---
title: "On-device cough detection and respiratory disease classification with generative data augmentation"
id: "pubmed-42229246"
canonical_url: "https://medichelpline.com/clinical-feed/pubmed-42229246"
content_type: "clinical_feed_article"
specialty: "Critical Care"
source_name: "PubMed / NCBI"
source_url: "https://pubmed.ncbi.nlm.nih.gov/42229246/"
doi: "10.1016/j.compbiomed.2026.111784"
published_at: "2026-08-15T00:00:00.000Z"
evidence_level: "Journal Article"
license: "CC-BY-NC-4.0 / Informational Use"
---
# On-device cough detection and respiratory disease classification with generative data augmentation
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/pubmed-42229246
- **Specialty:** [Critical Care](https://medichelpline.com/clinical-feed/critical-care.md)
- **Primary Source:** PubMed / NCBI
- **Source URL:** [Original Journal Publication](https://pubmed.ncbi.nlm.nih.gov/42229246/)
- **DOI:** [10.1016/j.compbiomed.2026.111784](https://doi.org/10.1016%2Fj.compbiomed.2026.111784)
- **Published At:** 2026-08-15T00:00:00.000Z
- **Evidence Rating:** Journal Article
## Executive GIST (TL;DR)
- Cough acoustic signals captured by smartphones are noninvasive biomarkers for assessing respiratory disease and support scalable monitoring. - Existing methods often separate cough detection from disease classification or require server-side deep learning, limiting deployability and raising privacy concerns. - Small, imbalanced cough datasets impede model generalization and reduce classifier reliability for conditions such as asthma and COVID-19. - The authors propose a multilayer, smartphone-compatible AI framework combining real-time **on-device cough detection**, cough-level disease classification, and a novel generative augmentation approach. - The system comprises three modules: a lightweight Cough Detection Module (CDM) for real-time segmentation; a Disease Analysis Module (DAM) that uses parallel Support Vector Machine classifiers and a probabilistic cough-level fusion strategy to classify asthma, COVID-19, or healthy coughs; and a Generative Augmentation Module (GAM) with five Variational Autoencoder variants. - The GAM operates across the time-frequency domain for latent feature optimization and reconstructs samples in the time-domain to preserve acoustic verifiability and enable clinical review of synthetic coughs. - The CDM delivers reliable segmentation across heterogeneous recording conditions and is optimized for on-device execution on commodity Android hardware. - The DAM discriminates between asthma, COVID-19, and healthy coughs using compact cepstral and spectral features and applies probabilistic fusion across cough events. - The multi-variant GAM effectively addresses class imbalance and improves data scarcity scenarios where conventional audio augmentation fails. - All components run in real time on consumer Android devices, supporting privacy-preserving, deployable smartphone-based respiratory health monitoring. - The framework emphasizes interpretability of generative augmentation and addresses dataset availability, model generalizability, and deployability challenges in acoustic cough analytics.
## Clinical Analysis & Structured Key Points
Clipboard, Search History, and several other advanced features are temporarily unavailable. [ Skip to main page content ](https://pubmed.ncbi.nlm.nih.gov/42229246/#article-details) ![U.S. flag](https://cdn.ncbi.nlm.nih.gov/coreutils/uswds/img/favicons/favicon-57.png) An official website of the United States government Here's how you know ![Dot gov](https://cdn.ncbi.nlm.nih.gov/coreutils/uswds/img/icon-dot-gov.svg) **The .gov means it’s official.** Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site. ![Https](https://cdn.ncbi.nlm.nih.gov/coreutils/uswds/img/icon-https.svg) **The site is secure.