📣 It's another PREreview product weeknote!
To learn more about:
✶ Our amazing partnership with Preprints.org, and
✶ Our continued localization and translation work,
🔗 Check out our weeknote here: https://content.prereview.org/prereview-platform-news-11-april-2025/
🌟 Exciting News! ✨
We’re thrilled to welcome Preprints.org to the growing list of preprint servers where authors can request feedback from the PREreview community with just one simple click!
This integration is made possible via @coar_repositories COAR Notify. 🙏
🔗Ready to get started? https://www.preprints.org/user/home/submissions
#openscience #preprints #preprintreview #prereview #openpeerreview
📣 Want to be part of a collaborative, open, peer review process? Join @prereview and @JMIRPub this week for our next Live Review!
⭐ When: April 10 @ 16:00 UTC
🔗 DOI here: https://doi.org/10.48550/arXiv.2503.04802
🔗 Register here: http://bit.ly/livereview-april
#prereview #openpeerreview #openscience #livereview
#reviewtogether
Background:Speech patterns have emerged as potential diagnostic markers for conditions with varying etiologies. Machine learning (ML) presents an opportunity to harness these patterns for accurate disease diagnosis. Objective: This review synthesized findings from studies exploring ML's capability in leveraging speech for the diagnosis of neurological, laryngeal and mental disorders. Methods: A systematic examination of 564 articles was conducted with 91 articles included in the study, which encompassed a wide spectrum of conditions, ranging from voice pathologies to mental and neurological disorders. Methods for speech classifications were assessed based on the relevant studies and scored between 0-10 based on the reported diagnostic accuracy of their ML models. Results: High diagnostic accuracies were consistently observed for laryngeal disorders, dysarthria, and changes related to speech in Parkinsons disease. These findings indicate the robust potential of speech as a diagnostic tool. Disorders like depression, schizophrenia, mild cognitive impairment and Alzheimers dementia also demonstrated high accuracies, albeit with some variability across studies. Meanwhile, disorders like OCD and autism highlighted the need for more extensive research to ascertain the relationship between speech patterns and the respective conditions. Conclusion: ML models utilizing speech patterns demonstrate promising potential in diagnosing a range of mental, laryngeal, and neurological disorders. However, the efficacy varies across conditions, and further research is needed. The integration of these models into clinical practice could potentially revolutionize the evaluation and diagnosis of a number of different medical conditions.
⭐ Interested in building community? Want to contribute to a collective, open, peer review process?
Join @prereview and @JMIRPub on April 10 @16:00 UTC for our next Live Review, where we will be reviewing: "The order in speech disorder: a scoping review of state of the art machine learning methods for clinical speech classification."
🔗 DOI here: https://doi.org/10.48550/arXiv.2503.04802
🔗 Register here: http://bit.ly/livereview-april
#prereview #openpeerreview #openscience #livereview #reviewtogether
Background:Speech patterns have emerged as potential diagnostic markers for conditions with varying etiologies. Machine learning (ML) presents an opportunity to harness these patterns for accurate disease diagnosis. Objective: This review synthesized findings from studies exploring ML's capability in leveraging speech for the diagnosis of neurological, laryngeal and mental disorders. Methods: A systematic examination of 564 articles was conducted with 91 articles included in the study, which encompassed a wide spectrum of conditions, ranging from voice pathologies to mental and neurological disorders. Methods for speech classifications were assessed based on the relevant studies and scored between 0-10 based on the reported diagnostic accuracy of their ML models. Results: High diagnostic accuracies were consistently observed for laryngeal disorders, dysarthria, and changes related to speech in Parkinsons disease. These findings indicate the robust potential of speech as a diagnostic tool. Disorders like depression, schizophrenia, mild cognitive impairment and Alzheimers dementia also demonstrated high accuracies, albeit with some variability across studies. Meanwhile, disorders like OCD and autism highlighted the need for more extensive research to ascertain the relationship between speech patterns and the respective conditions. Conclusion: ML models utilizing speech patterns demonstrate promising potential in diagnosing a range of mental, laryngeal, and neurological disorders. However, the efficacy varies across conditions, and further research is needed. The integration of these models into clinical practice could potentially revolutionize the evaluation and diagnosis of a number of different medical conditions.
🗒️ Our weekly product update is out! Learn more about our platform updates and community design sprints here: https://content.prereview.org/prereview-platform-news-14-march-2025/
7/7 If you're interested in seeing this process in real time and learning more, we encourage you to register for:
🔗our Live Review webinar on Wednesday, March 19: https://bit.ly/LiveReview-webinar25
🔗our Live Review on Friday, March 21st @16:00 UTC: https://bit.ly/review-together-march21
And make sure to follow us so you can continue [Learning about Live Reviews]! 📓💭
Join JMIR Publications and PREreview for a discussion on Live Reviews—an innovative, community-driven approach to peer review. This webinar will explore how Live Reviews bring authors, reviewers, and facilitators together in real time to improve the transparency, rigor, and inclusivity of the review process.
I've been privileged to be able to bring together a group of key opinion leaders in the fields of #ComputationalMassSpectrometry, #Proteomics, and #Metabolomics to discuss future data formats for storing data from #MassSpectrometry experiments. After a lot of deliberation (and a lot of help from Tim Van Den Bossche drafting) we are proud to announce the initial Whitepaper describing goals for the next generation format. This is available on Zenodo at https://lnkd.in/edhWJ7d4
Now it's your turn to get involved. We are looking for comment, reviews and thoughts on what we've put together so far. We are looking to use #PreReview as a platform to do this. So, if you work with mass spec data, or know anyone who does, please read the whitepaper, comment on it at
https://lnkd.in/efNqu7Z2 and share with your mass spec loving friends. We are hoping to have a first round of discussions based on feedback at the HUPO Proteomics Standards Initiative meeting at the end of March, and publish an updated Whitepaper for more comments from there.
Welcome to 2025 and the first PREreview newsletter of the year! 🥳 Inside, we’ve got some exciting updates, engaging opportunities, and even more events that we’d like to share: https://content.prereview.org/prereview-january-2025-newsletter/
It’s time for the PREreview Product weeknote! 📝
We've been improving our review publication workflow, and we have some exciting projects coming soon, which you can learn more about here: https://content.prereview.org/prereview-platform-news-17-january-2025/
#prereview #openscholarship #openresearch #peerreview #platformupdates
Today, we published our ☀️2024 Annual Report🌕!!
To learn more about our achievements from last year, as well as our renewed commitment to work in community to shape a more equitable, open, and transparent scholarly evaluation landscape, check out our blog here: https://content.prereview.org/2024-a-year-of-expansion-and-introspection, and read our full report here: https://zenodo.org/records/14675020.
We thank everyone in our community, our collaborators, and funders! We could not do this work without you!
Today we published our 2024 Annual Report, sharing our achievements from last year and renewing our commitment to work in collaboration with you to shape an equitable, open, and transparent scholarly evaluation landscape. We built our annual strategic approach to advance our mission around three key objectives: Strengthen PREreview's financial
PREreview
Dr. Samuel Wein