@article{Oquendo2012,

title = {Machine Learning and Data Mining: Strategies for Hypothesis Generation},

author = {Maria A Oquendo and Enrique Baca-Garc\'{i}a and Antonio Art\'{e}s-Rodr\'{i}guez and Fernando Perez-Cruz and H C Galfalvy and Hilario Blasco-Fontecilla and D Madigan and N Duan},

url = {http://www.ncbi.nlm.nih.gov/pubmed/22230882},

issn = {1476-5578},

year  = {2012},

date = {2012-01-01},

journal = {Molecular psychiatry},

volume = {17},

number = {10},

pages = {956--959},

abstract = {Strategies for generating knowledge in medicine have included observation of associations in clinical or research settings and more recently, development of pathophysiological models based on molecular biology. Although critically important, they limit hypothesis generation to an incremental pace. Machine learning and data mining are alternative approaches to identifying new vistas to pursue, as is already evident in the literature. In concert with these analytic strategies, novel approaches to data collection can enhance the hypothesis pipeline as well. In data farming, data are obtained in an \'{o}rganic' way, in the sense that it is entered by patients themselves and available for harvesting. In contrast, in evidence farming (EF), it is the provider who enters medical data about individual patients. EF differs from regular electronic medical record systems because frontline providers can use it to learn from their own past experience. In addition to the possibility of generating large databases with farming approaches, it is likely that we can further harness the power of large data sets collected using either farming or more standard techniques through implementation of data-mining and machine-learning strategies. Exploiting large databases to develop new hypotheses regarding neurobiological and genetic underpinnings of psychiatric illness is useful in itself, but also affords the opportunity to identify novel mechanisms to be targeted in drug discovery and development.},

keywords = {Artificial Intelligence, Biological, Data Mining, Humans, Mental Disorders, Mental Disorders: diagnosis, Mental Disorders: therapy, Models},

pubstate = {published},

tppubtype = {article}

}

@article{Lopez-Castroman2011,

title = {Distinguishing the Relevant Features of Frequent Suicide Attempters},

author = {Jorge Lopez-Castroman and Mercedes M Perez-Rodriguez and Isabelle Jaussent and AnaLucia A Alegria and Antonio Art\'{e}s-Rodr\'{i}guez and Peter Freed and S\'{e}bastien Guillaume and Fabrice Jollant and Jose M Leiva-Murillo and Alain Malafosse and Maria A Oquendo and Mario de Prado-Cumplido and Jeronimo Saiz-Ruiz and Enrique Baca-Garc\'{i}a and Philippe Courtet},

url = {http://www.tsc.uc3m.es/~antonio/papers/P39_2011_Distinguishing the Relevant Features of Frequent Suicide Attempters.pdf 

http://www.ncbi.nlm.nih.gov/pubmed/21055768},

issn = {1879-1379},

year  = {2011},

date = {2011-01-01},

journal = {Journal of psychiatric research},

volume = {45},

number = {5},

pages = {619--625},

abstract = {BACKGROUND: In spite of the high prevalence of suicide behaviours and the magnitude of the resultant burden, little is known about why individuals reattempt. We aim to investigate the relationships between clinical risk factors and the repetition of suicidal attempts. METHODS: 1349 suicide attempters were consecutively recruited in the Emergency Room (ER) of two academic hospitals in France and Spain. Patients were extensively assessed and demographic and clinical data obtained. Data mining was used to determine the minimal number of variables that blinded the rest in relation to the number of suicide attempts. Using this set, a probabilistic graph ranking relationships with the target variable was constructed. RESULTS: The most common diagnoses among suicide attempters were affective disorders, followed by anxiety disorders. Risk of frequent suicide attempt was highest among middle-aged subjects, and diminished progressively with advancing age of onset at first attempt. Anxiety disorders significantly increased the risk of presenting frequent suicide attempts. Pathway analysis also indicated that frequent suicide attempts were linked to greater odds for alcohol and substance abuse disorders and more intensive treatment. CONCLUSIONS: Novel statistical methods found several clinical features that were associated with a history of frequent suicide attempts. The identified pathways may promote new hypothesis-driven studies of suicide attempts and preventive strategies.},

keywords = {Adult, Attempted, Attempted: psychology, Attempted: statistics \& numerical data, Female, France, Humans, Interview, Male, Middle Aged, Prevalence, Probability, Psychiatric Status Rating Scales, Psychological, Risk Factors, ROC Curve, Spain, Suicide},

pubstate = {published},

tppubtype = {article}

}

@article{Carballo2010,

title = {Stability of Childhood Anxiety Disorder Diagnoses: a Follow-Up Naturalistic Study in Psychiatric Care},

author = {Juan J Carballo and Enrique Baca-Garc\'{i}a and Carlos Blanco and Mercedes M Perez-Rodriguez and Miguel A Jimenez-Arriero and Antonio Art\'{e}s-Rodr\'{i}guez and Moira Rynn and David Shaffer and Maria A Oquendo},

