Using temporal abduction for biosignal interpretation: A case study on QRS detection

In this work, we propose an abductive framework for biosignal interpretation, based on the concept of Temporal Abstraction Patterns. A temporal abstraction pattern defines an abstraction relation between an observation hypothesis and a set of observations constituting its evidence support. New observations are generated abductively from any subset of the evidence of a pattern, building an abstraction hierarchy of observations in which higher levels contain those observations with greater interpretative value of the physiological processes underlying a given signal. Non-monotonic reasoning techniques have been applied to this model in order to find the best interpretation of a set of initial observations, permitting even to correct these observations by removing, adding or modifying them in order to make them consistent with the available domain knowledge. Some preliminary experiments have been conducted to apply this framework to a well known and bounded problem: the QRS detection on ECG signals. The objective is not to provide a new better QRS detector, but to test the validity of an abductive paradigm. These experiments show that a knowledge base comprising just a few very simple rhythm abstraction patterns can enhance the results of a state of the art algorithm by significantly improving its detection F1-score, besides proving the ability of the abductive framework to correct both sensitivity and specificity failures.Comment: 7 pages, Healthcare Informatics (ICHI), 2014 IEEE International Conference o

A method for context-based adaptive QRS clustering in real-time

Continuous follow-up of heart condition through long-term electrocardiogram monitoring is an invaluable tool for diagnosing some cardiac arrhythmias. In such context, providing tools for fast locating alterations of normal conduction patterns is mandatory and still remains an open issue. This work presents a real-time method for adaptive clustering QRS complexes from multilead ECG signals that provides the set of QRS morphologies that appear during an ECG recording. The method processes the QRS complexes sequentially, grouping them into a dynamic set of clusters based on the information content of the temporal context. The clusters are represented by templates which evolve over time and adapt to the QRS morphology changes. Rules to create, merge and remove clusters are defined along with techniques for noise detection in order to avoid their proliferation. To cope with beat misalignment, Derivative Dynamic Time Warping is used. The proposed method has been validated against the MIT-BIH Arrhythmia Database and the AHA ECG Database showing a global purity of 98.56% and 99.56%, respectively. Results show that our proposal not only provides better results than previous offline solutions but also fulfills real-time requirements.Comment: 12 pages, 6 figure

Non-parametric Estimation of Stochastic Differential Equations with Sparse Gaussian Processes

The application of Stochastic Differential Equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we introduce a non-parametric method for estimating the drift and diffusion terms of SDEs from a densely observed discrete time series. The use of Gaussian processes as priors permits working directly in a function-space view and thus the inference takes place directly in this space. To cope with the computational complexity that requires the use of Gaussian processes, a sparse Gaussian process approximation is provided. This approximation permits the efficient computation of predictions for the drift and diffusion terms by using a distribution over a small subset of pseudo-samples. The proposed method has been validated using both simulated data and real data from economy and paleoclimatology. The application of the method to real data demonstrates its ability to capture the behaviour of complex systems

Management of acute diverticulitis with pericolic free gas (ADIFAS). an international multicenter observational study

Background: There are no specific recommendations regarding the optimal management of this group of patients. The World Society of Emergency Surgery suggested a nonoperative strategy with antibiotic therapy, but this was a weak recommendation. This study aims to identify the optimal management of patients with acute diverticulitis (AD) presenting with pericolic free air with or without pericolic fluid. Methods: A multicenter, prospective, international study of patients diagnosed with AD and pericolic-free air with or without pericolic free fluid at a computed tomography (CT) scan between May 2020 and June 2021 was included. Patients were excluded if they had intra-abdominal distant free air, an abscess, generalized peritonitis, or less than a 1-year follow-up. The primary outcome was the rate of failure of nonoperative management within the index admission. Secondary outcomes included the rate of failure of nonoperative management within the first year and risk factors for failure. Results: A total of 810 patients were recruited across 69 European and South American centers; 744 patients (92%) were treated nonoperatively, and 66 (8%) underwent immediate surgery. Baseline characteristics were similar between groups. Hinchey II-IV on diagnostic imaging was the only independent risk factor for surgical intervention during index admission (odds ratios: 12.5, 95% CI: 2.4-64, P =0.003). Among patients treated nonoperatively, at index admission, 697 (94%) patients were discharged without any complications, 35 (4.7%) required emergency surgery, and 12 (1.6%) percutaneous drainage. Free pericolic fluid on CT scan was associated with a higher risk of failure of nonoperative management (odds ratios: 4.9, 95% CI: 1.2-19.9, P =0.023), with 88% of success compared to 96% without free fluid ( P <0.001). The rate of treatment failure with nonoperative management during the first year of follow-up was 16.5%. Conclusion: Patients with AD presenting with pericolic free gas can be successfully managed nonoperatively in the vast majority of cases. Patients with both free pericolic gas and free pericolic fluid on a CT scan are at a higher risk of failing nonoperative management and require closer observation

