Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 1, 2014 Category: Bioinformatics Source Type: research

Automatic classification of epilepsy types using ontology-based and genetics-based machine learning
Conclusion: Our results demonstrate that the developed methods form important ingredients for realizing a fully automatic classification of epilepsy types and can contribute to the definition of signs that are most important for the classification. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 17, 2014 Category: Bioinformatics Authors: Yohannes Kassahun, Roberta Perrone, Elena De Momi, Elmar Berghöfer, Laura Tassi, Maria Paola Canevini, Roberto Spreafico, Giancarlo Ferrigno, Frank Kirchner Tags: Research Articles Source Type: research

A methodology for the characterization and diagnosis of cognitive impairments—Application to specific language impairment
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 12, 2014 Category: Bioinformatics Authors: Jesús Oliva, J. Ignacio Serrano, M. Dolores del Castillo, Ángel Iglesias Tags: Research Articles Source Type: research

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods
Conclusions: Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both local and global learning strategies, able to exploit the overall topology of the network. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 10, 2014 Category: Bioinformatics Authors: Giorgio Valentini, Alberto Paccanaro, Horacio Caniza, Alfonso E. Romero, Matteo Re Tags: Research Articles Source Type: research

Sepsis mortality prediction with the Quotient Basis Kernel
Conclusion: Several scoring systems for patients with sepsis have been introduced and developed over the last 30 years. They allow for the assessment of the severity of disease and provide an estimate of in-hospital mortality. Physiology-based scoring systems are applied to critically ill patients and have a number of advantages over diagnosis-based systems. Severity score systems are often used to stratify critically ill patients for possible inclusion in clinical trials. In this paper, we present an effective algorithm that combines both scoring methodologies for the assessment of death in patients with sepsis that can b...
Source: Artificial Intelligence in Medicine - April 10, 2014 Category: Bioinformatics Authors: Vicent J. Ribas Ripoll, Alfredo Vellido, Enrique Romero, Juan Carlos Ruiz-Rodríguez Tags: Research Articles Source Type: research

De-identification of health records using : Effectiveness and robustness across datasets
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 3, 2014 Category: Bioinformatics Authors: Guido Zuccon, Daniel Kotzur, Anthony Nguyen, Anton Bergheim Tags: Special issue Articles Source Type: research

Interval type-2 fuzzy neural network controller for a multivariable anesthesia system based on a hardware-in-the-loop simulation
Conclusion: The IT2FNN controller is superior to the T1FNN controller for the handling of uncertain information due to the structure of type-2 fuzzy logic systems (FLSs), which are able to model and minimize the numerical and linguistic uncertainties associated with the inputs and outputs of the FLSs. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 3, 2014 Category: Bioinformatics Authors: Ahmad M. El-Nagar, Mohammad El-Bardini Tags: Research Articles Source Type: research

Adaptation of machine translation for multilingual information retrieval in the medical domain
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 28, 2014 Category: Bioinformatics Authors: Pavel Pecina, Ondřej Dušek, Lorraine Goeuriot, Jan Hajič, Jaroslava Hlaváčová, Gareth J.F. Jones, Liadh Kelly, Johannes Leveling, David Mareček, Michal Novák, Martin Popel, Rudolf Rosa, Aleš Tamchyna, Zdeňka Urešová Tags: Special issue Articles Source Type: research

Statistical parsing of varieties of clinical Finnish
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 28, 2014 Category: Bioinformatics Authors: Veronika Laippala, Timo Viljanen, Antti Airola, Jenna Kanerva, Sanna Salanterä, Tapio Salakoski, Filip Ginter Tags: Special issue Articles Source Type: research

Unsupervised tissue segmentation from dynamic contrast-enhanced magnetic resonance imaging
Conclusions: The sparse representation of DCE MRI signals obtained by means of adaptive dictionary learning techniques appears to be well-suited for unsupervised tissue segmentation and applicable to different clinical contexts with little effort. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 24, 2014 Category: Bioinformatics Authors: Gabriele Chiusano, Alessandra Staglianò, Curzio Basso, Alessandro Verri Tags: Research Articles Source Type: research

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 20, 2014 Category: Bioinformatics Authors: Giorgio Valentini, Alberto Paccanaro, Horacio Caniza, Alfonso E. Romero, Matteo Re Tags: Research Articles Source Type: research

Vicinal support vector classifier using supervised kernel-based clustering
Conclusion: Incorporating a supervised clustering algorithm into the SVM technique leads to a sparse but effective solution, while making the proposed VSVC adaptive to different probability distributions of the training data. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 17, 2014 Category: Bioinformatics Authors: Xulei Yang, Aize Cao, Qing Song, Gerald Schaefer, Yi Su Tags: Research Articles Source Type: research

