Brain Painting: Usability testing according to the user-centered design in end users with severe motor paralysis
Conclusion: The P300 Brain Painting application can be operated with high effectiveness and efficiency. End users with severe motor paralysis would like to use the application in daily life. User-friendliness, specifically ease of use, is a mandatory necessity when bringing BCI to end users. Early and active involvement of users and iterative user-centered evaluation enable developers to work toward this goal. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Claudia Zickler, Sebastian Halder, Sonja C. Kleih, Cornelia Herbert, Andrea Kübler Tags: Special Issue Articles Source Type: research

The auditory P300-based single-switch brain–computer interface: Paradigm transition from healthy subjects to minimally conscious patients
Conclusion: This work shows the transition of a paradigm from healthy subjects to MCS patients. Promising results with healthy subjects are, however, no guarantee of good results with patients. Therefore, more investigations are required before any definite conclusions about the usability of this paradigm for MCS patients can be drawn. Nevertheless, this paradigm might offer an opportunity to support bedside clinical assessment of MCS patients and eventually, to provide them with a means of communication. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Christoph Pokorny, Daniela S. Klobassa, Gerald Pichler, Helena Erlbeck, Ruben G.L. Real, Andrea Kübler, Damien Lesenfants, Dina Habbal, Quentin Noirhomme, Monica Risetti, Donatella Mattia, Gernot R. Müller-Putz Tags: Special Issue Articles Source Type: research

User-centered design in brain–computer interfaces—A case study
Conclusion: The user's performance on the first BCI paradigm would typically have excluded her from further ERP-based BCI studies. However, this study clearly shows that, with the numerous paradigms now at our disposal, the pursuit for a functioning BCI system should not be stopped after an initial failed attempt. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Martijn Schreuder, Angela Riccio, Monica Risetti, Sven Dähne, Andrew Ramsay, John Williamson, Donatella Mattia, Michael Tangermann Tags: Special Issue Articles Source Type: research

Asynchronous gaze-independent event-related potential-based brain–computer interface
In this study a gaze independent event related potential (ERP)-based brain computer interface (BCI) for communication purpose was combined with an asynchronous classifier endowed with dynamical stopping feature. The aim was to evaluate if and how the performance of such asynchronous system could be negatively affected in terms of communication efficiency and robustness to false positives during the intentional no-control state.Material and methods: The proposed system was validated with the participation of 9 healthy subjects. A comparison was performed between asynchronous and synchronous classification technique outputs ...
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Fabio Aloise, Pietro Aricò, Francesca Schettini, Serenella Salinari, Donatella Mattia, Febo Cincotti Tags: Special Issue Articles Source Type: research

Facing the challenge: Bringing brain–computer interfaces to end-users
Brain–computer interfaces (BCIs) are devices that translate changes of the neurophysiological activity of the brain into control commands for an application. The research summarized in this Special Issue was presented at the 3rd workshop of the large scale integrating project TOBI (TOols for Brain–computer Interaction) funded by the European ICT programme (FP7). Bringing BCIs to end-users was the leading topic of the TOBI workshop. More than 100 researchers presented their work with the focus on involving people with disabilities with real need for assistive technology (AT), and possibly BCI. In the field of BC...
Source: Artificial Intelligence in Medicine - September 30, 2013 Category: Bioinformatics Authors: Andrea Kübler, Donatella Mattia, Rüdiger Rupp, Michael Tangermann Tags: Guest Editorial Source Type: research

Hybrid brain–computer interfaces and hybrid neuroprostheses for restoration of upper limb functions in individuals with high-level spinal cord injury
Conclusion: This proof-of-concept study has demonstrated that with the support of hybrid FES systems consisting of FES and a semiactive orthosis, restoring hand, finger and elbow function is possible in a tetraplegic end-user. Remarkably, even after one year of training and 415 MI-BCI runs, the end user's average BCI performance remained at about 70%. This supports the view that in high-level tetraplegic subjects, an initially moderate BCI performance cannot be improved by extensive training. However, this aspect has to be validated in future studies with a larger population. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 23, 2013 Category: Bioinformatics Authors: Martin Rohm, Matthias Schneiders, Constantin Müller, Alex Kreilinger, Vera Kaiser, Gernot R. Müller-Putz, Rüdiger Rupp Tags: Special Issue Articles Source Type: research