** The **https://** ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely. [ ![NIH NLM Logo](https://cdn.ncbi.nlm.nih.gov/coreutils/nwds/img/logos/AgencyLogo.svg) ](https://www.ncbi.nlm.nih.gov/) [Log in](https://account.ncbi.nlm.nih.gov/?back_url=https%3A%2F%2Fpubmed.ncbi.nlm.nih.gov%2F42229246%2F) Show account info Close #### Account Logged in as: **username** * [Dashboard](https://www.ncbi.nlm.nih.gov/myncbi/) * [Publications](https://www.ncbi.nlm.nih.gov/myncbi/collections/bibliography/) * [Account settings](https://www.ncbi.nlm.nih.gov/account/settings/) * [Log out](https://www.ncbi.nlm.nih.gov/account/signout/?back_url=https%3A//pubmed.ncbi.nlm.nih.gov/42229246/) [Access keys](https://www.ncbi.nlm.nih.gov/guide/browsers/#ncbi_accesskeys) [NCBI Homepage](https://www.ncbi.nlm.nih.gov) [MyNCBI Homepage](https://pubmed.ncbi.nlm.nih.gov/myncbi/) [Main Content](https://pubmed.ncbi.nlm.nih.gov/42229246/#maincontent) [Main Navigation](https://pubmed.ncbi.nlm.nih.gov/42229246/) [ ![pubmed logo](https://cdn.ncbi.nlm.nih.gov/pubmed/af7de7da-df5d-41c6-8de4-8c266af8ccfb/core/images/pubmed-logo-blue.svg) ](https://pubmed.ncbi.nlm.nih.gov/) [ ](https://pubmed.ncbi.nlm.nih.gov/42229246/ "Show search bar") Search: [](https://pubmed.ncbi.nlm.nih.gov/42229246/ "Clear search input")Search [Advanced](https://pubmed.ncbi.nlm.nih.gov/advanced/) [ Clipboard ](https://pubmed.ncbi.nlm.nih.gov/clipboard/) [ User Guide ](https://pubmed.ncbi.nlm.nih.gov/help/) Save Email Send to * [ Clipboard ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * [My Bibliography](https://account.ncbi.nlm.nih.gov/?back_url=https%3A%2F%2Fpubmed.ncbi.nlm.nih.gov%2F42229246%2F%23open-bibliography-panel) * [Collections](https://account.ncbi.nlm.nih.gov/?back_url=https%3A%2F%2Fpubmed.ncbi.nlm.nih.gov%2F42229246%2F%23open-collections-panel) * [Citation manager](https://pubmed.ncbi.nlm.nih.gov/42229246/) Display options Display options Format Abstract PubMed PMID ## Save citation to file Format: Summary (text) PubMed PMID Abstract (text) CSV Create file Cancel ## Email citation Email address has not been verified. Go to [ My NCBI account settings ](https://account.ncbi.nlm.nih.gov/settings/) to confirm your email and then refresh this page. To: Subject: Body: Format: Summary Summary (text) Abstract Abstract (text) MeSH and other data Send email Cancel ### Add to Collections * Create a new collection * Add to an existing collection Name your collection: Name must be less than 100 characters Choose a collection: Unable to load your collection due to an error [Please try again](https://pubmed.ncbi.nlm.nih.gov/42229246/) Add Cancel ### Add to My Bibliography * My Bibliography Unable to load your delegates due to an error [Please try again](https://pubmed.ncbi.nlm.nih.gov/42229246/) Add Cancel ## Your saved search Name of saved search: Search terms: [Test search terms](https://pubmed.ncbi.nlm.nih.gov/42229246/) Would you like email updates of new search results? Saved Search Alert Radio Buttons * Yes * No Email: ([change](https://www.ncbi.nlm.nih.gov/account/settings/)) Frequency: Monthly Weekly Daily Which day? The first Sunday The first Monday The first Tuesday The first Wednesday The first Thursday The first Friday The first Saturday The first day The first weekday Which day? Sunday Monday Tuesday Wednesday Thursday Friday Saturday Report format: Summary Summary (text) Abstract Abstract (text) PubMed Send at most: 1 item 5 items 10 items 20 items 50 items 100 items 200 items Send even when there aren't any new results Optional text in email: Save Cancel ## Create a file for external citation management software Create file Cancel ## Your RSS Feed Name of RSS Feed: Number of items displayed: 5 10 15 20 50 100 Create RSS Cancel RSS Link Copy ### Full text links [![Elsevier Science full text link](https://cdn.ncbi.nlm.nih.gov/corehtml/query/egifs/https:--linkinghub.elsevier.com-ihub-images-elsevieroa.png) Elsevier Science ](https://linkinghub.elsevier.com/retrieve/pii/S0010-4825\(26\)00348-3 "See full text options at Elsevier Science") [ Full text links ](https://pubmed.ncbi.nlm.nih.gov/42229246/) ### Actions Cite Collections Add to Collections * Create a new collection * Add to an existing collection Name your collection: Name must be less than 100 characters Choose a collection: Unable to load your collection due to an error [Please try again](https://pubmed.ncbi.nlm.nih.gov/42229246/) Add Cancel Permalink Permalink Copy Display options Display options Format Abstract PubMed PMID ### Page navigation * [ Title & authors ](https://pubmed.ncbi.nlm.nih.gov/42229246/#heading) * [ Abstract ](https://pubmed.ncbi.nlm.nih.gov/42229246/#abstract) * [ Conflict of interest statement ](https://pubmed.ncbi.nlm.nih.gov/42229246/#conflict-of-interest) * [Similar articles](https://pubmed.ncbi.nlm.nih.gov/42229246/#similar) * [ Publication types ](https://pubmed.ncbi.nlm.nih.gov/42229246/#publication-types) * [ MeSH terms ](https://pubmed.ncbi.nlm.nih.gov/42229246/#mesh-terms) * [Related information](https://pubmed.ncbi.nlm.nih.gov/42229246/#related-links) * [ LinkOut - more resources ](https://pubmed.ncbi.nlm.nih.gov/42229246/#linkout) Title & authors Abstract Conflict of interest statement Similar articles Publication types MeSH terms Related information LinkOut - more resources Review Comput Biol Med Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Comput+Biol+Med%22%5Bjour%5D&sort=date&sort_order=desc) * [ Search in NLM Catalog ](https://www.ncbi.nlm.nih.gov/nlmcatalog?term=%22Comput+Biol+Med%22%5BTitle+Abbreviation%5D) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) . 