Kantify will host a webinar on AI and cardiology in practice
The World Health Organization (WHO) estimates that around 32% of all deaths worldwide are caused by cardiovascular diseases (CVD), where 17.9 million people die each year. Identifying those people at highest risk of CVDs and ensuring they receive appropriate and timely treatment can prevent premature deaths. Luckily, artificial intelligence and machine learning can help prevent premature deaths by detecting cardiac pathologies and predicting an occurrence of a cardiac event.
**Join us on our second webinar hosted by Kantify’s experts, where we'll talk about where and how artificial intelligence can be used to detect and predict various cardiac pathologies. **
Content: Throughout the webinar, Kantify will share its experience in developing AI applications in cardiology, where attendees will learn:
- the concepts of artificial intelligence and machine learning,
- common data formats and AI techniques used in cardiology,
- where and how AI can enhance cardiology diagnostics,
- how to use AI in their work and what are the benefits that AI could bring.
Meet us for a virtual chat on the 9th of December at 12pm CET time!
Audience: the webinar is intended for pharma, biotech, medtech companies, and research organizations looking to practically understand how to use AI in their work and what benefits AI can bring. After the completion of the webinar Kantify will provide certificates of participation to the attendees.
Registration: The webinar is free but registration is mandatory with a limited number of places, so make sure you reserve your spot today! Click here to register for the webinar.
About Kantify: Kantify is an Artificial Intelligence (AI) technology company specialized in life sciences. Our core expertise is Machine Learning: a branch of Artificial Intelligence that uses data to train mathematical algorithms to perform complex tasks, such as predictions, pattern recognition, anomaly detection, and many more.
Our journey in life sciences started in early 2018, where we had a world-first in real-time prediction of Atrial Fibrillation episodes based solely on a patient's signal data. Ever since then, we have been developing AI to help solve complex human-health problems related to early drug discovery, detection and prediction of human pathologies, automating and empowering laboratory analysis, and many more.