Personalized modeling for drug concentration prediction using Support Vector Machine

Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

A new hybrid summarizer based on vector Space model, statistical physics and linguistics

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.

On the Segregation of Genetically Modified, Conventional, and Organic Products in European Agriculture: A Multi-market Equilibrium Analysis, October 2005

Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU) this regulation envisions the “co-existence” of GM food with conventional and quality-enhanced products, mandates the labelling and traceability of GM products, and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large-scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non-GM products, but the producers of quality-enhanced products actually benefit.

Unstable equilibrium: young adult women in family and career formation in Southern Europe

The paper examines the relationship between family formation (i.e., living with a partner and having children) and women’s occupational career in southern Europe (i.e., Greece, Italy, Portugal and Spain). The relationship is explored by analysing the impact that different family structures and male [nvolvement in caring activities have on women’s early occupational trajectories (i.e., remaining in the same occupational status, experiencing downward or upward mobility, or withdrawing from paid work). This research shows that male involvement in caring activities does not really push women ahead in their career, but the absolute lack of male support seems to negatively affect women’s permanence in paid work. These results apply to all southern European countries except Portugal, where the absolute absence of the partners’ support in caring activities does not seem to alter women’s determination to remain in paid work. The methodology applied consists of the estimation of multinomial logit regression models and the analysis is based on eight waves (1994-2001) of the European Community Household Panel (ECHP).

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

Hyperactivity and attention problems in a Swiss sample of school-aged children: effects of school achievement, child gender, and informants.

OBJECTIVE: The sensitivity and tolerance regarding ADHD symptoms obviously differ from one culture to another and according to the informants (parents, teachers, or children). This stimulates the comparison of data across informants and countries. METHOD: Parents and teachers of more than 1,000 school-aged Swiss children (5 to 17 years old) fill in Conners's questionnaires on ADHD. Children who are older than 10 years old also fill in a self-report questionnaire. Results are compared to data from a North American sample. RESULTS: Swiss parents and teachers tend to report more ADHD symptoms than American parents and teachers as far as the oldest groups of children are concerned. Interactions are evidenced between school achievement, child gender, and informants. A relatively low rate of agreement between informants is found. CONCLUSION: These results strengthen the importance to take into account all informants in the pediatric and the child psychiatry clinic, as well as in the epidemiological studies.

Adverse Selection, Credit, and Efficiency: the Case of the Missing Market

We analyze a standard environment of adverse selection in credit markets. In our envi- ronment, entrepreneurs who are privately informed about the quality of their projects need to borrow from banks. As is generally the case in economies with adverse selection, the competitive equilibrium of our economy is shown to be ine¢ cient. Under adverse selection, the choices made by one type of agents limit what can be o¤ered to other types in an incentive-compatible manner. This gives rise to an externality, which cannot be internalized in a competitive equilibrium. We show that, in this type of environment, the ine¢ ciency associated to adverse selection is the consequence of one implicit assumption: entrepreneurs can only borrow from banks. If an additional market is added (say, a .security market.), in which entrepreneurs can obtain funds beyond those o¤ered by banks, we show that the e¢ cient allocation is an equilibrium of the economy. In such an equilibrium, all entrepreneurs borrow at a pooling rate in the security market. When they apply to bank loans, though, only entrepreneurs with good projects pledge these additional funds as collateral. This equilibrium thus simultaneously entails cross- subsidization and separation between di¤erent types of entrepreneurs.

On Certain Greedoid Polyhedra, Partially Indexable Scheduling Problems, and Extended Restless Bandit Allocation Indices

We present a polyhedral framework for establishing general structural properties on optimal solutions of stochastic scheduling problems, where multiple job classes vie for service resources: the existence of an optimal priority policy in a given family, characterized by a greedoid (whose feasible class subsets may receive higher priority), where optimal priorities are determined by class-ranking indices, under restricted linear performance objectives (partial indexability). This framework extends that of Bertsimas and Niño-Mora (1996), which explained the optimality of priority-index policies under all linear objectives (general indexability). We show that, if performance measures satisfy partial conservation laws (with respect to the greedoid), which extend previous generalized conservation laws, then the problem admits a strong LP relaxation over a so-called extended greedoid polytope, which has strong structural and algorithmic properties. We present an adaptive-greedy algorithm (which extends Klimov's) taking as input the linear objective coefficients, which (1) determines whether the optimal LP solution is achievable by a policy in the given family; and (2) if so, computes a set of class-ranking indices that characterize optimal priority policies in the family. In the special case of project scheduling, we show that, under additional conditions, the optimal indices can be computed separately for each project (index decomposition). We further apply the framework to the important restless bandit model (two-action Markov decision chains), obtaining new index policies, that extend Whittle's (1988), and simple sufficient conditions for their validity. These results highlight the power of polyhedral methods (the so-called achievable region approach) in dynamic and stochastic optimization.

Adverse selection, credit, and efficiency: the case of the missing market

We analyze a standard environment of adverse selection in credit markets. In our environment, entrepreneurs who are privately informed about the quality of their projects need to borrow in order to invest. Conventional wisdom says that, in this class of economies, the competitive equilibrium is typically inefficient. We show that this conventional wisdom rests on one implicit assumption: entrepreneurs can only access monitored lending. If a new set of markets is added to provide entrepreneurs with additional funds, efficiency can be attained in equilibrium. An important characteristic of these additional markets is that lending in them must be unmonitored, in the sense that it does not condition total borrowing or investment by entrepreneurs. This makes it possible to attain efficiency by pooling all entrepreneurs in the new markets while separating them in the markets for monitored loans.

Knowledge and attitudes of nurses towards alcohol and related problems: the impact of an educational intervention

An exploratory study of quasi-experimental approach that aimed to verify the impact of an educational intervention on attitudes and knowledge of nurses towards alcohol use and associated problems. The sample included 185 nurses, divided into two groups: 84 submitted to a training course and formed the experimental group. Data were collected through a knowledge survey and an attitude scale. The attitudes of the participants of both groups were positive. There were no significant differences between groups in relation to knowledge. The strongest predictors of positive attitudes were possessed preparation to act with chemical dependents (OR = 2.18), "have received increased workload during graduation on the theme, 'alcohol and other drugs'" (OR = 1.70), and "completed graduate school" (OR = 2.59). The educational intervention had a positive impact on the attitudes of nurses towards alcoholics, work and interpersonal relationships with such clientele.