Empirical advances with text mining of electronic health records.

BACKGROUND: Korian is a private group specializing in medical accommodations for elderly and dependent people. A professional data warehouse (DWH) established in 2010 hosts all of the residents' data. Inside this information system (IS), clinical narratives (CNs) were used only by medical staff as a residents' care linking tool. The objective of this study was to show that, through qualitative and quantitative textual analysis of a relatively small physiotherapy and well-defined CN sample, it was possible to build a physiotherapy corpus and, through this process, generate a new body of knowledge by adding relevant information to describe the residents' care and lives. METHODS: Meaningful words were extracted through Standard Query Language (SQL) with the LIKE function and wildcards to perform pattern matching, followed by text mining and a word cloud using R® packages. Another step involved principal components and multiple correspondence analyses, plus clustering on the same residents' sample as well as on other health data using a health model measuring the residents' care level needs. RESULTS: By combining these techniques, physiotherapy treatments could be characterized by a list of constructed keywords, and the residents' health characteristics were built. Feeding defects or health outlier groups could be detected, physiotherapy residents' data and their health data were matched, and differences in health situations showed qualitative and quantitative differences in physiotherapy narratives. CONCLUSIONS: This textual experiment using a textual process in two stages showed that text mining and data mining techniques provide convenient tools to improve residents' health and quality of care by adding new, simple, useable data to the electronic health record (EHR). When used with a normalized physiotherapy problem list, text mining through information extraction (IE), named entity recognition (NER) and data mining (DM) can provide a real advantage to describe health care, adding new medical material and helping to integrate the EHR system into the health staff work environment.

Public Health and Epidemiology Informatics.

OBJECTIVES: The aim of this manuscript is to provide a brief overview of the scientific challenges that should be addressed in order to unlock the full potential of using data from a general point of view, as well as to present some ideas that could help answer specific needs for data understanding in the field of health sciences and epidemiology. METHODS: A survey of uses and challenges of big data analyses for medicine and public health was conducted. The first part of the paper focuses on big data techniques, algorithms, and statistical approaches to identify patterns in data. The second part describes some cutting-edge applications of analyses and predictive modeling in public health. RESULTS: In recent years, we witnessed a revolution regarding the nature, collection, and availability of data in general. This was especially striking in the health sector and particularly in the field of epidemiology. Data derives from a large variety of sources, e.g. clinical settings, billing claims, care scheduling, drug usage, web based search queries, and Tweets. CONCLUSION: The exploitation of the information (data mining, artificial intelligence) relevant to these data has become one of the most promising as well challenging tasks from societal and scientific viewpoints in order to leverage the information available and making public health more efficient.

Salting-in effect in organic dispersions of poly(3-hexyl thiophene)-carbon-nanotubes.

Addition of small concentrations of different inorganic salts to THF solutions of poly(3-hexyl thiophene), which contain non-dispersed powder of Multi-Walled Carbon Nanotubes (MWNTs), was found to "salt-in" the precipitated tubes leading to the formation of a stable dispersion of the MWNTs. This effect seems to result from a salt-induced conformational change of polymer chains adsorbed onto the CNTs, resulting in the onset of (entropic) steric repulsion among polymer-decorated chains.

Modelling transmission of bovine tuberculosis in red deer and wild boar in Normandy, France.

In early 2001, Mycobacterium bovis infection was confirmed in red deer (RD) (Cervus elaphus) shot in Normandy region, France. An epidemiological survey conducted during the following hunting season in two connected forests confirmed the occurrence of the disease in both free-ranging RD and wild boar (WB) (Sus scrofa). This was the first detected bovine tuberculosis outbreak in wildlife in France. We present a simple deterministic age-structured model of the within- and between-species M. bovis transmission in RD and WB populations that distinguishes direct transmission (horizontal and pseudo-vertical) and indirect transmission through contaminated offal left behind by hunters. Results issued from the epidemiological surveys conducted in Normandy forests were used to estimate transmission parameters. Because data for RD and WB populations were not available, population sizes at demographic equilibrium were estimated and used to run the model. We qualitatively tested different control measure scenarios with our model, considering different mortality rates and offal harvesting, to determine which ones affect the success of infection control. The most realistic control scenario would combine the total depopulation of RD and good compliance with offal harvesting, because the model suggests that infected offal left by hunters represents the main transmission source of M. bovis in the field.

Asymptotic distribution of stage-grouped population models.

