Creating a computer assisted ICD coding system: Performance metric choice and use of the ICD hierarchy.

Objective: Machine learning methods hold the promise of leveraging available data and generating higher-quality data while alleviating the data collection burden on healthcare professionals. International Classification of Diseases (ICD) diagnoses data, collected globally for billing and epidemiological purposes, represents a valuable source of structured information. However, ICD coding is a challenging task.

Quantifying physician's bias to terminate resuscitation. The TERMINATOR study.

Context: Deciding on "termination of resuscitation" (TOR) is a dilemma for any physician facing cardiac arrest. Due to the lack of evidence-based criteria and scarcity of the existing guidelines, crucial arbitration to interrupt resuscitation remains at the practitioner's discretion.

Aim: Evaluate with a quantitative method the existence of a physician internal bias to terminate resuscitation.

Genesis of the αβ T-cell receptor.

The T-cell (TCR) repertoire relies on the diversity of receptors composed of two chains, called α and β, to recognize pathogens. Using results of high throughput sequencing and computational chain-pairing experiments of human TCR repertoires, we quantitively characterize the αβ generation process. We estimate the probabilities of a rescue recombination of the β chain on the second chromosome upon failure or success on the first chromosome.

High-throughput immune repertoire analysis with IGoR.

High-throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis, and interpretation of these data sets. We present IGoR (Inference and Generation Of Repertoires)-a comprehensive tool that takes B or T cell receptor sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA.

A model for the integration of conflicting exogenous and endogenous signals by dendritic cells.

Cells of the immune system are confronted with opposing pro- and anti-inflammatory signals. Dendritic cells (DC) integrate these cues to make informed decisions whether to initiate an immune response. Confronted with exogenous microbial stimuli, DC endogenously produce both anti- (IL-10) and pro-inflammatory (TNFα) cues whose joint integration controls the cell's final decision.