv.org%2Fcontent%2F10.64898%2F2026.10.16.759501v1%26title%3DLocalising%2520the%2520Seizure%2520Onset%2520Zone%2520from%2520Routine%2520Interictal%2520and%2520Ictal%2520Scalp%2520EEG%2520Via%2520a%2520Factorised%2520Spatiotemporal%2520Ensemble%2520Deep%2520Learning%2520Framework "Share on Mendeley") [ Citation Tools](https://www.biorxiv.org/ "Citation Tools") [ Get QR code](https://connect.biorxiv.org/qr/2026.10.16.759501) * [Tweet Widget](http://twitter.com/share?url=https%3A//www.biorxiv.org/content/10.64898/2026.10.16.759501v1&count=horizontal&via=&text=Localising%20the%20Seizure%20Onset%20Zone%20from%20Routine%20Interictal%20and%20Ictal%20Scalp%20EEG%20Via%20a%20Factorised%20Spatiotemporal%20Ensemble%20Deep%20Learning%20Framework&counturl=www.biorxiv.org/content/10.64898/2026.10.16.759501v1 "Tweet This") Reviews and Context 0 Comment 0 TRIP Peer Reviews 0 Community Reviews 0 Automated Services 0 Blogs/Media 0 Author Videos **Subject Areas** [**All Articles**](https://www.biorxiv.org/content/early/recent) * [Animal Behavior and Cognition](https://www.biorxiv.org/collection/animal-behavior-and-cognition) (8164) * [Animal Behavior and Cognition](https://www.biorxiv.org/collection/animal-behavior-and-cognition-0) (8173) * Animal Behavior and Cognition * [Biochemistry](https://www.biorxiv.org/collection/biochemistry) (19027) * Biochemistry * [Biochemistry](https://www.biorxiv.org/taxonomy/term/318468) (19029) * Biochemistry * [Biochemistry](https://www.biorxiv.org/taxonomy/term/318471) (19029) * [Biochemistry](https://www.biorxiv.org/collection/biochemistry-1) (19029) * Biochemistry * [Biochemistry](https://www.biorxiv.org/collection/biochemistry-0) (19047) * [Biochemistry](https://www.biorxiv.org/collection/biochemistry-11) (19030) * [Bioengineering](https://www.biorxiv.org/collection/bioengineering) (15171) * Bioengineering * [Bioengineering](https://www.biorxiv.org/collection/bioengineering-0) (15191) * [Bioengineering](https://www.biorxiv.org/taxonomy/term/318482) (15172) * [Bioengineering](https://www.biorxiv.org/collection/bioengineering-2) (15176) * [Bioinformatics](https://www.biorxiv.org/collection/bioinformatics) (45308) * [Bioinformatics](https://www.biorxiv.org/collection/bioinformatics-0) (45254) * [Bioinformatics](https://www.biorxiv.org/collection/bioinformatics-1) (45257) * [Biophysics](https://www.biorxiv.org/collection/biophysics) (22958) * [Biophysics](https://www.biorxiv.org/collection/biophysics-0) (22972) * [Biophysics](https://www.biorxiv.org/taxonomy/term/318443) * [Biophysics](https://www.biorxiv.org/taxonomy/term/318450) (22958) * [Biophysics](https://www.biorxiv.org/taxonomy/term/318507) (22961) * [Cancer Biology](https://www.biorxiv.org/collection/cancer-biology) (20101) * [Cancer Biology](https://www.biorxiv.org/collection/cancer-biology-0) (20080) * [Cell Biology](https://www.biorxiv.org/collection/cell-biology) (27289) * [Clinical Trials](https://www.biorxiv.org/collection/clinical-trials)
## Related Clinical Research

- [Rostral–caudal subthalamic nucleus encoding of flexible versus habitual value in primates](https://medichelpline.com/clinical-feed/biorxiv-3-differential-value-processing-in-the-rostral-and-causal-subthalamic-nucleus.md)
- [Scalp EEG Signatures of Anterior Thalamic DBS: Reproducible Gamma Enhancement](https://medichelpline.com/clinical-feed/biorxiv-0-acute-scalp-eeg-signatures-of-anterior-thalamic-dbs-in-epilepsy-reproducible.md)
- [Ultra-processed foods linked to MRI signs of vascular brain injury in middle-aged adults](https://medichelpline.com/clinical-feed/medical-news-today-0-ultra-processed-foods-may-be-harming-brain-health-in-otherwise-healthy-adults.md)
- [Global dementia incidence projected to reach 24.7 million new cases annually by 2050](https://medichelpline.com/clinical-feed/medical-news-today-0-dementia-cases-to-double-by-2050-why-women-some-countries-may-be-at-higher-risk.md)
- [Sample Size and Power Calculations Using Endpoint Responsiveness for Parkinson’s Disease Trials](https://medichelpline.com/clinical-feed/medrxiv-0-sample-size-and-power-calculations-based-on-endpoint-responsiveness.md)

## Navigation
- [← Back to Neurology Feed](https://medichelpline.com/clinical-feed/neurology.md)
- [← All Clinical Specialties](https://medichelpline.com/clinical-feed.md)
## Medical & Regulatory Disclaimer

> [!CAUTION]
> MedicHelpline content is structured for research, educational, and professional discovery purposes. It does not constitute individual medical advice, clinical diagnosis, or treatment recommendations.
> Always verify dosing, contraindications, and regulatory alerts against official product labeling and primary regulatory sources before clinical decision-making.