Matrix models are often used to predict the dynamics of size-structured or age-structured populations. The asymptotic behaviour of such models is defined by their malthusian growth rate lambda, and by their stationary distribution w that gives the asymptotic proportion of individuals in each stage. As the coefficients of the transition matrix are estimated from a sample of observations, lambda and w can be considered as random variables whose law depends on the distribution of the observations. The goal of this study is to specify the asymptotic law of lambda and w when using the maximum likelihood estimators of the coefficients of the transition matrix. We prove that lambda and w are asymptotically normal, and the expressions of the asymptotic variance of lambda and of the asymptotic covariance matrix of w are given. The convergence speed of lambda and w towards their asymptotic law is studied using simulations. The results are applied to a real case study that consists of a Usher model for a tropical rain forest in French Guiana. They permit to assess the number of trees to measure to get a given precision on the estimated asymptotic diameter distribution, which is an important information on tropical forest management.

Determination of the differentially expressed genes in microarray experiments using local FDR.

BACKGROUND: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile. RESULTS: Using process intensity estimation methods, we define and give estimates of the local FDR, which may be considered as the probability for a gene to be a false positive. After a global assessment rule controlling the false positive error, the local FDR is a valuable guideline for deciding wether a gene is differentially expressed. The interest of the method is illustrated on three well known data sets. A R routine for computing local FDR estimates from p-values is available at http://www.inapg.fr/ens_rech/mathinfo/recherche/mathematique/outil.html. CONCLUSIONS: The local FDR associated with each gene measures the probability that it is a false positive. It gives the opportunity to compute the FDR of any given group of clones (of the same gene) or genes pertaining to the same regulation network or the same chromosomic region.

Yield stability in Coffea canephora from diallel mating designs monitored for 14 years.

The genetic parameters of several agronomic traits were estimated in Coffea canephora in a triangular diallel with six parents and in a partial diallel with 18 parents. The yield data came from harvests obtained over 14 years divided into an initial 6-year cycle, a second cycle of 5 years after cutting back and a third cycle of 3 years after topping. Risk incidence was also observed over several years. The general combining abilities (GCA) were the principal sources of variation for the various traits considered. Parents derived from the Yangambi selections (Democratic Republic of Congo) proved to be best for yields in the three cropping cycles. The rank correlations between the GCA of the various traits indicated that first-cycle production was still not enough to predict the GCA for yield over 14 years. Susceptibility to leaf anthracnose and to drought could lead to modifications in successive classifications, with a more significant impact on production during the first cycle. The differences in susceptibility to Coffee Berry Borers had an impact on yield, which increased in line with coffee tree age. There was a rather good relation between inherent values and values in parent combinations and it was thus possible to choose parents on their own performance.

Ascent rate, age, maximal oxygen uptake, adiposity, and circulating venous bubbles after diving.

Decompression sickness in diving is recognized as a multifactorial phenomenon, depending on several factors, such as decompression rate and individual susceptibility. The Doppler ultrasonic detection of circulating venous bubbles after diving is considered a useful index for the safety of decompression because of the relationship between bubbles and decompression sickness risk. The aim of this study was to assess the effects of ascent rate, age, maximal oxygen uptake (VO(2 max)), and percent body fat on the production of bubbles after diving. Fifty male recreational divers performed two dives at 35 m during 25 min and then ascended in one case at 9 m/min and in the other case at 17 m/min. They performed the same decompression stops in the two cases. Twenty-eight divers were Doppler monitored at 10-min intervals, until 60 min after surfacing, and the data were analyzed by Wilcoxon signed-rank test to compare the effect of ascent rate on the kinetics of bubbles. Twenty-two divers were monitored 60 min after surfacing. The effect on bubble production 60 min after surfacing of the four variables was studied in 47 divers. The data were analyzed by multinomial log-linear model. The analysis showed that the 17 m/min ascent produced more elevated grades of bubbles than the 9 m/min ascent (P < 0.05), except at the 40-min interval, and showed relationships between grades of bubbles and ascent rate and age and interaction terms between VO(2 max) and age, as well as VO(2 max) and percent body fat. Younger, slimmer, or aerobically fitter divers produced fewer bubbles compared with older, fatter, or poorly physically fit divers. These findings and the conclusions of previous studies performed on animals and humans led us to support that ascent rate, age, aerobic fitness, and adiposity are factors of susceptibility for bubble formation after diving.