Design and Implementation of a Community Driven Clinical Trial Information Management System for Precision Oncology Settings.

Introduction: Trial recruitment is a crucial factor for precision oncology, potentially improving patient outcomes and generating new scientific evidence. To identify suitable, biomarker-based trials for patients' clinicians need to screen multiple clinical trial registries which lack support for modern trial designs and offer only limited options to filter for in- and exclusion criteria. Several registries provide trial information but are limited regarding factors like timeliness, quality of information and capability for semantic, terminology enhanced searching for aspects like specific inclusion criteria.

From Data Mining of Public Sources to Clinical Decision Support in Personalized Medicine.

Personalized medicine enables precise tumor treatment for a patient's molecular genetic profile. To devise optimal targeted treatment plans for patients in a molecular tumor board, physicians must consider alterations on gene- and proteins levels but also cancer cell phenotypes. Machine learning can uncover buried patterns, extract pivotal information, and unveil corresponding insights from available data.

Challenge of Detecting Personal Deviations and Trends in Sensor Based Activity Data.

Introduction: Physical activity and health are closely linked. Therefore, monitoring movement behavior is of great interest e.g.

Assessing Quality of Life Using FHIR - How to Combine Patient Reported Outcome with Patient Generated Data for Better Compliance.

Quality of life (QoL) is affected by environmental influences and varies between patients. A combined measurement through Patient Reported Outcomes (PROs) and Patient Generated Data (PGD) may enhance the detection of QoL impairments by a longitudinal survey. Leveraging different approaches of QoL measurement techniques, the challenge is to combine data in a standardized, interoperable way.

Evaluating Online Consumer Medication Information Systems: Comparative Online Usability Study.

Background: Medication is the most common intervention in health care, and the number of online consumer information systems within the pharmaceutical sector is increasing. However, online consumer information systems can be a barrier for users, imposing information asymmetries between stakeholders.

Objective: The objective of this study was to quantify and compare the usability of an online consumer medication information system (OCMIS) against a reference implementation based on an interoperable information model for patients, physicians, and pharmacists.