A drug administration decision support system

Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.

Deploying the Maintenance Decision Support System (MDSS) in Iowa, 2003

Adverse weather conditions dramatically affect the nation’s surface transportation system. The development of a prototype winter Maintenance Decision Support System (MDSS) is part of the Federal Highway Administration’s effort to produce a prototype tool for decision support to winter road maintenance managers to help make the highways safer for the traveling public. The MDSS is based on leading diagnostic and prognostic weather research capabilities and road condition algorithms, which are being developed at national research centers. In 2003, the Iowa Department of Transportation was chosen as a field test bed for the continuing development of this important research program. The Center for Transportation Research and Education assisted the Iowa Department of Transportation by collecting and analyzing surface condition data. The Federal Highway Administration also selected five national research centers to participate in the development of the prototype MDSS. It is anticipated that components of the prototype MDSS system developed by this project will ultimately be deployed by road operating agencies, including state departments of transportation, and generally supplied by private vendors.

A decision support system for selective cleaning

[Abstract]

Evaluation of a revision of the BSPcast decision support system for control of brown spot of pear

Control of brown spot of pear requires fungicide treatments of pear trees during the growing season. Scheduling fungicide sprays with the Brown spot of pear forecasting system (BSPcast) provides significantfungicide savings but does not increase the efficacy of disease control. Modifications in BSPcast wereintroduced in order to increase system performance. The changes consisted of: (1) the use of a daily infectionrisk (Rm≥0.2) instead of the 3-day cumulative risk (CR≥0.4) to guide the fungicide scheduling, and (2) theinclusion of the effect of relative humidity during interrupted wetness periods. Trials were performed during2 years in an experimental pear orchard in Spain. The modifications introduced did not result in increaseddisease control efficacy, compared with the original BSPcast system. In one year, no reduction in the numberof fungicide applications was obtained using the modified BSPcast system in comparison to the original system, but in the second year the number of treatments was reduced from 15 to 13. The original BSPcast model overestimated the daily infection risk in 6.5% of days with wetness periods with low relative humidity during the wetness interruption, and in these cases the modified version was more adequate

A decision support system for cost determination in grain storage facility operations

Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, hourly capacity of drying, cleaning, and receiving, and dispatch. By applying the decision support system, it was observed that the reception and expedition costs were exponentially reduced as the turnover rate of the storage increased. The cleaning and drying costs increased linearly with grain initial moisture. The storage cost increased exponentially as the occupancy rate of the storage facility decreased.

Decision support system for the diagnosis of schizophrenia disorders

Clinical decision support systems are useful tools for assisting physicians to diagnose complex illnesses. Schizophrenia is a complex, heterogeneous and incapacitating mental disorder that should be detected as early as possible to avoid a most serious outcome. These artificial intelligence systems might be useful in the early detection of schizophrenia disorder. The objective of the present study was to describe the development of such a clinical decision support system for the diagnosis of schizophrenia spectrum disorders (SADDESQ). The development of this system is described in four stages: knowledge acquisition, knowledge organization, the development of a computer-assisted model, and the evaluation of the system's performance. The knowledge was extracted from an expert through open interviews. These interviews aimed to explore the expert's diagnostic decision-making process for the diagnosis of schizophrenia. A graph methodology was employed to identify the elements involved in the reasoning process. Knowledge was first organized and modeled by means of algorithms and then transferred to a computational model created by the covering approach. The performance assessment involved the comparison of the diagnoses of 38 clinical vignettes between an expert and the SADDESQ. The results showed a relatively low rate of misclassification (18-34%) and a good performance by SADDESQ in the diagnosis of schizophrenia, with an accuracy of 66-82%. The accuracy was higher when schizophreniform disorder was considered as the presence of schizophrenia disorder. Although these results are preliminary, the SADDESQ has exhibited a satisfactory performance, which needs to be further evaluated within a clinical setting.

A dynamic knowledge-based decision support system to handle solids separation problems in activated sludge systems: development and validation

