{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"","title":"Machine learning for improved image analysis in research and development","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/651410d2ea278b00116fb811/1700068830284-ffa056ad819c5c01116e958cefab0e1a.jpeg?height=200","description":"

In this interview, Philip Kainz, CEO of KML Vision, talks about the development of analysis tools for scientific research.

https://www.kmlvision.com/about-us/#team


He describes how machine learning algorithms efficiently support scientists in pattern recognition. He shares his journey from computer scientist to co-founder of KML Vision, a company dedicated to bringing ML solutions to those without the technical knowledge or resources.


He talks about the differences between working with academics and the pharmaceutical industry.


Finally, he explains the advantages of KI technology over traditional image analysis methods. How these new, future-oriented tools can be successfully used for both prospective and retrospective data analysis.


You can also watch the interview on Youtube:

https://www.youtube.com/live/1BjC-wffe4Q?si=R-JRVe5oalj2orFT



#machinelearning #research #academia #industry #artificialintelligence #cellima #imageanalysis #algortihms

https://www.cellima.com

","author_name":"Stefan Prechtl"}