An evaluation of indexes as support tools in the diagnosis of sleep apnea

Abstract This article evaluates several indexes as support tools to diagnose pa-1 tients with Sleep Apnea-Hypopnea Syndrome (SAHS). Some of these indexes, such as the Apnea-Hypopnea Index, have been standardized and studied in depth in the literature. Other indexes are used extensively in the reports that commercial polysomnographs generate. However, they have not been studied in detail and clinicians have no standardized guidelines for interpreting them. Examples are the mean and maximum duration of apneas and hypopneas. Finally, several novel indexes proposed by the authors are also evaluated. To evaluate the indexes, we have used a database of 274 patients who have undergone a polysomnographic test. Several feature selection techniques were used to assess the capability of each index to discriminate between healthy and SAHS patients. The capability of the indexes for diagnosing the patients was analyzed by using decision trees which were trained using each index individually, and all the indexes together. Our results suggest that some indexes which are often present in the reports of commercial polysomnographs provide little or no information. On the other hand, other indexes that are usually not considered have a great capability to discern between SAHS and control patients

Comparison of standard and artificial neural network estimators of hemodialysis adequacy

The National Kidney Foundation and the European Renal Association recommend routine measurement of hemodialysis (HD) dose and have set standards for adequacy of treatment. We compare the results of five methods for HD dose estimation, classifying each result as adequate or inadequate on the basis of equilibrated (eq) Urea Reduction Ratio (URReq) ≥ 65% or Kt/V eq ≥ 1.2, to assess the accuracy of each method as a diagnostic tool. Data from 113 patients from two different dialysis units were analyzed. Equilibrated postdialysis blood urea was measured 60 min after each hemodialysis session to calculate URReq and Kt/Veq, considered as gold standard indexes (GSI). URR and Kt/V were estimated by using the Smye formula, an artificial neural network (ANN), modified URR, the second generation Kt/V Daugirdas formula, and standard indexes based on postdialysis urea, then compared to the GSI. For URR, best estimator was ANN (error rate: ER% = 12.70), followed by modified URR (ER% = 17.46%), the Smye (ER% = 22.22), and standard URR (ER% = 23.81). For Kt/V, the Daugirdas equation and the ANN were similar (ER% = 9.52 and 11.11). The single-pool Kt/V (Kt/Vsp) ≥ 1.4 (ERA recommended) produced an ER% = 7.94 and a false positive rate (FPR%) equal to that shown by the ANN (FPR% = 3.17). According to the current threshold limits for HD dose adequacy, the ANN was a reliable and accurate tool for URR monitoring, better than the Smye and the modified URR methods. The use of the ANN urea estimation yields accurate results when used to calculate Kt/V. The Kt/Vsp with an adequacy threshold of 1.4 is a superior approach for HD adequacy monitoring, suggesting that the current adequacy limits should be reviewed for both URR and Kt/V.Fil: Fernández, Elmer. Universidad Católica de Córdoba. Facultad de Ciencias de la Salud; ArgentinaFil: Valtuille, Rodolfo. Fresenius Medical Care, Buenos Aires, ArgentinaFil: Presedo, J.M.R. University of Santiago de Compostela, Santiago de Compostela, SpainFil: Willshaw, Peter. School of Health Science, University of Wales, Swansea, United Kingdo

