Background: Physicians and health policy makers are required to make predictions during
their decision making in various medical problems. Many advances have been made in …

Healthcare professionals have long envisioned using the enormous processing powers of
computers to discover new facts and medical knowledge locked inside electronic health …

Background Conventional risk prediction techniques may not be the most suitable approach
for personalized prediction for individual patients. Therefore, individualized predictive …

Background As healthcare-related data proliferate, there is need to annotate them expertly
for the purposes of personalized medicine. Crowdworking is an alternative to expensive …

Evidence-based medicine often involves the identification of patients with similar conditions,
which are often captured in ICD (International Classification of Diseases (World Health …

Personalized modeling usually trains a predictive model for a new point using only
observations similar to the new point. However, existing methodologies have limitations that …

Medical research can greatly benefit from advances in data mining. We propose a mining
approach for cohort analysis in a longitudinal population-based epidemiological study, and …

Electronic Health Records (EHRs) provide the possibilities to improve patient care and
promote clinical research. In recent years, there has been an exponential increase in the …

Medical diagnostics are based on epidemiological findings about reliable predictive factors.
In this work, we investigate how sequences of historical recordings of routinely measured …

In healthcare, a tsunami of medical data has emerged, including electronic health records,
images, literature, etc. These data are heterogeneous and noisy, which renders clinical …