Automatic classification of epilepsy types using ontology-based and genetics-based machine learning
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 14, 2014 Category: Bioinformatics Authors: Yohannes Kassahun, Roberta Perrone, Elena De Momi, Elmar Berghöfer, Laura Tassi, Maria Paola Canevini, Roberto Spreafico, Giancarlo Ferrigno, Frank Kirchner Tags: Research Articles Source Type: research

Multi-test decision tree and its application to microarray data classification
Conclusion: This paper introduces a new type of decision tree which is more suitable for solving biological problems. MTDTs are relatively easy to analyze and much more powerful in modeling high dimensional microarray data than their popular counterparts. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 14, 2014 Category: Bioinformatics Authors: Marcin Czajkowski, Marek Grześ, Marek Kretowski Tags: Research Articles Source Type: research

Twitter mining for fine-grained syndromic surveillance
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 12, 2014 Category: Bioinformatics Authors: Paola Velardi, Giovanni Stilo, Alberto E. Tozzi, Francesco Gesualdo Tags: Special issue Articles Source Type: research

Statistical parsing of varieties of clinical Finnish
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 5, 2014 Category: Bioinformatics Authors: Veronika Laippala, Timo Viljanen, Antti Airola, Jenna Kanerva, Sanna Salanterä, Tapio Salakoski, Filip Ginter Source Type: research

Intensity-based image registration using scatter search
We present a novel intensity-based algorithm for medical image registration (IR).Methods and materials: The IR problem is formulated as a continuous optimization task, and our work focuses on the development of the optimization component. Our method is designed over an advanced scatter search template, and it uses a combination of restart and dynamic boundary mechanisms integrated within a multi-resolution strategy.Results: The experimental validation is performed over two datasets of human brain magnetic resonance imaging. The algorithm is evaluated in both a stand-alone registration application and an atlas-based segment...
Source: Artificial Intelligence in Medicine - March 4, 2014 Category: Bioinformatics Authors: Andrea Valsecchi, Sergio Damas, José Santamaría, Linda Marrakchi-Kacem Tags: Research Articles Source Type: research

Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 1, 2014 Category: Bioinformatics Source Type: research

Cue-based assertion classification for Swedish clinical text—Developing a lexicon for pyConTextSwe
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 20, 2014 Category: Bioinformatics Authors: Sumithra Velupillai, Maria Skeppstedt, Maria Kvist, Danielle Mowery, Brian E. Chapman, Hercules Dalianis, Wendy W. Chapman Tags: Special issue Articles Source Type: research

Twitter mining for fine-grained syndromic surveillance
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 17, 2014 Category: Bioinformatics Authors: Paola Velardi, Giovanni Stilo, Alberto E. Tozzi, Francesco Gesualdo Source Type: research

Temporal abstraction and temporal Bayesian networks in clinical domains: A survey
Conclusion: The main conclusion transpiring from this review is that techniques/methods from these two areas, that so far are being largely used independently of each other in clinical domains, could be effectively integrated in the context of medical decision-support systems. The anticipated key benefits of the perceived integration are: (a) during problem solving, the reasoning can be directed at different levels of temporal and/or conceptual abstractions since the nodes of the TBNs can be complex entities, temporally and structurally and (b) during model building, knowledge generated in the form of basic and/or complex ...
Source: Artificial Intelligence in Medicine - February 13, 2014 Category: Bioinformatics Authors: Kalia Orphanou, Athena Stassopoulou, Elpida Keravnou Tags: Research Articles Source Type: research

Multi-objective evolutionary algorithms for fuzzy classification in survival prediction
Conclusions: Our proposal improves the accuracy and interpretability of the classifiers, compared with other non-evolutionary techniques. We also conclude that ENORA outperforms niched pre-selection and NSGA-II algorithms. Moreover, given that our multi-objective evolutionary methodology is non-combinational based on real parameter optimization, the time cost is significantly reduced compared with other evolutionary approaches existing in literature based on combinational optimization. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 12, 2014 Category: Bioinformatics Authors: Fernando Jiménez, Gracia Sánchez, José M. Juárez Tags: Research Articles Source Type: research

Adaptation of machine translation for multilingual information retrieval in the medical domain
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 6, 2014 Category: Bioinformatics Authors: Pavel Pecina, Ondřej Dušek, Lorraine Goeuriot, Jan Hajič, Jaroslava Hlaváčová, Gareth J.F. Jones, Liadh Kelly, Johannes Leveling, David Mareček, Michal Novák, Martin Popel, Rudolf Rosa, Aleš Tamchyna, Zdeňka Urešová Source Type: research

