Exhaustively Characterizing a Patient Cohort by Prevalence of EMR Facts: a Generalized, Vendor-Agnostic Method for Quality Control and Research.

We present a method for rapidly ranking all distinct facts in an electronic medical record (EMR) system by howover-represented or under-represented they are in a patient cohort of interest relative to some larger referencepopulation of patients in the same EMR. We have implemented this method as a plugin for i2b2, the open sourcedata warehouse platform widely used in research health informatics. Our method is highly flexible in terms of whatmedical terminologies it supports and is vendor-independent thanks to leveraging the i2b2 star schema rather thanany one specific EMR.

Multiplexed highly-accurate DNA sequencing of closely-related HIV-1 variants using continuous long reads from single molecule, real-time sequencing.

Single Molecule, Real-Time (SMRT) Sequencing (Pacific Biosciences, Menlo Park, CA, USA) provides the longest continuous DNA sequencing reads currently available. However, the relatively high error rate in the raw read data requires novel analysis methods to deconvolute sequences derived from complex samples. Here, we present a workflow of novel computer algorithms able to reconstruct viral variant genomes present in mixtures with an accuracy of >QV50.

A Grid-based HIV expert system.

Objectives: This paper addresses Grid-based integration and access of distributed data from infectious disease patient databases, literature on in-vitro and in-vivo pharmaceutical data, mutation databases, clinical trials, simulations and medical expert knowledge.

Methods: Multivariate analyses combined with rule-based fuzzy logic are applied to the integrated data to provide ranking of patient-specific drugs. In addition, cellular automata-based simulations are used to predict the drug behaviour over time.

Information object definition-based unified modeling language representation of DICOM structured reporting: a case study of transcoding DICOM to XML.

Supplement 23 to DICOM (Digital Imaging and Communications for Medicine), Structured Reporting, is a specification that supports a semantically rich representation of image and waveform content, enabling experts to share image and related patient information. DICOM SR supports the representation of textual and coded data linked to images and waveforms. Nevertheless, the medical information technology community needs models that work as bridges between the DICOM relational model and open object-oriented technologies.