Phased searching with NEAT in a Time-Scaled Framework: Experiments on a computer-aided detection system for lung nodules
Abstract: Objective: In the field of computer-aided detection (CAD) systems for lung nodules in computed tomography (CT) scans, many image features are presented and many artificial neural network (ANN) classifiers with various structural topologies are analyzed; frequently, the classifier topologies are selected by trial-and-error experiments. To avoid these trial and error approaches, we present a novel classifier that evolves ANNs using genetic algorithms, called “Phased Searching with NEAT in a Time or Generation-Scaled Framework”, integrating feature selection with the classification task.Methods and mater...
Source: Artificial Intelligence in Medicine - September 12, 2013 Category: Bioinformatics Authors: Maxine Tan, Rudi Deklerck, Jan Cornelis, Bart Jansen Tags: Research Articles Source Type: research

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

Semantic conditioning of salivary pH for communication
Conclusion: Improvements in the paradigm are necessary before testing it with the critical target population of patients to prove its profit for basic yes/no communication in case no other reliable means of communication could be preserved. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 26, 2013 Category: Bioinformatics Authors: Carolin A. Ruf, Daniele De Massari, Franziska Wagner-Podmaniczky, Tamara Matuz, Niels Birbaumer Tags: Special Issue Articles Source Type: research

Clinical decision support systems: Need for evidence, need for evaluation
Modern health care is unthinkable without the progress in theory and practice of health information systems . Health informatics (alias Health IT, or HIT) in general has been shown to have the potential for positive impact on quality and efficiency of patient care . On the other side, experience shows that these benefits are not self-evident; they can only be reached when Health IT is carefully designed, implemented, and managed . Failures in this respect can lead to ill-functioning or user-unfriendly technology that does not understand and is not well integrated into the clinical workflow and is therefore not accepted by ...
Source: Artificial Intelligence in Medicine - July 1, 2013 Category: Bioinformatics Authors: Elske Ammenwerth, Pirkko Nykänen, Michael Rigby, Nicolette de Keizer Tags: Guest Editorial Source Type: research

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

A quantifier-based fuzzy classification system for breast cancer patients
Conclusion: The fuzzy algorithm provides a simple to interpret, linguistic rule set which classifies over 95% of breast cancer patients into one of seven clinical groups. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 19, 2013 Category: Bioinformatics Authors: Daniele Soria, Jonathan M. Garibaldi, Andrew R. Green, Desmond G. Powe, Christopher C. Nolan, Christophe Lemetre, Graham R. Ball, Ian O. Ellis Tags: Research Articles Source Type: research

An approach for Ewing test selection to support the clinical assessment of cardiac autonomic neuropathy
Conclusions: The outcomes obtained can be used to determine the optimal sequences of tests for each individual cost-function by following the ODPF procedure. The results show that the best single Ewing test for diagnosing CAN is the deep breathing heart rate variation test. Optimal sequences found for the cost-function equal to the number of tests guarantee that the best accuracy is achieved after any number of tests and provide an improvement in comparison with the previous ordering of tests or a random sequence. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 14, 2013 Category: Bioinformatics Authors: Andrew Stranieri, Jemal Abawajy, Andrei Kelarev, Shamsul Huda, Morshed Chowdhury, Herbert F. Jelinek Tags: Research Articles Source Type: research

