Key takeaways from the FCAI and Helsinki Brain & Mind webinar.
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Innovative virtual laboratories could help, for example, medicinal chemists in optimising chemical reactions. A whole new pharmaceutical ecosystem is emerging around AI in Finland.
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Generative AI could augment randomized controlled trials (RCT), making them cheaper and more accurate.
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People have to be in the loop when machine learning is adapted for medical use.
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Microscopy plus machine learning equals a quick, cheap and automated way to detect coronavirus and other emerging pathogens.
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The MAITE project studied how artificial intelligence could be used to predict the multidisciplinary service use of the elderly.
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A completely new treatment option affects the immune system in patients with advanced melanoma.
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Modeling how MRSA bacteria spread on the body can enhance treatments
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Academy–industry collaboration can be a real win-win: FCAI, health equipment manufacturer Planmeca and Tampere University Hospital developed machine learning for dental radiology.
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Artificial data can be generated in large amounts and does not contain patient information.
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The Future Clinical Trials project led by Bayer utilises artificial intelligence (AI) to improve the safety and efficiency of clinical drug research.
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The developed tool has broad applications in understanding the function of immune system in infections, autoimmune disorders, and cancer.
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Heli Julkunen developed a machine learning method that predicts how different drug combinations kill cancer cells, and now she helps advance preventive healthcare as a data scientist.
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AI-Mind is a 5-year project funded by Horizon 2020, with the goal of facilitating a paradigm shift in clinical practice of mild cognitive impairment. A team of Aalto University and HUS Helsinki University Hospital researchers are involved in the project.
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An international collaboration project to develop and implement novel genome-based disease prediction tools has received over 10 million euros from the EU Horizon 2020 Research and Innovation program.
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Researchers at FCAI have developed a machine learning-based method that can produce research data synthetically. The application is based on a method that allows academics and companies to share data with each other without compromising the privacy of the individuals involved in the study.
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A machine learning model can help us treat cancer more effectively
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DataLit is an interdisciplinary collaboration between social sciences, law and AI methods aims at understandable and trustworthy practices for utilising Finnish health, social, and welfare data.
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Researchers at FCAI, Planmeca and Tampere University Hospital have developed an artificial intelligence method that helps, for example, with the placement of teeth implants.
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An international research team recently conducted the first population-based and genome-wide bacterial transcriptomics study, combined with dense longitudinal genome data and virulome characterization using an animal model.
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