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Online cardiac output estimation during transvalvular left ventricular assistance
• Novel optical pressure sensors on a VAD• Simple cardiovascular system model• Joint parameter/state estimation using an extended Kalman filter• Online total cardiac output estimation with estimation errors in the same range as the accuracy of the gold standard in research for invasive blood flow measurement (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 29, 2016 Category: Bioinformatics Authors: Daniel R üschen, Miriam Rimke, Jonas Gesenhues, Steffen Leonhardt, Marian Walter Source Type: research

Cardiac arrhythmia beat classification using DOST and PSO tuned SVM
• A new method is proposed in this manuscript for the classification of cardiac arrhythmia beats. Algorithms used in this method are Pan-Tompkins algorithm for R-peak detection, discrete orthogonal stockwell transform (DOST) for feature extraction of ECG signals, support vector machines (SVMs) for classification whose parameters are tuned using particle swarm optimization (PSO) technique for automatic cardiac arrhythmia beat classification.• The best performance parameters for the SVM classifier are selected by employing PSO technique to achieve maximum accuracy. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 28, 2016 Category: Bioinformatics Authors: Sandeep Raj, Kailash Chandra Ray, Om Shankar Source Type: research

Improving the text classification using clustering and a novel HMM to reduce the dimensionality
• A dimensionality reduction method based on document content is proposed• The technique utilizes a document clustering to separate data into groups• It introduces a similarity-based document representation based on a Text HMM• The model is tested with the SVM and k-NN classifiers using two medical corpora• Results show the method outperforms other dimensionality reduction approximations (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 26, 2016 Category: Bioinformatics Authors: A. Seara Vieira, L. Borrajo, E.L. Iglesias Source Type: research

Correlation Coefficient based Supervised Locally Linear Embedding for Pulmonary Nodule Recognition
• A correlation coefficient is introduced to adjust the distance metric in the supervised locally linear embedding to ensure more suitable neighbors that could be chosen, and thus to enhance the discriminating power of embedded data.• The method is validated on a clinical lung image database. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 26, 2016 Category: Bioinformatics Authors: Panpan Wu, Kewen Xia, Hengyong Yu Source Type: research

A new computer vision-based approach to aid the diagnosis of parkinson's disease
• To develop a new dataset based on handwritten exams to aid Parkinson's Disease diagnosis;• To propose a new approach to extract features from those exams based on image processing;• To evaluate the features extracted from the dataset over two different drawings: spirals and meanders;• To m ake available the dataset to the scientific community. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 24, 2016 Category: Bioinformatics Authors: Clayton R. Pereira, Danilo R. Pereira, Francisco A. Silva, Jo ão P. Masieiro, Silke A.T. Weber, Christian Hook, João P. Papa Source Type: research

Automatic identification of epileptic seizures from EEG signals using linear programming boosting
• A single lead EEG based automated epilepsy seizure screening method is proposed.• A novel signal processing technique, namely CEEMDAN is employed.• We introduce LPBoost to classify epileptic seizures for the first time.• Efficacy of the method is confirmed by statistical and graphical anal yses.• The performance of the proposed scheme, compared to the existing ones is promising. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 24, 2016 Category: Bioinformatics Authors: Ahnaf Rashik Hassan, Abdulhamit Subasi Source Type: research

Integrating Evolutionary Game Theory into an Agent-Based Model of Ductal Carcinoma in Situ: Role of Gap Junctions in Cancer Progression
• The propagation of signals via gap junctions is modeled by using evolutionary game theory.• Game theory payoffs are considered to be a function of cellular context.• The results show the gap junction communication reduces cancer progression.• The model illustrates the role of gap junctions at the early stage of cancer. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 23, 2016 Category: Bioinformatics Authors: Negin Malekian, Jafar Habibi, Mohammad Hossein Zangooei, Hojjat Aghakhani Source Type: research

The Effect of Particulate Matter Size on Cardiovascular Health in Taipei Basin, Taiwan
• Distributed Lag Non-linear Model (DLNM) was used to explore the risk effect of different particulate matter sizes such as PM10, PM2.5-10, PM2.5.• Only PM2.5 is significantly positively correlated with the number of daily outpatient visits with cardiovascular disease.• To quantify the effect of different PM sizes on CVD and could be the basis of a local, more detailed environmental study. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 23, 2016 Category: Bioinformatics Authors: Hsuan-Chia Yang, Shu-Hao Chang, Richard Lu, Der-Ming Liou Source Type: research