Computational intelligence for the Balanced Scorecard: Studying performance trends of hemodialysis clinics
Conclusion: These results highlight the ability of the proposed methods to extract insights about performance trends that cannot be easily extrapolated using standard analyses and that are valuable in directing management strategies within a continuous quality improvement policy. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 13, 2013 Category: Bioinformatics Authors: Isabella Cattinelli, Elena Bolzoni, Milena Chermisi, Francesco Bellocchio, Carlo Barbieri, Flavio Mari, Claudia Amato, Marcus Menzer, Andrea Stopper, Emanuele Gatti Tags: Research Articles Source Type: research

Physicians’ responses to clinical decision support on an intensive care unit—Comparison of four different alerting methods
Conclusion: The alert presentation method used for CDSSs is crucial for the compliance with alerts for the clinical rules and, consequently, for the efficacy of these systems. Active alerts such as pop-ups and pharmacy intervention were more effective than passive alerts, which do not automatically appear within the clinical workflow. In this pilot study, ICU clinicians also preferred pharmacy intervention and pop-up alerts. More research is required to expand these results to other departments and other hospitals, as well as to other types of CDSSs and different alert presentation methods. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 10, 2013 Category: Bioinformatics Authors: Anne-Marie J. Scheepers-Hoeks, Rene J. Grouls, Cees Neef, Eric W. Ackerman, Erik H. Korsten Tags: Special Issue Articles Source Type: research

Safety and usability evaluation of a web-based insulin self-titration system for patients with type 2 diabetes mellitus
Conclusion: T2DM patients with no prior experience with the web-based self-management system were capable of consulting the system without encountering significant usability problems. Furthermore, the large majority of PANDIT advice were considered clinically safe according to the expert panel. One advice was considered unsafe. This could however easily be corrected by implementing a small modification to the system's knowledge base. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 3, 2013 Category: Bioinformatics Authors: Airin C.R. Simon, Frits Holleman, Wouter T. Gude, Joost B.L. Hoekstra, Linda W. Peute, Monique W.M. Jaspers, Niels Peek Tags: Special Issue Articles Source Type: research

Subpopulation-specific confidence designation for more informative biomedical classification
Conclusion: The classification accuracy increases as the designated confidence increases. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 3, 2013 Category: Bioinformatics Authors: Chuanlei Zhang, Ralph L. Kodell Tags: Research Articles Source Type: research

Homer Richards Warner, 1922–2012
Homer, the ancient Greek poet (8th or 7th century BC) was the creator of the Iliad, an epic poem of dactylic hexameters that tells us the history of the Trojan, and also – as a kind of sequel – the Odyssey that tells us about the hero Odysseus’ journey home after the fall of Troy in dactylic hexameters. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 3, 2013 Category: Bioinformatics Authors: Rudolf Seising Source Type: research

Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach
Conclusion: Quantitative results are discussed from a medical point of view, reflecting a clear translation to the clinical manifestations of PD. Moreover, results include a brief panel of non-motor symptoms that could help clinical practitioners to identify patients who are at different stages of the disease from a limited set of symptoms, such as hallucinations, fainting, inability to control body sphincters or believing in unlikely facts. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 28, 2013 Category: Bioinformatics Authors: Rubén Armañanzas, Concha Bielza, Kallol Ray Chaudhuri, Pablo Martinez-Martin, Pedro Larrañaga Tags: Research Articles Source Type: research

Editorial Board
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 22, 2013 Category: Bioinformatics Source Type: research

From an expert-driven paper guideline to a user-centred decision support system: A usability comparison study
Conclusion: Analysis showed that usability problems experienced by healthcare practitioners when using a paper-based guideline could be overcome by implementing the guideline in a user-centred CDSS design. Although different types of usability problems were experienced with the prototype CDSS, they did not inhibit effective and efficient performance of tasks in the system. The usability problem analysis of the paper-based guideline effectively supported comparison of usability problems found in the two information retrieval systems and it supported the UCD of the CDSS. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 17, 2013 Category: Bioinformatics Authors: Ellen Kilsdonk, Linda W. Peute, Rinke J. Riezebos, Leontien C. Kremer, Monique W.M. Jaspers Tags: Special Issue Articles Source Type: research

