Workshop on PRedictive Intelligence in Medicine (PRIME)

Topics of interests include but are not limited to predictive methods dedicated to the following topics:

Modeling and predicting disease development or evolution from a limited number of observations;
Computer-aided prognostic methods (e.g., for brain diseases, prostate cancer, cervical cancer, dementia, acute disease, neurodevelopmental disorders);
Forecasting disease/cancer progression over time;
Predicting low-dimensional data (e.g., behavioral scores, clinical outcome, age, gender);
Predicting the evolution or development of high-dimensional data (e.g., shapes, graphs, images, patches, abstract features, learned features);
Predicting high-resolution data from low-resolution data;
Prediction methods using 2D, 2D+t, 3D, 3D+t, ND and ND+t data;
Predicting image modality from a different modality (e.g., data synthesis);
Predicting lesion evolution;
Predicting missing data (e.g., data imputation or data completion problems).
Predicting clinical outcome from medical data (genomic, imaging data, etc).