Comparison of different methods for hemodialysis evaluation by means of ROC curves: From artificial intelligence to current methods

Background: The National Kidney Foundation Guidelines (DOQI) and the European Renal Association (ERA) have set standards for adequacy of hemodialysis treatment. They recommended minimum single pool doses of 1.2 (Kt/Vsp DOQI), and 1.4 (Kt/Vsp ERA) and a "standard" urea removal ratio (URR) of 65%. Here, we compare an Artificial Intelligence Method (AIM) based on an Artificial Neural Network (ANN) and the usual methods for hemodialysis treatment follow-up such as Smye, Daugirdas, standard urea reduction ratio (URR using post-dialysis urea concentration) and modified URR [Cheng et al. 2001] against equilibrated Kt/V and URR calculated using a 60 min post-dialysis urea concentration. Methods: We used ROC analysis to evaluate and compare these methodologies. We also propose a method to find a minimum target dose that maximizes the sensitivity, specificity and positive predictive values of the diagnostic tool. Results: From a URR point of view, the ANN, stdURR and mURR perform almost equally well with an area under the curve (AUC) of 0.90, 0.93 and 0.92, respectively, but the ANN achieved the lowest false positive rate (FPR = 7.94%) and error rate (ER = 12.7%). When Kt/V is used as a dose index, the logarithmic single-and double-pool equations perform almost equally (AUC 0.957 and 0.962), and the ANN method achieves an AUC of 0.934. The lowest FPR was for ANN and Kt/Vsp (4.76%), which also achieved the lowest ER of 6.39%. Conclusions: For both cases (URR and Kt/V), the minimum doses required to achieve the lowest FPR and ER for the standard methods (stdURR and Kt/Vsp) were higher than those reported by the DOQI guidelines, being 70% for stdURR and 1.35 for Kt/Vsp, whereas for those methods using the double-pool Kt/V or equilibrated URR, the dose targets were close to those recommended by DOQI and ERA. Our proposed method for target dose selection is easy to understand, and it takes into account both accuracy and confidence of the adequacy tool. We found the ANN method to be superior to the Smye method for estimation of equilibrated urea, and the results presented here suggest that ANN methods could be useful tools in the analysis of nephrology data.Fil: Fernández, Elmer. Universidad Católica de Córdoba. Facultad de Ciencias de la Salud; ArgentinaFil: Valtuille, Rodolfo. Fresenius Medical Care, Buenos Aires, ArgentinaFil: Presedo, J.M.R. University of Santiago de Compostela, Santiago de Compostela, SpainFil: Willshaw, P. School of Health Science, University of Wales, Swansea, United Kingdo

SUTIL : intelligent ischemia monitoring system

SUTIL is an intelligent monitoring system for intensive and exhaustive follow up of patients in coronary care units. This system processes electrocardiographic and hemodynamic signals in real time, with the main objective of detecting ischemic episodes. In this paper, we describe the tasks included in SUTIL. In addition to basic tasks, those at higher levels will also be presented. Some of these latter tasks attempt to mimic, to some extent, the way in which the human expert operates

Azterketa informatizatu eraginkor baten bila

Tests are a common method for assessing knowledge. In their classic version, they consist of fixed questions created according to the experience of the test developer. In computer adaptive tests (CAT) each person will have different items depending on her/his previous answers. To achieve this behavior, each item has to be calibrated. That is, certain characteristics have to be estimated using specific processes. This paper shows how to create a CAT and the necessary steps for calibrating the items.; Gaur egun testak ohikoak dira, ezagutza ebaluatzeko garaian. Gehienetan, ebaluatzailearen esperientzian eta eskarmentuan oinarrituta hartzen dira azterketarako galdera edo itemak. Test Egokigarri Informatizatu (TEI) batean pertsona bakoitzak item ezberdinak ditu, aurreko erantzunen arabera. Hori lortu ahal izateko, item bakoitza kalibratu egin behar da, hau da, item bakoitzari balio batzuk eman behar zaizkio, prozesu jakin, zehatz bati jarraituz. Artikulu honetan azaltzen da zer egin behar den TEI bat osatzeko eta itemak kalibratzeko