Evaluation of rule effectiveness and positive predictive value of clinical rules in a Dutch clinical decision support system in daily hospital pharmacy practice
Conclusion: ADEAS can effectively be used in daily hospital pharmacy practice to select patients at risk of potential ADEs, but to increase the benefits for routine patient care and to increase efficiency, both rule effectiveness and PPV for the clinical rules should be improved. Furthermore, clinical rules would have to be refined and restricted to those categories that are potentially most promising for clinical relevance, i.e. “clinical rules with a combination of pharmacy and laboratory data” and “clinical rules based upon the basic CPOE medication safety alerts fine-tuned to high risk patients”...
Source: Artificial Intelligence in Medicine - May 9, 2013 Category: Bioinformatics Authors: Mirjam K. Rommers, Juliëtte Zwaveling, Henk-Jan Guchelaar, Irene M. Teepe-Twiss Tags: Special Issue Articles Source Type: research

Discovering metric temporal constraint networks on temporal databases
Conclusions: A temporal data mining technique for discovering frequent temporal patterns in collections of time-stamped event sequences is presented. The resulting patterns describe different and distinguishable temporal arrangements among sets of event types in terms of repetitive appearance and similarity of the dispositions between the same events. ASTPminer allows users to participate in the mining process by introducing domain knowledge in the form of a temporal pattern using the STP formalism. This knowledge constrains the search to patterns consistent with the provided pattern and improves the performance of the pro...
Source: Artificial Intelligence in Medicine - May 8, 2013 Category: Bioinformatics Authors: Miguel R. Álvarez, Paulo Félix, Purificación Cariñena Tags: Research Articles Source Type: research

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

A preclustering-based ensemble learning technique for acute appendicitis diagnoses
Conclusion: The PEL technique is capable of addressing imbalanced sample learning associated with acute appendicitis diagnosis. Our evaluation results suggest PEL is less biased toward a positive or negative class than the investigated benchmark techniques. In addition, our results indicate the overall effectiveness of the proposed technique, compared with prevalent scoring systems or salient classification techniques that follow the resampling approach. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 25, 2013 Category: Bioinformatics Authors: Yen-Hsien Lee, Paul Jen-Hwa Hu, Tsang-Hsiang Cheng, Te-Chia Huang, Wei-Yao Chuang Tags: Research Articles Source Type: research

The readiness of SNOMED problem list concepts for meaningful use of electronic health records
Conclusion: PL concepts suffer from the same issues as general SCT concepts, although to a slightly lesser extent, and do require further QA efforts to promote meaningful use of EHRs. To support such efforts, a structural indicator is shown to effectively ferret out potentially problematic concepts where those QA efforts should be focused. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 22, 2013 Category: Bioinformatics Authors: Ankur Agrawal, Zhe He, Yehoshua Perl, Duo Wei, Michael Halper, Gai Elhanan, Yan Chen Tags: Research Articles Source Type: research

Artificial metaplasticity prediction model for cognitive rehabilitation outcome in acquired brain injury patients
Conclusions: The proposed prediction model presented in this study allows to increase the knowledge about the contributing factors of an ABI patient recovery and to estimate treatment efficacy in individual patients. The ability to predict treatment outcomes may provide new insights toward improving effectiveness and creating personalized therapeutic interventions based on clinical evidence. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 15, 2013 Category: Bioinformatics Authors: Alexis Marcano-Cedeño, Paloma Chausa, Alejandro García, César Cáceres, Josep M. Tormos, Enrique J. Gómez Tags: Research Articles Source Type: research

Training artificial neural networks directly on the concordance index for censored data using genetic algorithms
Conclusions: We have found empirical evidence that ensembles of ANN models can be optimized directly on the c-index. Comparison with a Cox model indicates that near identical performance is achieved on a real cancer data set while on a non-linear data set the ANN model is clearly superior. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 12, 2013 Category: Bioinformatics Authors: Jonas Kalderstam, Patrik Edén, Pär-Ola Bendahl, Carina Strand, Mårten Fernö, Mattias Ohlsson Tags: Research Articles Source Type: research

