983 resultados para Medical Informatics Computing


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We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

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In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatent of Parkinson's disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different registration algorithms and to evaluate their ability to locate the STN automatically. Using this scheme we can evaluate the expert variability against the error of the algorithms and we demonstrate that automatic STN location is possible and as accurate as the methods currently used.

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Terveydenhuollossa käytetään nykyisin informaatioteknologian (IT) mahdollisuuksia parantamaan hoidon laatua, vähentämään hoitoon liittyviä kuluja sekä yksinkertaistamaan ja selkeyttämään laakareiden työnkulkua. Tietojärjestelmät, jotka edustavat jokaisen IT-ratkaisun ydintä, täytyy kehittää täyttämään lukuisia vaatimuksia, ja yksi niistä on kyky integroitua saumattomasti toisten tietojärjestelmien kanssa. Järjestelmäintegraatio on kuitenkin yhä haastava tehtävä, vaikka sita varten on kehitetty useita standardeja. Tässä työssä kuvataan vastakehitetyn lääketieteellisen tietojärjestelmän liittymäratkaisu. Työssä pohditaan vaatimuksia, jotka tällaiselle sovellukselle asetetaan, ja myös tapa, jolla vaatimukset toteutuvat on esitetty. Liittymaratkaisu on jaettu kahteen osaan, tietojärjestelmaliittymään ja "liittymakoneeseen" (interfacing engine). Edellinen on käsittää perustoiminnallisuuden, jota tarvitaan vastaanottamaan ja lähettämään tietoa toisiin järjestelmiin, kun taas jälkimmäinen tarjoaa tuen tuotantoympäristössa käytettäville standardeille. Molempien osien suunnitelu on esitelty perusteellisesti tässä työssä. Ongelma ratkaistiin modulaarisen ja geneerisen suunnittelun avulla. Tämä lähestymistapa osoitetaan työssä kestäväksi ja joustavaksi ratkaisuksi, jota voidaan käyttää tarkastelemaan laajaa valikoimaa liittymäratkaisulle asetettuja vaatimuksia. Lisaksi osoitetaan kuinka tehty ratkaisu voidaan joustavuutensa ansiosta helposti mukauttaa vaatimuksiin, joita ei ole etukäteen tunnistettu, ja siten saavutetaan perusta myös tulevaisuuden tarpeille

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Fetal MRI reconstruction aims at finding a high-resolution image given a small set of low-resolution images. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has considered several regularization terms s.a. Dirichlet/Laplacian energy [1], Total Variation (TV)based energies [2,3] and more recently non-local means [4]. Although TV energies are quite attractive because of their ability in edge preservation, standard explicit steepest gradient techniques have been applied to optimize fetal-based TV energies. The main contribution of this work lies in the introduction of a well-posed TV algorithm from the point of view of convex optimization. Specifically, our proposed TV optimization algorithm for fetal reconstruction is optimal w.r.t. the asymptotic and iterative convergence speeds O(1/n(2)) and O(1/root epsilon), while existing techniques are in O(1/n) and O(1/epsilon). We apply our algorithm to (1) clinical newborn data, considered as ground truth, and (2) clinical fetal acquisitions. Our algorithm compares favorably with the literature in terms of speed and accuracy.

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INFORMACION E INFORMATICA La evolución del ser humano se ha comparado a una espiral ascendente cuyo radio es cada vez menor, queriendo simbolizar con ella el incremento en la velocidad con la que se adquieren nuevas conocimientos y aplicaciones de los mismos que son en definitiva, una consecuencia de toda la experiencia acumulada previamente...

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This study was aimed to analyze and assess the use and perception of electronic health records (EHRs) by nurses. The study sample included 113 nurses from different shifts of primary health facilities in Catalonia, Spain, devoted to adult as well as pediatric outpatients using EHRs throughout the year 2010. A majority of the sample (87.5%) were women and 12.5% were men. The average age was 44.27 years and the average time working in primary healthcare was 47.15 months. A majority (80.4%) received specific training on the use of the EHR and 19.6% did not. The use of the application required side technical support (mean: 3.42) and it is considered necessary to learn more about the performance of the application (mean: 3.50). The relationship between the average ratings that nurses have about the EHR and age shows that there is no statistically significant linear relationship (r = - 0.002, p-value = 0.984). As to how long they have used the EHRs, there are significant differences (r= -0.304, p-value = 0.00), so the more time the nurse takes using the EHR, the greater degree of satisfaction is shown. In addition, there are significant differences between nurses" perceptions regarding the EHR and gender (t = - 0.421, p-value = 0.675). Nurses assessed as positive the contribution of the EHRs in their nursing care day work (average score: 2.55/5). Considering that the usability of the EHR device is assessed as satisfactory, the results of the perception of nurses show that we must also take into account the training and emphasize the need for a side technical support in the implementation process of the EHR. Doing so, the positive perception that nurses have in regard to information and communication technology in general and with respect to the EHR in particular may be increased.