Fuzzy logic-based diagnostic algorithm for implantable cardioverter defibrillators
Conclusion: The paper presents a fuzzy logic-based control algorithm for ICD. Its main advantages are: simplicity and ability to decrease the rate of occurrence of inappropriate therapies. The algorithm can work in real time (i.e. update the diagnosis after every RR-interval) with very limited computational resources. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 5, 2014 Category: Bioinformatics Authors: András Bárdossy, Aleksandra Blinowska, Wieslaw Kuzmicz, Jacky Ollitrault, Michał Lewandowski, Andrzej Przybylski, Zbigniew Jaworski Tags: Research Articles Source Type: research

Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 1, 2014 Category: Bioinformatics Source Type: research

Supervised machine learning-based classification of oral malodor based on the microbiota in saliva samples
Conclusions: Using T-RF proportions and frequencies, models to classify the presence of methyl mercaptan, a volatile sulfur-containing compound that causes oral malodor, were developed. SVM classifiers successfully classified the presence of methyl mercaptan with high specificity, and this classification is expected to be useful for screening saliva for oral malodor before visits to specialist clinics. Classification by a SVM and an ANN does not require the identification of the oral microbiota species responsible for the malodor, and the ANN also does not require the proportions of T-RFs. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 16, 2014 Category: Bioinformatics Authors: Yoshio Nakano, Toru Takeshita, Noriaki Kamio, Susumu Shiota, Yukie Shibata, Nao Suzuki, Masahiro Yoneda, Takao Hirofuji, Yoshihisa Yamashita Tags: Research Articles Source Type: research

Using a multi-agent system approach for microaneurysm detection in fundus images
Conclusions: We achieved competitive results, primarily in detecting microaneurysms close to vessels, compared to more conventional algorithms. Despite these results not being optimum, they are encouraging and reveal that some improvements may be made. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 13, 2014 Category: Bioinformatics Authors: Carla Pereira, Diana Veiga, Jason Mahdjoub, Zahia Guessoum, Luís Gonçalves, Manuel Ferreira, João Monteiro Tags: Research Articles Source Type: research

Employing heat maps to mine associations in structured routine care data
Conclusion: We could demonstrate that heat maps of measures of association are effective for the visualization of patterns in routine care EMRs. The adjustable method for the assignment of attributes to image dimensions permits a balance between the display of ample information and a favorable level of graphical complexity. The scope of the search can be adapted by the use of pre-existing assumptions about plausible effects to select exposure and outcome attributes. Thus, the proposed method promises to simplify the detection of undiscovered causal effects within routine EMR data. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 6, 2014 Category: Bioinformatics Authors: Dennis Toddenroth, Thomas Ganslandt, Ixchel Castellanos, Hans-Ulrich Prokosch, Thomas Bürkle Tags: Research Articles Source Type: research

Fuzzy model identification of dengue epidemic in Colombia based on multiresolution analysis
Conclusions: The fuzzy model identification technique based on multiresolution analysis produced a proper representation of dengue and severe dengue cases for Colombia despite the complexity and uncertainty that characterize this biological system. Additionally, the obtained models generate plausible predictions that can be used by surveillance authorities to support decision-making oriented to designing and developing control strategies. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 2, 2014 Category: Bioinformatics Authors: Claudia Torres, Samier Barguil, Miguel Melgarejo, Andrés Olarte Tags: Research Articles Source Type: research

Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - January 1, 2014 Category: Bioinformatics Source Type: research

Performance of a dermoscopy-based computer vision system for the diagnosis of pigmented skin lesions compared with visual evaluation by experienced dermatologists
Conclusion: We show that simple statistical classifiers can be trained to provide a recommendation on whether a pigmented skin lesion requires biopsy to exclude skin cancer with a performance that is comparable to and exceeds that of experienced dermatologists. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 31, 2013 Category: Bioinformatics Authors: Maciel Zortea, Thomas R. Schopf, Kevin Thon, Marc Geilhufe, Kristian Hindberg, Herbert Kirchesch, Kajsa Møllersen, Jörn Schulz, Stein Olav Skrøvseth, Fred Godtliebsen Tags: Research Articles Source Type: research