Discovering human immunodeficiency virus mutational pathways using temporal Bayesian networks
Conclusion: Our results suggest possible applications of TNBN for studying drug-mutation and mutation–mutation networks in the context of antiretroviral therapy, with direct impact on the clinical management of patients under antiretroviral therapy. This opens new horizons for predicting HIV mutational pathways in immune selection with relevance for antiretroviral drug development and therapy plan. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 5, 2013 Category: Bioinformatics Authors: Pablo Hernandez-Leal, Alma Rios-Flores, Santiago Ávila-Rios, Gustavo Reyes-Terán, Jesus A. Gonzalez, Lindsey Fiedler-Cameras, Felipe Orihuela-Espina, Eduardo F. Morales, L. Enrique Sucar Tags: Special Issue Articles Source Type: research

A pilot study of distributed knowledge management and clinical decision support in the cloud
Conclusion: Decision support in the cloud is feasible and may be a reasonable path toward achieving better support of clinical decision-making across the widest range of health care providers. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 1, 2013 Category: Bioinformatics Authors: Brian E. Dixon, Linas Simonaitis, Howard S. Goldberg, Marilyn D. Paterno, Molly Schaeffer, Tonya Hongsermeier, Adam Wright, Blackford Middleton Tags: Special Issue Articles Source Type: research

Impact of four training conditions on physician use of a web-based clinical decision support system
Conclusion: Training format may have differential effects on initial and long-term follow-up of CDSSs use by physicians. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 1, 2013 Category: Bioinformatics Authors: Edith Kealey, Emily Leckman-Westin, Molly T. Finnerty Tags: Special Issue Articles Source Type: research

A pilot study of distributed knowledge management and clinical decision support in the cloud
Conclusion: Decision support in the cloud is feasible and may be a reasonable path toward achieving better support of clinical decision-making across the widest range of health care providers. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 1, 2013 Category: Bioinformatics Authors: Brian E. Dixon, Linas Simonaitis, Howard S. Goldberg, Marilyn D. Paterno, Molly Schaeffer, Tonya Hongsermeier, Adam Wright, Blackford Middleton Tags: Special Issue Articles Source Type: research

Impact of four training conditions on physician use of a web-based clinical decision support system
Conclusion: Training format may have differential effects on initial and long-term follow-up of CDSSs use by physicians. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 1, 2013 Category: Bioinformatics Authors: Edith Kealey, Emily Leckman-Westin, Molly T. Finnerty Tags: Special Issue Articles Source Type: research

Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions
Conclusion: Introducing new features to those of the grey-level co-occurrence matrix significantly increased the differentiation between the malignant and the benign breast lesions, thus resulting in a high sensitivity and improved specificity. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 1, 2013 Category: Bioinformatics Authors: Jana Milenković, Kristijana Hertl, Andrej Košir, Janez Žibert, Jurij Franc Tasič Tags: Research Articles Source Type: research

Argumentation-logic for creating and explaining medical hypotheses
Conclusion: Our comparative evaluation of the EIRA system against the newly developed tool highlights the multiple benefits that the use of argumentation-logic can bring to the field of medical decision support and explanation. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 25, 2013 Category: Bioinformatics Authors: Maria Adela Grando, Laura Moss, Derek Sleeman, John Kinsella Tags: Research Articles Source Type: research

Predicting patient survival after liver transplantation using evolutionary multi-objective artificial neural networks
Conclusion: The proposed rule-based system is objective, because it does not involve medical experts (the expert's decision may be biased by several factors, such as his/her state of mind or familiarity with the patient). This system is a useful tool that aids medical experts in the allocation of organs; however, the final allocation decision must be made by an expert. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 14, 2013 Category: Bioinformatics Authors: Manuel Cruz-Ramírez, César Hervás-Martínez, Juan Carlos Fernández, Javier Briceño, Manuel de la Mata Tags: Research Articles Source Type: research