El sistema de fangs activats és el tractament biològic més àmpliament utilitzat arreu del món per la depuració d'aigües residuals. El seu funcionament depèn de la correcta operació tant del reactor biològic com del decantador secundari. Quan la fase de sedimentació no es realitza correctament, la biomassa no decantada s'escapa amb l'efluent causant un impacte sobre el medi receptor. Els problemes de separació de sòlids, són actualment una de les principals causes d'ineficiència en l'operació dels sistemes de fangs activats arreu del món. Inclouen: bulking filamentós, bulking viscós, escumes biològiques, creixement dispers, flòcul pin-point i desnitrificació incontrolada. L'origen dels problemes de separació generalment es troba en un desequilibri entre les principals comunitats de microorganismes implicades en la sedimentació de la biomassa: els bacteris formadors de flòcul i els bacteris filamentosos. Degut a aquest origen microbiològic, la seva identificació i control no és una tasca fàcil pels caps de planta. Els Sistemes de Suport a la Presa de Decisions basats en el coneixement (KBDSS) són un grup d'eines informàtiques caracteritzades per la seva capacitat de representar coneixement heurístic i tractar grans quantitats de dades. L'objectiu de la present tesi és el desenvolupament i validació d'un KBDSS específicament dissenyat per donar suport als caps de planta en el control dels problemes de separació de sòlids d'orígen microbiològic en els sistemes de fangs activats. Per aconseguir aquest objectiu principal, el KBDSS ha de presentar les següents característiques: (1) la implementació del sistema ha de ser viable i realista per garantir el seu correcte funcionament; (2) el raonament del sistema ha de ser dinàmic i evolutiu per adaptar-se a les necessitats del domini al qual es vol aplicar i (3) el raonament del sistema ha de ser intel·ligent. En primer lloc, a fi de garantir la viabilitat del sistema, s'ha realitzat un estudi a petita escala (Catalunya) que ha permès determinar tant les variables més utilitzades per a la diagnosi i monitorització dels problemes i els mètodes de control més viables, com la detecció de les principals limitacions que el sistema hauria de resoldre. Els resultats d'anteriors aplicacions han demostrat que la principal limitació en el desenvolupament de KBDSSs és l'estructura de la base de coneixement (KB), on es representa tot el coneixement adquirit sobre el domini, juntament amb els processos de raonament a seguir. En el nostre cas, tenint en compte la dinàmica del domini, aquestes limitacions es podrien veure incrementades si aquest disseny no fos òptim. En aquest sentit, s'ha proposat el Domino Model com a eina per dissenyar conceptualment el sistema. Finalment, segons el darrer objectiu referent al seguiment d'un raonament intel·ligent, l'ús d'un Sistema Expert (basat en coneixement expert) i l'ús d'un Sistema de Raonament Basat en Casos (basat en l'experiència) han estat integrats com els principals sistemes intel·ligents encarregats de dur a terme el raonament del KBDSS. Als capítols 5 i 6 respectivament, es presenten el desenvolupament del Sistema Expert dinàmic (ES) i del Sistema de Raonament Basat en Casos temporal, anomenat Sistema de Raonament Basat en Episodis (EBRS). A continuació, al capítol 7, es presenten detalls de la implementació del sistema global (KBDSS) en l'entorn G2. Seguidament, al capítol 8, es mostren els resultats obtinguts durant els 11 mesos de validació del sistema, on aspectes com la precisió, capacitat i utilitat del sistema han estat validats tant experimentalment (prèviament a la implementació) com a partir de la seva implementació real a l'EDAR de Girona. Finalment, al capítol 9 s'enumeren les principals conclusions derivades de la present tesi.

Development of a decision support system for the integrated control of membrane bioreactors

The work presented in this PhD thesis includes various partial studies aimed at developing a decision support system for membrane bioreactor integrated control. The decision support systems (DSS) have as a main goal to facilitate the operation of complex processes due to the multiple variables that are processed. For this reason, the research used has focused on aspects related to nutrient removal, and on the development of indicators or sensors capable of facilitating, automating and controlling the filtration process in an integrated way with the biological processes that taking place. Work has also been done on the design, development, implementation and validation of tools based on the knowledge made available by the automatic control and the supervision of the MBRs

EDSS-maintenance prototype: an environmental decision support system to assess the definition of operation and maintenance protocols for horizontal subsurface constructed wetlands

Els Sistemes d'Aiguamolls Construïts (SAC) de Flux Subsuperficial Horitzontal (FSH) és una tecnologia apropiada pel sanejament d'aigües residuals procedents de nuclis de població petits. No obstant els SAC de FSH són considerats una tecnologia natural, l'operació i manteniment d'aquestes depuradores és crucial per a garantir el seu correcte funcionament. Aquestes necessitats d'operació i manteniment varien entre depuradores segons (1) les característiques de la comunitat, (2) la configuració de la depuradora i el disseny del SAC de FSH i (3) les característiques del medi receptor. En aquest sentit, en aquesta tesi es presenta el desenvolupament d'un Sistema d'Ajuda a la Decisió (SAD) per a la definició de protocols d'operació i manteniment per a SAC de FSH tenint en compte els factors que causen variabilitat entre aquest tipus de depuradores (1, 2 i 3).