Improving predictive models of glaucoma severity by incorporating quality indicators
Abstract: Objective: In this paper we present an evaluation of the role of reliability indicators in glaucoma severity prediction. In particular, we investigate whether it is possible to extract useful information from tests that would be normally discarded because they are considered unreliable.Methods: We set up a predictive modelling framework to predict glaucoma severity from visual field (VF) tests sensitivities in different reliability scenarios. Three quality indicators were considered in this study: false positives rate, false negatives rate and fixation losses. Glaucoma severity was evaluated by considering a 3-le...
Source: Artificial Intelligence in Medicine - December 31, 2013 Category: Bioinformatics Authors: Lucia Sacchi, Allan Tucker, Steve Counsell, David Garway-Heath, Stephen Swift Tags: Research Articles Source Type: research

Detecting rare events using extreme value statistics applied to epileptic convulsions in children
Conclusions: A person-dependent epileptic seizure detection method has been designed that requires little human interaction. In contrast to traditional machine learning approaches, the imbalance of the dataset does not cause substantial difficulties. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 27, 2013 Category: Bioinformatics Authors: Stijn Luca, Peter Karsmakers, Kris Cuppens, Tom Croonenborghs, Anouk Van de Vel, Berten Ceulemans, Lieven Lagae, Sabine Van Huffel, Bart Vanrumste Tags: Research Articles Source Type: research

Knowledge discovery in clinical decision support systems for pain management: A systematic review
Conclusions: Computer technologies that have been applied in CDSSs are important but not determinant in improving the systems’ accuracy and the clinical practice, as evidenced by the moderate correlation among the studies. However, these systems play an important role in the design of computerised systems oriented to a patient's symptoms as is required for pain management. Several limitations related to CDSSs were observed: the lack of integration with mobile devices, the reduced use of web-based interfaces, and scarce capabilities for data to be inserted by patients. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 26, 2013 Category: Bioinformatics Authors: Nuno Pombo, Pedro Araújo, Joaquim Viana Tags: Survey Paper Source Type: research

Classification of small lesions on dynamic breast MRI: Integrating dimension reduction and out-of-sample extension into CADx methodology
Conclusions: The results reported in this study with the proposed CADx methodology present a significant improvement over previous results reported with such small lesions on dynamic breast MRI. In particular, non-linear algorithms for dimension reduction exhibited better classification performance than linear approaches, when integrated into our CADx methodology. We also note that while dimension reduction techniques may not necessarily provide an improvement in classification performance over feature selection, they do allow for a higher degree of feature compaction. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 18, 2013 Category: Bioinformatics Authors: Mahesh B. Nagarajan, Markus B. Huber, Thomas Schlossbauer, Gerda Leinsinger, Andrzej Krol, Axel Wismüller Tags: Research Articles Source Type: research

A computer vision framework for finger-tapping evaluation in Parkinson's disease
Conclusion: The work supports the feasibility of the approach, which is presumed suitable for PD monitoring in the home environment. The system offers advantages over other technologies (e.g. magnetic sensors, accelerometers, etc.) previously developed for objective assessment of tapping symptoms. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 12, 2013 Category: Bioinformatics Authors: Taha Khan, Dag Nyholm, Jerker Westin, Mark Dougherty Tags: Research Articles Source Type: research

Automatic detection of solitary lung nodules using quality threshold clustering, genetic algorithm and diversity index
Conclusion: Lung cancer presents the highest mortality rate in addition to one of the smallest survival rates after diagnosis. An early diagnosis considerably increases the survival chance of patients. The methodology proposed herein contributes to this diagnosis by being a useful tool for specialists who are attempting to detect nodules. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 11, 2013 Category: Bioinformatics Authors: Antonio Oseas de Carvalho Filho, Wener Borges de Sampaio, Aristófanes Corrêa Silva, Anselmo Cardoso de Paiva, Rodolfo Acatauassú Nunes, Marcelo Gattass Tags: Research Articles Source Type: research

Multi-agent model of hepatitis C virus infection
Conclusions: The proposed method has many advantages in comparison to the currently used model types and can be used successfully for analyzing HCV infection. With almost no modifications, it can also be used for other types of viral infections. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 4, 2013 Category: Bioinformatics Authors: Szymon Wasik, Paulina Jackowiak, Marek Figlerowicz, Jacek Blazewicz Tags: Research Articles Source Type: research

White box radial basis function classifiers with component selection for clinical prediction models
Conclusions: This work proposes a new method to obtain flexible and sparse risk prediction models. The proposed method performs as well as a support vector machine using the standard RBF kernel, but has the additional advantage that the resulting model can be interpreted by experts in the application domain. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 20, 2013 Category: Bioinformatics Authors: Vanya Van Belle, Paulo Lisboa Tags: Research Articles Source Type: research