Creating personalised clinical pathways by semantic interoperability with electronic health records
Conclusion: This study contributes towards improving the clinical personalised practicality of standardised CPs. In addition, this study establishes the foundation for future work on the research and development of an independent CP system. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 6, 2013 Category: Bioinformatics Authors: Hua-Qiong Wang, Jing-Song Li, Yi-Fan Zhang, Muneou Suzuki, Kenji Araki Tags: Research Articles Source Type: research

Impact of precision of Bayesian network parameters on accuracy of medical diagnostic systems
Conclusion: The experiments’ results provide evidence that as long as we avoid zeroes among model parameters, diagnostic accuracy of Bayesian network models does not suffer from decreased precision of their parameters. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 6, 2013 Category: Bioinformatics Authors: Agnieszka Oniśko, Marek J. Druzdzel Tags: Special Issue Articles Source Type: research

A knowledge-based clinical toxicology consultant for diagnosing multiple exposures
Conclusions: Although the system failed to completely diagnose exposures to multiple toxins, the ability to identify the primary contributor in such cases may prove valuable in aiding medical personnel as they seek to diagnose and treat patients. As time passes and more cases are added to the FPIC database, we believe system accuracy will continue to improve, producing a viable decision support system for clinical toxicology. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 4, 2013 Category: Bioinformatics Authors: Joel D. Schipper, Douglas D. Dankel, A. Antonio Arroyo, Jay L. Schauben Tags: Research Articles Source Type: research

Prediction of body mass index status from voice signals based on machine learning for automated medical applications
Conclusion: Our results could support the development of BMI diagnosis tools for real-time monitoring; such tools are considered helpful in improving automated BMI status diagnosis in remote healthcare or telemedicine and are expected to have applications in forensic and medical science. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 1, 2013 Category: Bioinformatics Authors: Bum Ju Lee, Keun Ho Kim, Boncho Ku, Jun-Su Jang, Jong Yeol Kim Tags: Research Articles Source Type: research

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

Missing data in medical databases: Impute, delete or classify?
Conclusions: In this work, we improve modeling performance in a simulated test bed, and then confirm improved performance replicating previously published work by using the proposed approach for missing data classification. We offer this new method to other researchers who wish to improve predictive risk modeling performance in the ICU through advanced missing data management. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 21, 2013 Category: Bioinformatics Authors: Federico Cismondi, André S. Fialho, Susana M. Vieira, Shane R. Reti, João M.C. Sousa, Stan N. Finkelstein Tags: Research Articles Source Type: research

Probabilistic problem solving in biomedicine
With the current trend towards pervasive health care (see e.g. ), personalised health care (see e.g. ), and the ever growing amount of evidence coming from biomedical research, methods that can handle reasoning and learning under uncertainty are becoming more and more important. Probabilistic methods, and in particular Bayesian networks (BNs), have been introduced in the 1980s as a formalism for representing and reasoning with models of problems involving uncertainty, adopting probability theory as a basic framework. Since the beginning of the 1990s, researchers are exploring its possibilities for developing medical applic...
Source: Artificial Intelligence in Medicine - February 21, 2013 Category: Bioinformatics Authors: Arjen Hommersom, Peter J.F. Lucas Tags: Guest Editorial Source Type: research

Generating personalized advice for schizophrenia patients
Conclusions: Our findings suggest that an approach that uses problem severities to identify important problems for a patient corresponds closely to the way a clinician thinks. Furthermore, after applying a severity threshold, the majority of advice units selected by the system are considered relevant by the patients. Our findings pave the way for the development of systems that facilitate patient-centered care for chronic illnesses by automating the sharing of assessment results between patient and clinician. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 18, 2013 Category: Bioinformatics Authors: Ando Emerencia, Lian van der Krieke, Sjoerd Sytema, Nicolai Petkov, Marco Aiello Tags: Research Articles Source Type: research