url = {http://www.ncbi.nlm.nih.gov/pubmed/19826859},

issn = {1435-165X},

year  = {2010},

date = {2010-01-01},

journal = {European child \& adolescent psychiatry},

volume = {19},

number = {4},

pages = {395--403},

abstract = {Few studies have examined the stability of major psychiatric disorders in pediatric psychiatric clinical populations. The objective of this study was to examine the long-term stability of anxiety diagnoses starting with pre-school age children through adolescence evaluated at multiple time points. Prospective cohort study was conducted of all children and adolescents receiving psychiatric care at all pediatric psychiatric clinics belonging to two catchment areas in Madrid, Spain, between 1 January, 1992 and 30 April, 2006. Patients were selected from among 24,163 children and adolescents who received psychiatric care. Patients had to have a diagnosis of an ICD-10 anxiety disorder during at least one of the consultations and had to have received psychiatric care for the anxiety disorder. We grouped anxiety disorder diagnoses according to the following categories: phobic disorders, social anxiety disorders, obsessive-compulsive disorder (OCD), stress-related disorders, and \"{o}ther" anxiety disorders which, among others, included generalized anxiety disorder, and panic disorder. Complementary indices of diagnostic stability were calculated. As much as 1,869 subjects were included and had 27,945 psychiatric/psychological consultations. The stability of all ICD-10 anxiety disorder categories studied was high regardless of the measure of diagnostic stability used. Phobic and social anxiety disorders showed the highest diagnostic stability, whereas OCD and \"{o}ther" anxiety disorders showed the lowest diagnostic stability. No significant sex differences were observed on the diagnostic stability of the anxiety disorder categories studied. Diagnostic stability measures for phobic, social anxiety, and \"{o}ther" anxiety disorder diagnoses varied depending on the age at first evaluation. In this clinical pediatric outpatient sample it appears that phobic, social anxiety, and stress-related disorder diagnoses in children and adolescents treated in community outpatient services may have high diagnostic stability.},

keywords = {Adolescent, Ambulatory Care, Ambulatory Care: utilization, Anxiety Disorders, Anxiety Disorders: diagnosis, Anxiety Disorders: epidemiology, Catchment Area (Health), Child, Cohort Studies, Female, Follow-Up Studies, Humans, International Classification of Diseases, Male, Mental Health Services, Mental Health Services: utilization, Preschool, Prospective Studies, Severity of Illness Index, Spain, Spain: epidemiology},

pubstate = {published},

tppubtype = {article}

}

@article{Baca-Garcia2008,

title = {Patterns of Mental Health Service Utilization in a General Hospital and Outpatient Mental Health Facilities: Analysis of 365,262 Psychiatric Consultations},

author = {Enrique Baca-Garc\'{i}a and Mercedes M Perez-Rodriguez and Ignacio Basurte-Villamor and Javier F Quintero-Gutierrez and Juncal Sevilla-Vicente and Maria Martinez-Vigo and Antonio Art\'{e}s-Rodr\'{i}guez and Antonio Fernandez L del Moral and Miguel A Jimenez-Arriero and Jose Gonzalez L de Rivera},

url = {http://www.ncbi.nlm.nih.gov/pubmed/17990050},

issn = {0940-1334},

year  = {2008},

date = {2008-01-01},

journal = {European archives of psychiatry and clinical neuroscience},

volume = {258},

number = {2},

pages = {117--123},

abstract = {PURPOSE: Mental health is one of the priorities of the European Commission. Studies of the use and cost of mental health facilities are needed in order to improve the planning and efficiey of mental health resources. We analyze the patterns of mental health service use in multiple clinical settings to identify factors associated with high cost. SUBJECTS AND METHODS: 22,859 patients received psychiatric care in the catchment area of a Spanish hospital (2000-2004). They had 365,262 psychiatric consultations in multiple settings. Two groups were selected that generated 80% of total costs: the medium cost group (N = 4,212; 50% of costs), and the high cost group (N = 236; 30% of costs). Statistical analyses were performed using univariate and multivariate techniques. Significant variables in univariate analyses were introduced as independent variables in a logistic regression analysis using "high cost" (\>7,263$) as dependent variable. RESULTS: Costs were not evenly distributed throughout the sample. 19.4% of patients generated 80% of costs. The variables associated with high cost were: age group 1 (0-14 years) at the first evaluation, permanent disability, and ICD-10 diagnoses: Organic, including symptomatic, mental disorders; Mental and behavioural disorders due to psychoactive substance use; Schizophrenia, schizotypal and delusional disorders; Behavioural syndromes associated with physiological disturbances and physical factors; External causes of morbidity and mortality; and Factors influencing health status and contact with health services. DISCUSSION: Mental healthcare costs were not evenly distributed throughout the patient population. The highest costs are associated with early onset of the mental disorder, permanent disability, organic mental disorders, substance-related disorders, psychotic disorders, and external factors that influence the health status and contact with health services or cause morbidity and mortality. CONCLUSION: Variables related to psychiatric diagnoses and sociodemographic factors have influence on the cost of mental healthcare.},

keywords = {80 and over, Adolescent, Adult, Age Distribution, Aged, Ambulatory Care, Ambulatory Care: statistics \& numerical data, Ambulatory Care: utilization, Child, Diagnosis-Related Groups, Female, General, General: statistics \& numerical data, General: utilization, Health Care Costs, Health Care Costs: statistics \& numerical data, Health Services Accessibility, Health Services Accessibility: statistics \& numeri, Health Services Needs and Demand, Health Services Needs and Demand: statistics \& num, Hospitals, Humans, Male, Mental Disorders, Mental Disorders: classification, Mental Disorders: diagnosis, Mental Disorders: epidemiology, Mental Disorders: therapy, Mental Health Services, Mental Health Services: economics, Mental Health Services: utilization, Middle Aged, Outcome and Process Assessment (Health Care), Preschool, Psychiatry, Psychiatry: economics, Psychiatry: statistics \& numerical data, Sex Distribution, Spain, Spain: epidemiology, Utilization Review, Utilization Review: statistics \& numerical data},

pubstate = {published},

tppubtype = {article}

}