Image partitioning and illumination in image-based pose detection for teleoperated flexible endoscopes
Conclusions: This work demonstrates that both WLI and NBI, combined with feature partitioning based on the anatomy of the colon, provide valid mechanisms for endoscopic camera pose estimation via image stream. Illumination provided by WLI and NBI produce ANNs with similar performance which are comparable to that of a state-of-the-art magnetic tracker. However, NBI produces features that are stronger than WLI, which enables more robust feature tracking, and better performance of the ANN in terms of accuracy. Thus, NBI with lumen-centered partitioning resulted the best approach among the different variations tested for visio...
Source: Artificial Intelligence in Medicine - November 4, 2013 Category: Bioinformatics Authors: Charreau S. Bell, Keith L. Obstein, Pietro Valdastri Tags: Research Articles Source Type: research

Describing disease processes using a probabilistic logic of qualitative time
Conclusion: The combination of qualitative time and probabilistic logic offers a useful framework for modelling knowledge and data to describe disease processes in clinical medicine. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 4, 2013 Category: Bioinformatics Authors: Maarten van der Heijden, Peter J.F. Lucas Tags: Research Articles Source Type: research

Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 1, 2013 Category: Bioinformatics Source Type: research

Data structure-guided development of electrocardiographic signal characterization and classification
Conclusions: It was shown that granular representation of electrocardiographic signals is essential to data analysis and classification by providing a means to reveal and characterize the data structure and by providing prerequisites to construct pattern classifiers. The study also shows that fuzzy clusters deliver important structural information about the data that could be further quantified by looking into the content of clusters. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 28, 2013 Category: Bioinformatics Authors: Adam Gacek Tags: Research Articles Source Type: research

Comparing the accuracy of syndrome surveillance systems in detecting influenza-like illness: GUARDIAN vs. RODS vs. electronic medical record reports
Abstract: Background: A highly sensitive real-time syndrome surveillance system is critical to detect, monitor, and control infectious disease outbreaks, such as influenza. Direct comparisons of diagnostic accuracy of various surveillance systems are scarce.Objective: To statistically compare sensitivity and specificity of multiple proprietary and open source syndrome surveillance systems to detect influenza-like illness (ILI).Methods: A retrospective, cross-sectional study was conducted utilizing data from 1122 patients seen during November 1–7, 2009 in the emergency department of a single urban academic medical cen...
Source: Artificial Intelligence in Medicine - October 25, 2013 Category: Bioinformatics Authors: Julio C. Silva, Shital C. Shah, Dino P. Rumoro, Jamil D. Bayram, Marilyn M. Hallock, Gillian S. Gibbs, Michael J. Waddell Tags: Research Articles Source Type: research

Transferring brain–computer interfaces beyond the laboratory: Successful application control for motor-disabled users
Conclusion: The points raised in this paper are very widely applicable and we anticipate that they might be faced similarly by other groups, if they move on to bringing the BCI technology to the end-user, to home environments and towards application prototype control. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 11, 2013 Category: Bioinformatics Authors: Robert Leeb, Serafeim Perdikis, Luca Tonin, Andrea Biasiucci, Michele Tavella, Marco Creatura, Alberto Molina, Abdul Al-Khodairy, Tom Carlson, José d.R. Millán Tags: Special Issue Articles Source Type: research

Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 1, 2013 Category: Bioinformatics Source Type: research

Comparative analysis of a-priori and a-posteriori dietary patterns using state-of-the-art classification algorithms: A case/case-control study
Conclusion: Both dietary pattern approaches achieved equivalent classification accuracy over most classification algorithms. The choice, therefore, depends on the application at hand. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Christina-Maria Kastorini, George Papadakis, Haralampos J. Milionis, Kallirroi Kalantzi, Paolo-Emilio Puddu, Vassilios Nikolaou, Konstantinos N. Vemmos, John A. Goudevenos, Demosthenes B. Panagiotakos Tags: Research Articles Source Type: research

Brain–computer interface controlled gaming: Evaluation of usability by severely motor restricted end-users
Conclusion: Effectiveness and efficiency are lower as compared to applications using the event-related potential as input channel. Nevertheless, the SMR-BCI application was satisfactorily accepted by the end-users and two of four could imagine using the BCI application in their daily life. Thus, despite moderate effectiveness and efficiency BCIs might be an option when controlling an application for entertainment. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Elisa Mira Holz, Johannes Höhne, Pit Staiger-Sälzer, Michael Tangermann, Andrea Kübler Tags: Special Issue Articles Source Type: research