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This study was aimed to analyze and assess the use and perception of electronic health records (EHRs) by nurses. The study sample included 113 nurses from different shifts of primary health facilities in Catalonia, Spain, devoted to adult as well as pediatric outpatients using EHRs throughout the year 2010. A majority of the sample (87.5%) were women and 12.5% were men. The average age was 44.27 years and the average time working in primary healthcare was 47.15 months. A majority (80.4%) received specific training on the use of the EHR and 19.6% did not. The use of the application required side technical support (mean: 3.42) and it is considered necessary to learn more about the performance of the application (mean: 3.50). The relationship between the average ratings that nurses have about the EHR and age shows that there is no statistically significant linear relationship (r = - 0.002, p-value = 0.984). As to how long they have used the EHRs, there are significant differences (r= -0.304, p-value = 0.00), so the more time the nurse takes using the EHR, the greater degree of satisfaction is shown. In addition, there are significant differences between nurses" perceptions regarding the EHR and gender (t = - 0.421, p-value = 0.675). Nurses assessed as positive the contribution of the EHRs in their nursing care day work (average score: 2.55/5). Considering that the usability of the EHR device is assessed as satisfactory, the results of the perception of nurses show that we must also take into account the training and emphasize the need for a side technical support in the implementation process of the EHR. Doing so, the positive perception that nurses have in regard to information and communication technology in general and with respect to the EHR in particular may be increased.

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Cualquiera que pregunte a un médico qué desea de una historia clínica informatizada recibirá la misma respuesta:'poder obtener información actualizada y útil del paciente cuando quiera, dónde quiera y cómo quiera'. Para dar respuesta a este deseo, totalmente lógico y comprensible, es necesario abordar el problema desde una visión informática especialmente amplia, ya que la información médica tiene unos formatos de estructuras muy heterogénea y de consulta muy variada...

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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.

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Introduction : La cyber santé (CS) a le potentiel d’améliorer l'efficience et l'efficacité des services de santé. Malgré cela, son adoption demeure problématique et jusqu’à 70 % des projets d’implantation échouent. Objectifs : Cette étude vise à évaluer l’état de préparation d’une organisation par rapport à la CS et à identifier les facteurs personnels qui influencent cet état. Méthode : Une étude transversale a été réalisée auprès de 137 cliniciens, 28 gestionnaires et 47 membres du personnel non clinique d’un centre de réadaptation à Montréal. Les participants ont répondu à un questionnaire auto administré sur l’état de préparation organisationnelle vis-à-vis la CS qui comprend trois sous échelles (Individu, Organisation et Technologie) avec chacune un score sur 100. Des données ont aussi été colligées sur le profil des utilisateurs, leur utilisation des technologies et leur style de réponse à la nouvelle information. Résultats : Les participants se perçoivent prêts à adopter la CS dans leur travail ( = 73.8, SD = 8.5) et perçoivent aussi favorablement les technologies disponibles ( = 73.8, SD = 7.2). Toutefois, le personnel perçoit le centre comme étant modérément prête ( = 66.6, SD = 9.8). La charge de travail perçue et la fonction au sein de l'organisation ont été identifiées comme ayant une influence sur l'état de préparation à la CS. Discussion : Ces résultats appuient la pertinence d’aborder l’état de préparation organisationnelle comme un concept multidimensionnel. À partir des résultats obtenus, des stratégies d'implantation adaptées ont pu être identifiées.

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The characterization and grading of glioma tumors, via image derived features, for diagnosis, prognosis, and treatment response has been an active research area in medical image computing. This paper presents a novel method for automatic detection and classification of glioma from conventional T2 weighted MR images. Automatic detection of the tumor was established using newly developed method called Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA).Statistical Features were extracted from the detected tumor texture using first order statistics and gray level co-occurrence matrix (GLCM) based second order statistical methods. Statistical significance of the features was determined by t-test and its corresponding p-value. A decision system was developed for the grade detection of glioma using these selected features and its p-value. The detection performance of the decision system was validated using the receiver operating characteristic (ROC) curve. The diagnosis and grading of glioma using this non-invasive method can contribute promising results in medical image computing

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Desde la noción universal sobre la empresa como un sistema de interacción con un entorno determinado para alcanzar un objetivo, de manera planificada y en función de satisfacer las demandas de un mercado mediante la actividad económica, su viabilidad, sostenibilidad y crecimiento dependerán, por supuesto, de una serie de estrategias adecuadas no solo para tales fines, sino también para enfrentar diversidad de agentes endógenos y exógenos que puedan afectar el normal desempeño de su gestión. Estamos hablando de la importancia de la resiliencia organizacional y del Capital Psicológico. En un escenario tan impredecible como el de la economía mundial, donde la constante son los cambios en su comportamiento —unos propios de su dinámica e interdependencia, naturales de fenómenos como la globalización, y otros derivados de eventos disruptivos— hoy más que nunca es necesario implementar el modelo de la empresa resiliente, que es aquella entidad capaz de adaptarse y recuperarse frente a una perturbación. Al mismo tiempo, más allá de su tamaño, naturaleza u objeto social, es indispensable reconocer básicamente que toda organización está constituida por personas, lo cual implica la trascendencia que para su funcionamiento tiene el factor humano-dependiente, y por lo tanto se crea la necesidad de promover el Capital Psicológico y la resiliencia a nivel de las organizaciones a través de una cultura empresarial.

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Este texto contribuirá a que la institución de salud se organice y prepare la información necesaria para emprender el largo y tortuoso camino de la determinación de la razón costo/beneficio y de la acreditación. Además, podrá ser muy útil para los estudiantes de los programas de pregrado y posgrado de ingeniería biomédica que se quieran especializar en la gestión de tecnologías del equipamiento biomédico y la ingeniería clínica. También podrá ser usado como guía de referencia por personas que estén directamente vinculadas al sector de la salud en departamentos de mantenimiento, ingeniería clínica o de servicios hospitalarios.

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