Intraoral radiographs texture analysis for dental implant planning
This study aims to investigate the feasibility of using texture analysis of periapical radiograph images as a tool for dental implant treatment planning. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 22, 2016 Category: Bioinformatics Authors: Mayara B.V. Mundima, Danilo R. Diasa, Ronaldo M. Costa, Cl áudio R. Lelesa, Paulo M. Azevedo-Marques, Rejane F. Ribeiro-Rotta Source Type: research

Predicting intentions of nurses to adopt patient personal health records: a structural equation modeling approach
• Personal health records (PHRs) enhance multidisciplinary communication of providers.• No previous evidence was found on predicting nurses' intentions to adopt patient PHRs.• Few studies have used an extended technology acceptance model to explore medical information technology- related facto rs.• Evidence of how subjective norms influence nurses' attitudes for patient PHRs is provided.• Nurses had positive attitudes of using patient PHRs when it is encouraged by supervisors and colleagues. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 20, 2016 Category: Bioinformatics Authors: Min-Huey Chung, Cheng-Hsun Ho, Hsyien-Chia Wen Source Type: research

Traumatic brain injury in pedestrian –vehicle collisions: convexity and suitability of some functionals used as injury metrics
This study is a comparison of commonly used Injury Metrics for evaluation of Traumatic Brain Injury.• The study includes both an empirical comparison and a mathematical comparison of formal properties.• This study is intended as a guideline to obtain new suitable Injury Metrics.• Some new Injury Metrics are proposed, and evaluated using data of pedestrian-vehicle collision. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 20, 2016 Category: Bioinformatics Authors: D. S ánchez-Molina, C. Arregui-Dalmases, J. Velazquez-Ameijide, M. Angelini, J. Kerrigan, J. Crandall Source Type: research

EEG-based Mild Depressive Detection using Feature Selection Methods and Classifiers
• The combination of feature selection method Greedy-Stepwise (GSW) based on Correlation Features Selection (CFS) and classification algorithm KNN can achieve the optimal performance for mild depression detection.• Fewer EEG channels: FP1, FP2, F3, O2, T3 with linear features may be a good choic e for portable device and auxiliary diagnosis of mild depression.• Classification accuracy above 91% and AUC above 0.950, these results are better than some existing studies. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 17, 2016 Category: Bioinformatics Authors: Xiaowei Li, Bin Hu, Shuting Sun, Hanshu Cai Source Type: research

Supervised discretization can discover risk groups in cancer survival analysis
• TNM staging system of malignant tumors, initially developed in 1950 and with their successive amendments, still remains the main prognostic classification in many adult cancers in order to predict treatment outcomes.• Supervised algortihms from machine learning are performed to find different patient groups in the treatment of breast cancer disease.• The new approaches found novel groups risks that improve prediction results of breast cancer relapse. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 17, 2016 Category: Bioinformatics Authors: Iv án Gómez, Nuria Ribelles, Leonardo Franco, Emilio Alba, José M. Jerez Source Type: research

GPU accelerated dynamic respiratory motion model correction for MRI-guided cardiac interventions
• The highlight of this study is that a GPU accelerated dynamic motion model framework is described.• The proposed method is able to correct for respiratory motion in realtime, and be adaptive to changes in breathing pattern.• This methodology can be used to improve the accuracy of MRI guided cardiovascular interventions. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 17, 2016 Category: Bioinformatics Authors: Robert Xu, Graham A. Wright Source Type: research

Characterization of EEG patterns in brain-injured subjects and controls after a snoezelen ® intervention
• Snoezelen elicits changes in brain-injured subjects and controls' EEG activity.• Our results support the notion that Snoezelen affects central nervous system.• Snoezelen participants are more relaxed after the stimulation.• Cognitive deficits of brain-injured subjects may diminish the bene fits of Snoezelen.• Our study could contribute to design personalized non-pharmacological interventions. (Source: Computer Methods and Programs in Biomedicine)
Source: Computer Methods and Programs in Biomedicine - August 15, 2016 Category: Bioinformatics Authors: Carlos G ómez, Jesús Poza, María T. Gutiérrez, Esther Prada, Nuria Mendoza, Roberto Hornero Source Type: research