2026 Aug 15:213:111784. doi: 10.1016/j.compbiomed.2026.111784. Epub 2026 Jun 2. # On-device cough detection and respiratory disease classification enhanced by generative data augmentation [George Kontogiannis](https://pubmed.ncbi.nlm.nih.gov/?term=Kontogiannis+G&cauthor_id=42229246)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#full-view-affiliation-1 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: g.kontogiannis@ac.upatras.gr."), [Pantelis Tzamalis](https://pubmed.ncbi.nlm.nih.gov/?term=Tzamalis+P&cauthor_id=42229246)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#full-view-affiliation-2 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: tzamalis@ceid.upatras.gr."), [Anastases Giannikopoulos](https://pubmed.ncbi.nlm.nih.gov/?term=Giannikopoulos+A&cauthor_id=42229246)[ 3 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#full-view-affiliation-3 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: anastasesgiannikopoulos@gmail.com."), [Sotiris Nikoletseas](https://pubmed.ncbi.nlm.nih.gov/?term=Nikoletseas+S&cauthor_id=42229246)[ 4 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#full-view-affiliation-4 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: nikole@cti.gr.") Affiliations Expand ### Affiliations * 1 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: g.kontogiannis@ac.upatras.gr. * 2 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: tzamalis@ceid.upatras.gr. * 3 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: anastasesgiannikopoulos@gmail.com. * 4 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: nikole@cti.gr. * PMID: **42229246** * DOI: [ 10.1016/j.compbiomed.2026.111784 ](https://doi.org/10.1016/j.compbiomed.2026.111784) Free article Item in Clipboard Review # On-device cough detection and respiratory disease classification enhanced by generative data augmentation George Kontogiannis et al. Comput Biol Med. 2026. Free article Show details Display options Display options Format Abstract PubMed PMID Comput Biol Med Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Comput+Biol+Med%22%5Bjour%5D&sort=date&sort_order=desc) * [ Search in NLM Catalog ](https://www.ncbi.nlm.nih.gov/nlmcatalog?term=%22Comput+Biol+Med%22%5BTitle+Abbreviation%5D) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) . 2026 Aug 15:213:111784. doi: 10.1016/j.compbiomed.2026.111784. Epub 2026 Jun 2. ### Authors [George Kontogiannis](https://pubmed.ncbi.nlm.nih.gov/?term=Kontogiannis+G&cauthor_id=42229246)[ 1 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#short-view-affiliation-1 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: g.kontogiannis@ac.upatras.gr."), [Pantelis Tzamalis](https://pubmed.ncbi.nlm.nih.gov/?term=Tzamalis+P&cauthor_id=42229246)[ 2 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#short-view-affiliation-2 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: tzamalis@ceid.upatras.gr."), [Anastases Giannikopoulos](https://pubmed.ncbi.nlm.nih.gov/?term=Giannikopoulos+A&cauthor_id=42229246)[ 3 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#short-view-affiliation-3 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: anastasesgiannikopoulos@gmail.com."), [Sotiris Nikoletseas](https://pubmed.ncbi.nlm.nih.gov/?term=Nikoletseas+S&cauthor_id=42229246)[ 4 ](https://pubmed.ncbi.nlm.nih.gov/42229246/#short-view-affiliation-4 "Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: nikole@cti.gr.") ### Affiliations * 1 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: g.kontogiannis@ac.upatras.gr. * 2 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: tzamalis@ceid.upatras.gr. * 3 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: anastasesgiannikopoulos@gmail.com. * 4 Computer Engineering and Informatics Department, University of Patras, Patras, 26504, Greece. Electronic address: nikole@cti.gr. * PMID: **42229246** * DOI: [ 10.1016/j.compbiomed.2026.111784 ](https://doi.org/10.1016/j.compbiomed.2026.111784) Item in Clipboard Full text links Cite Display options Display options Format Abstract PubMed PMID ## Abstract **Background:** Cough sounds are accessible, non-invasive biomarkers for respiratory disease assessment and can be captured using consumer-grade smartphones. Existing approaches typically focus solely on cough detection or rely on server-based deep learning for disease classification, which limits deployability and raises privacy concerns. Small, imbalanced cough datasets further hinder model generalization. **Objective:** To develop a multilayer, smartphone-compatible AI framework for automated cough detection and respiratory disease classification, and to propose a pioneering generative augmentation strategy utilizing a suite of five Variational Autoencoder (VAE) variants and a probabilistic cough-level fusion mechanism to improve disease classification under severe data scarcity and the limitations of conventional audio augmentation techniques. **Methods:** The proposed framework consists of three AI modules: (1) A Cough Detection Module (CDM) that performs real-time cough event detection and segmentation from continuous audio using lightweight models optimized for on-device execution. (2) A Disease Analysis Module (DAM) that classifies cough events into asthma, COVID-19, or healthy classes using parallel Support Vector Machine classifiers and a probabilistic cough-level fusion strategy. (3) A Generative Augmentation Module (GAM) employing five distinct VAE architectures. This module uniquely operates across the time-frequency domain for latent feature optimization while reconstructing samples in the time-domain to ensure acoustic verifiability. **Results:** The CDM provides reliable segmentation across heterogeneous recording conditions. The DAM achieves strong discriminability between asthma, COVID-19, and healthy coughs using compact cepstral and spectral features. The multi-variant GAM framework demonstrates superior efficacy in alleviating class imbalance specifically, the cross-domain (time-frequency to time-domain) reconstruction allows for the clinical verification of synthetic biomarkers. All system components operate in real time on commodity Android hardware. **Conclusion:** This integrated framework addresses key limitations in dataset availability, model generalizability, and deployability, introducing an interpretable generative approach that demonstrates the feasibility of smartphone-based acoustic sensing as a scalable and privacy-preserving tool for respiratory health monitoring. **Keywords:** Convolutional neural networks; Cough detection; Cough sound analysis; Generative data augmentation; On-device machine learning; Respiratory health monitoring; Support vector machines; Ubiquitous computing; Variational autoencoders. Copyright © 2026 The Author(s). Published by Elsevier Ltd.. All rights reserved. [PubMed Disclaimer](https://pubmed.ncbi.nlm.nih.gov/disclaimer/) ## Conflict of interest statement Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ## Similar articles * [ An Evaluation of Pretrained Generative Models for Augmenting Small Health Data: Comparative Modeling Study. ](https://pubmed.ncbi.nlm.nih.gov/42296511/) Huet-Dastarac M, Dankar FK, Liu D, El Kababji S, Pilgram L, El Emam K.Huet-Dastarac M, et al.J Med Internet Res. 2026 Jun 15;28:e88678. doi: 10.2196/88678.J Med Internet Res. 2026.PMID: 42296511Free PMC article. * [ Nighttime Continuous Contactless Smartphone-Based Cough Monitoring for the Ward: Validation Study. ](https://pubmed.ncbi.nlm.nih.gov/36655551/) Barata F, Cleres D, Tinschert P, Iris Shih CH, Rassouli F, Boesch M, Brutsche M, Fleisch E.Barata F, et al.JMIR Form Res. 2023 Feb 20;7:e38439. doi: 10.2196/38439.JMIR Form Res. 2023.PMID: 36655551Free PMC article. * [ Generative adversarial network augmented data for improved heart sound abnormality detection. ](https://pubmed.ncbi.nlm.nih.gov/40561577/) Chakraborty S, Kochhar P, Patil S, Kotecha K, Gite S, Selvachandran G, Das S.Chakraborty S, et al.Comput Biol Med. 2025 Sep;195:110623. doi: 10.1016/j.compbiomed.2025.110623. Epub 2025 Jun 24.Comput Biol Med. 2025.PMID: 40561577 * [ Prospects of AI-Powered Bowel Sound Analytics for Diagnosis, Characterization, and Treatment Management of Inflammatory Bowel Disease. ](https://pubmed.ncbi.nlm.nih.gov/41133513/) Sood D, Riaz ZM, Mikkilineni J, Ravi NN, Chidipothu V, Yerrapragada G, Elangovan P, Shariff MN, Natarajan T, Janarthanan J, Asadimanesh N, Karuppiah SS, Gopalakrishnan K, Arunachalam SP.Sood D, et al.Med Sci (Basel). 