Article from Austria Presse Agentur (APA) about AI in healthcare

A multi-faceted article describing various applications of AI in healthcare has been published by Austria Presse Agentur (DE).

encevis team members contributed by discussing our solution for automatised data analysis of large EEG datasets for fast and reliable epilepsy diagnosis in adult and pediatric population.

See here:

Our “encevis4kids” project in GesundheitWirtschaft.at

A new article (DE) about our project was published on GesundheitWirtschaft.at platform.

The publication describes our new projects dedicated to the development of AI-powered algorithms for automatic detection of epileptic spikes and seizures in EEG data recorded from pediatric patients.

Follow the link to read more: https://www.gesundheitswirtschaft.at/blog/eine-schnellstmoegliche-epilepsiediagnose-bietet-betroffenen-kindern-eine-chance-fuer-bestmoegliche-entwicklung/

Interview in “Die Presse” about our stroke project

Künstliche Intelligenz soll das Gehirn retten helfen” is the title of the article published on 9.December.2023 in Die Presse newspaper.
Hannes Perko from the encevis team, in interview with Gerald Stampfel from Die Presse, talked about our stroke-focused project, and how efficiency of patient triage can be improved with AI analysis of EEG data.
Digital version of the article can be also found on the website of Die Presse (DE).

encevis strives towards the next milestone!

Within the framework of newly funded FFG-project, encevis team is working on developing AI-powered algorithms specifically for children and adolescents with suspected or confirmed epilepsy.
Building on our existing expertise with automatic review and analysis of (long-term) EEG data recorded from adults, we are now striving towards extending our application by training and validating algorithms on the brain activity data of young patients.

Both healthy and pathological brain activity might look very different depending on age. The anatomical and functional architecture of the brain undergoes tremendous changes across the development. Some epileptic syndroms occur only (e.g. ESES = electrical status epilepticus in sleep) or predominantly (e.g. absence seizures) in young age. Moreover, epileptic discharges can negatively impact the maturation process, or even cause regressions. When training algorithms to automatically detect epileptic activity in EEG data of children, all these factors must be considered.

encevis team is very much excited to embrace this challange!
To learn more, read the article describing our new project on the AIT’s website in DE or EN.

Interview in Gesundheitswirtschaft.at about our project on early diagnosis of dementia

In a recent article in Gesundheitswirtschaft.at, Hannes Perko talks about our dementia project called BrainCheck. In BrainCheck, a multidisciplinary team of scientists and enginners from AIT Health & Bioresources Center, in collaboration with industry parterns, develops a solution, which can be used to search for signs of dementia in the brain activity. Read the article to learn more about this neurological degenerative disease, and how AI-based analysis of EEG data can help with its early diagnosis.
See here: https://www.gesundheitswirtschaft.at/blog/mit-algorithmen-demenz-erkennen-ehe-sie-sich-zeigt/ (DE)

New publication based on the use of encevis spike detection

A brand new study by shows that the AI-driven encevis spike detection algorithm reaches a sensitivity of 92% with an average per patient FPR of 5.6/hour. This makes it possible to characterize epilepsy patients based on their temporal patterns of interictal epileptiform discharges, circadian rhythms, deep sleep and seizures. Precious insights can be won thanks to encevis automated analysis.  The full paper is available here until July 10th.

New publication shows the high sensitivity of encevis spike detection

Our newest spike detection is described in this publication together with a study performed with independent data from the Danish Epilepsy Centre in Dianalund. An artificial intelligence-based EEG algorithm for detection of epileptiform EEG discharges: Validation against the diagnostic gold standard. With a sensitivity of 89%, the new encevis spike detection performs better than any previously published algorithm. If you want to try it on your own data, just contact us!