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Medical visualization tools have traditionally been constrained to tethered imaging workstations or proprietary client viewers, typically part of hospital radiology systems. To improve accessibility to real-time, remote, interactive, stereoscopic visualization and to enable collaboration among multiple viewing locations, we developed an open source approach requiring only a standard web browser with no added client-side software.

Social networks have been used in the study of outbreaks of infectious diseases, including in small group settings such as individual hospitals. Collecting the data needed to create such networks, however, can be time consuming, costly, and error prone. We sought to create a social network of hospital inpatients using electronic medical record (EMR) data already collected for other purposes, for use in simulating outbreaks of nosocomial infections.

To summarize the literature describing computer-based interventions aimed at improving bidirectional communication between clinical and public health.

Self-monitoring of physical activity (PA) and diet are key components of behavioral weight loss programs. The purpose of this study was to assess the relationship between diet (mobile app, website, or paper journal) and PA (mobile app vs no mobile app) self-monitoring and dietary and PA behaviors.

The clinical element model (CEM) is an information model designed for representing clinical information in electronic health records (EHR) systems across organizations. The current representation of CEMs does not support formal semantic definitions and therefore it is not possible to perform reasoning and consistency checking on derived models. This paper introduces our efforts to represent the CEM specification using the Web Ontology Language (OWL). The CEM-OWL representation connects the CEM [...]

Privacy-preserving data publishing addresses the problem of disclosing sensitive data when mining for useful information. Among existing privacy models, ε-differential privacy provides one of the strongest privacy guarantees and makes no assumptions about an adversary's background knowledge. All existing solutions that ensure ε-differential privacy handle the problem of disclosing relational and set-valued data in a privacy-preserving manner separately. In this paper, we propose an algorithm that considers both relational and [...]

The aim of this research was to automate the search of publications concerning adverse drug reactions (ADR) by defining the queries used to search MEDLINE and by determining the required threshold for the number of extracted publications to confirm the drug/event association in the literature.

Medication  safety requires that each drug be monitored throughout its market life as early detection of adverse drug reactions (ADRs) can lead to alerts that prevent patient harm. Recently, electronic medical records (EMRs) have emerged as a valuable resource for pharmacovigilance. This study examines the use of retrospective medication orders and inpatient laboratory results documented in the EMR to identify ADRs.

The increasing availability of clinical data from electronic medical records (EMRs) has created opportunities for secondary uses of health information. When used in machine learning classification, many data features must first be transformed by discretization.