This year's mission:
A project of AI for Healthcare
In 2021 the team of about 20 students, supported by FBK researchers and other tutors of international level will delve into a project of AI for Healthcare and Precision Medicine, in collaboration with FBK Digital Health and Wellbeing research centre and the DSH and eHealthLab research units.
Data Science and Artificial Intelligence are pervasively spreading into the Life Science domain, opening the doors to a near future where algorithms are considered proper medical devices certified by institutional agencies. In this scenario, a growing number of prognostic tools are developed and tested to support physicians in their daily clinical tasks, with a particular interest in predictive systems raising red flags when signals of worsening conditions are detected. In particular, the WebValley 2021 Team will be involved in the development, implementation, and validation of AI algorithms aimed at detecting the early onset of comorbidities in diabetic patients starting from their healthcare trajectories collected as personal Electronic Health Record. In details, the Team will delve into the computational tools needed to analyze and make sense of the data, i.e. data science and machine/deep learning solutions and high-quality software collaboratively produced by the participants, after having been provided with the essential domain knowledge and effective operative, communicative, and organisational tools.
Throughout the project evolution, the students will develop technical skills in data science, acquiring working experience on machine learning and life science methodologies, including reproducibility, interpretability and privacy for AI solutions in health, and the basics of deploying models on the cloud.
Next Generation Computational Biologists
What are the desiderata needed to profile the top-notch data scientist for computational biology of the next generation? What blending of skills constitutes an essential portfolio?
WebValley 2020 tried to answer these questions, providing essential domain knowledge and effective operative tools. In details, the WebValley Team delved into omics biology, implementing machine and deep learning solutions through high-quality software collaboratively produced. Using the bleeding edge case study of unsupervised machine learning on single-cell sequencing, we aimed at forging a working prototype of the high-quality toolbox required to make a young researcher attractive to excellence biotech lab worldwide, thus providing a valuable training package.
AI for predictive medicine
The scientific theme of WebValley 2019 was the application of Deep Learning methods to the integration of biomedical imaging, omics markers and clinical data for predictive health. In particular, the project will aim at widening the use of machine learning on massive health data out of the hospital context, e.g. for surveillance and point of care of disease.
In collaboration with medical experts, the WebValley team will study how to combine phenotype data, extensive clinical exams and biomarkers from portable imaging devices. Challenges will span from biomedical to machine learning and techs aspects, from reproducibility and interpretability of AI in health to practical skills in data science, including how to run privacy-aware deep learning in cloud.