Janne Kauttonen

Haaga-Helia University of Applied Sciences

Papers

Total Citations

H-Index

About

Janne Kauttonen is a researcher whose work sits at the intersection of artificial intelligence, healthcare, and education, with a particular focus on how emerging AI technologies are adopted, trusted, and integrated into real-world settings. His most influential contribution, a quantitative survey analysis examining trust and acceptance challenges in AI adoption within healthcare, has garnered 53 citations since its 2025 publication, underscoring the timeliness and relevance of his investigations into consumer and patient attitudes toward AI-driven medical applications. This work addresses a critical barrier to AI implementation: the human dimension of trust, offering actionable insights for policymakers, clinicians, and technologists alike. Beyond adoption dynamics, Kauttonen has also made strides in the emerging field of Emotion AI, co-editing a notable editorial exploring next-generation applications in both healthcare and education. This work bridges traditional machine learning approaches — including Support Vector Machines and Random Forest methods — with advanced deep learning architectures such as LSTMs and CNNs, championing multimodal systems as the frontier of affective computing. Kauttonen's research reflects a compelling commitment to ensuring that sophisticated AI systems are not only technically robust but genuinely trusted and embraced by the people they are designed to serve.