2025 Oct 13;13(4):230. doi: 10.3390/medsci13040230.Med Sci (Basel). 2025.PMID: 41133513Free PMC article.Review. * [ Predictive Ability of Artificial Intelligence Algorithms in Pediatric Respiratory Disease Diagnosis Using Cough Sounds: A Systematic Review. ](https://pubmed.ncbi.nlm.nih.gov/40851747/) Ibrahim Abdelhalim AA, M Osman HM, Hafez Sadaka SI, Yousif Mohammed MA, Eissa E, Abdalla R, Mohamad Hassan DH.Ibrahim Abdelhalim AA, et al.Cureus. 2025 Jul 21;17(7):e88457. doi: 10.7759/cureus.88457. eCollection 2025 Jul.Cureus. 2025.PMID: 40851747Free PMC article.Review. [ See all similar articles ](https://pubmed.ncbi.nlm.nih.gov/?linkname=pubmed_pubmed&from_uid=42229246) ## Publication types * Review Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Review%22%5Bpt%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Review) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) ## MeSH terms * Autoencoder Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Autoencoder%22%5BMeSH%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Autoencoder) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Cough* / classification Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Cough%2Fclassification%22%5BMAJR%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Cough) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Cough* / diagnosis Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Cough%2Fdiagnosis%22%5BMAJR%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Cough) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Cough* / physiopathology Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Cough%2Fphysiopathology%22%5BMAJR%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Cough) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Generative Artificial Intelligence Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Generative+Artificial+Intelligence%22%5BMeSH%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Generative+Artificial+Intelligence) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Humans Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Humans%22%5BMeSH%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Humans) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Signal Processing, Computer-Assisted* Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Signal+Processing%2C+Computer-Assisted%22%5BMAJR%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Signal+Processing%2C+Computer-Assisted) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Smartphone* Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Smartphone%22%5BMAJR%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Smartphone) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) * Support Vector Machine Actions * [ Search in PubMed ](https://pubmed.ncbi.nlm.nih.gov/?term=%22Support+Vector+Machine%22%5BMeSH%5D&sort=date&sort_order=desc) * [ Search in MeSH ](https://www.ncbi.nlm.nih.gov/mesh?term=Support+Vector+Machine) * [ Add to Search ](https://pubmed.ncbi.nlm.nih.gov/42229246/) ## Related i
## Related Clinical Research

- [Post-vaccination adverse events and reduced COVID-19 booster uptake in the Netherlands](https://medichelpline.com/clinical-feed/pubmed-42603508.md) (DOI: 10.1016/j.vaccine.2026.129043)
- [Post-MI mortality by mental disorder in England: impact of care differences and the COVID-19 pande](https://medichelpline.com/clinical-feed/pubmed-41843746.md) (DOI: 10.1093/ehjqcco/qcag044)
- [Structured aerobic exercise linked to lower cancer recurrence and improved survival](https://medichelpline.com/clinical-feed/medical-news-today-0-aerobic-exercise-could-help-improve-outlook-after-cancer-treatment.md)
- [Retinal changes on OCT may predict atrial fibrillation risk years earlier](https://medichelpline.com/clinical-feed/medical-news-today-0-how-changes-in-the-eyes-may-help-spot-afib-risk-years-early.md)
- [Kennedy renews attacks on vaccines at Children’s Health Defense conference](https://medichelpline.com/clinical-feed/stat-news-1-kennedy-renews-attacks-on-vaccines-at-children-s-health-defense-conference.md)

## Navigation
- [← Back to Critical Care Feed](https://medichelpline.com/clinical-feed/critical-care.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.