SIM-CIG: A Serious Game to Practice and Improve Clinical Guidelines Adoption Based on Computer-Interpretable Guidelines.

Serious games have been used to increase the accuracy and usege of clinical guidelines during routine clinical practice. This document presents the development of a serious game called SIM-GIC, a video game designed to simulate virtual patients and evaluate the decision making of players based on computer-interpretable clinical guidelines. The system is currently being developed with a content focus on antenatal care guidelines, where a number of obstetric guidelines were coded in XML files.

Latent structure in random sequences drives neural learning toward a rational bias.

People generally fail to produce random sequences by overusing alternating patterns and avoiding repeating ones-the gambler's fallacy bias. We can explain the neural basis of this bias in terms of a biologically motivated neural model that learns from errors in predicting what will happen next. Through mere exposure to random sequences over time, the model naturally develops a representation that is biased toward alternation, because of its sensitivity to some surprisingly rich statistical structure that emerges in these random sequences.

AMIA Board white paper: definition of biomedical informatics and specification of core competencies for graduate education in the discipline.

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is 'the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health.' Application areas range from bioinformatics to clinical and public health informatics and span the spectrum from the molecular to population levels of health and biomedicine.

MEDRank: using graph-based concept ranking to index biomedical texts.

Background: As the volume of biomedical text increases exponentially, automatic indexing becomes increasingly important. However, existing approaches do not distinguish central (or core) concepts from concepts that were mentioned in passing. We focus on the problem of indexing MEDLINE records, a process that is currently performed by highly trained humans at the National Library of Medicine (NLM).

Biomedical informatics: changing what physicians need to know and how they learn.

The explosive growth of biomedical complexity calls for a shift in the paradigm of medical decision making-from a focus on the power of an individual brain to the collective power of systems of brains. This shift alters professional roles and requires biomedical informatics and information technology (IT) infrastructure. The authors illustrate this future role of medical informatics with a vignette and summarize the evolving understanding of both beneficial and deleterious effects of informatics-rich environments on learning, clinical care, and research.

A process to identify military injury prevention priorities based on injury type and limited duty days.

Background: Injuries, one of the leading public health problems in an otherwise healthy military population, affect operational readiness, increase healthcare costs, and result in disabilities and fatalities. This paper describes a systematic, data-driven, injury prevention-decision making process to rank potential injury prevention targets.

Methods: Medical surveillance and safety report data on injuries for 2004 were reviewed.

What is biomedical informatics?

Biomedical informatics lacks a clear and theoretically-grounded definition. Many proposed definitions focus on data, information, and knowledge, but do not provide an adequate definition of these terms. Leveraging insights from the philosophy of information, we define informatics as the science of information, where information is data plus meaning.

Synergies and distinctions between computational disciplines in biomedical research: perspective from the Clinical andTranslational Science Award programs.

Clinical and translational research increasingly requires computation. Projects may involve multiple computationally oriented groups including information technology (IT) professionals, computer scientists, and biomedical informaticians. However, many biomedical researchers are not aware of the distinctions among these complementary groups, leading to confusion, delays, and suboptimal results.

Ontology driven integration platform for clinical and translational research.

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online.

Ontology Driven Construction of a Knowledgebase for Bayesian Decision Models Based on UMLS.

All decision models use some form of language to describe domain elements and their interactions. The terminology is often specific and even unique to the algorithm and is a choice of designers. Nevertheless the domain elements and concepts of any decision problem are almost never unique and are used and reused in many other decision problems.

Commercial clinical data warehouses: from wave of the past to the state of the art.

This article provides an overview of clinical data warehousing and its historical perspective from the early 1990s to present. It uses a survey of five Houston-area healthcare leaders to answer questions such as why commercially available solutions may be more suitable as their enterprise information systems vs. developing them in-house.

Human-centered design of a distributed knowledge management system.

Many healthcare technology projects fail due to the lack of consideration of human issues, such as workflow, organizational change, and usability, during the design and implementation stages of a project's development process. Even when human issues are considered, the consideration is typically on designing better user interfaces. We argue that human-centered computing goes beyond a better user interface: it should include considerations of users, functions and tasks that are fundamental to human-centered computing.