Victoria Blanes-Vidal

Victoria Blanes-Vidal is a Professor at The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, specializing in Applied AI and Data Science. Her research bridges artificial intelligence with medical applications, particularly in cancer screening, diabetes complications, and environmental epidemiology. With over 80 research outputs and significant research metrics (3320 citations, h-index 30), she maintains an active presence in both academic and clinical research domains.

Her research interests span Data Science, Biostatistics, Epidemiology, Machine Learning, and AI applications in healthcare, with specific focus on Cardiovascular diseases, Diabetes, Cancer screening (prostate, breast, colorectal, cervical), Emotions recognition, Liver diseases, Preeclampsia, and Respiratory health. She investigates Screening methodologies, Early detection techniques, and Prediction models within Medical Informatics and Mobile Health frameworks, extending to Environmental Epidemiology and Health Risk Assessment.

Analysis of her recent publications reveals a strong trend toward applying AI in medical diagnostics, particularly in gastrointestinal cancer screening using capsule endoscopy, cervical cancer detection through colposcopic image analysis, and non-invasive diabetes complication detection through facial analysis and eye tracking. Her work consistently focuses on developing explainable AI models that can be integrated into clinical pathways while maintaining diagnostic accuracy.

Professor Blanes-Vidal serves as a peer reviewer for prestigious journals including PLOS ONE and Scientific Reports, demonstrating her standing in the academic community. She has been involved in editorial work since 2022 and maintains membership in research networks such as the Polytechnical University of Valencia since 2008.

Her teaching portfolio includes courses in Statistical Data Analysis, Data Science, and Datamining, reflecting her commitment to educating the next generation of data scientists. She has supervised research on topics including "Public perception of environmental quality: Improving quantitative analysis of statistical data in epidemiological studies." Her work has received significant media attention, with 11 press/media mentions including coverage in Danish media about AI applications for detecting life-threatening liver disease.