Applied Artificial Intelligence

Artificial Intelligence solutions have the potential to transform healthcare as we now it today. By 2030 the vision of us all manufacturing our own medicines with advanced printing methods in our home with the optimal dosage is not far fetched. Artificial Intelligence solutions can be found in most industries today, but healthcare and life sciences have yet to adopt such technologies en masse. Applied Artificial Intelligence involves solutions of real-life problems with technologies such as machine learning, neural networks, genetic algorithms etc. The AI field itself is interdisciplinary and based on computer science, mathematics, psychology, linguistics, philosophy and neuroscience. Life Science and healthcare

in particular is centered around matters such as patient safety, evidence-based decision making, regulatory compliance, legal considerations, reimbursement, sensitive data, identify theft etc. In navigating this field the mathematical and technological comprehension of AI tools does not suffice. How can healtchare be transformed and what sacrifices may be made on the way? This presentation gives a brief introduction to Artificial Intelligence and ventures into the complexities of the healthcare and other parts of the Life Science.

The second part of the presentation is a case study of an authentic case Lytics worked with; detecting drowsiness in ECG data. In this case study we will discuss machine learning for time series data and describe the progress and events during the project. We will dwell on topics like feature extraction and also talk a bit about the nature of ECG signals.

This presentation requires no previous knowledge or experience of Applied Artificial Intelligence or Life Science. Its intended audiences are software engineers, clinicians or the general public interested in the combination of the two and what can be achieved with such solutions.

Mattias Paulsson is Partner & CEO of Lytics (formerly Experlytics) in Malmö. He has served in international positions

in the medical device and ICT industries and spends the majority of his time at Lytics in crafting applications and solutions for their customers and business partners. He holds an M.Sc. in Business Administration from School of Economics and Management at Lund University and a B.Sc. in Sociology from Linnaeus University.

Jonas Aron Öman is a data scientist and analyst at Lytics where he develops machine learning solutions for problems in medicine and healthcare. Jonas has previously worked at Expertmaker and also teaches in Artificial Intelligence at Lund University. He holds an M.Sc. in Engineering Physics from Lund University where he specialized in statistical modeling.

Mikael Andreen is a data scientist and analyst at Lytics which means he is responsible for applying algorithms on data to gain insights. Mikael has a background in programming and signal processing. He has previously worked within the mobile phone industry in Malmö and Lund at companies such as Ericsson, Sony and Blackberry. He holds an M.Sc in Electronics from Lund University, majoring in signal processing and digital communications.

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