Optimization of anemia treatment in hemodialysis patients via reinforcement learning
Anemia is a common complication characterized by a reduced concentration of hemoglobin (Hb) that occurs in over 90% of patients undergoing hemodialysis [1]. Hemodialysis is the most common treatment for patients in advanced stages of chronic kidney disease (CKD), particularly in its end state, commonly referred as end-stage renal disease (ESRD). In the last years the prevalence of ESRD has increased substantially, reaching more than 1000 per million population in most of the developed countries [2]. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 19, 2014 Category: Bioinformatics Authors: Pablo Escandell-Montero, Milena Chermisi, José M. Martínez-Martínez, Juan Gómez-Sanchis, Carlo Barbieri, Emilio Soria-Olivas, Flavio Mari, Joan Vila-Francés, Andrea Stopper, Emanuele Gatti, José D. Martín-Guerrero Source Type: research

Improving structural medical process comparison by exploiting domain knowledge and mined information
Process model comparison and similar process retrieval is a key issue to be addressed in many real-world situations. For example, when two companies are merged, process engineers need to compare processes originating from the two companies, in order to analyze their possible overlaps, and to identify areas for consolidation. Moreover, large companies build over time huge process model repositories, which serve as a knowledge base for their ongoing process management/enhancement efforts. Before adding a new process model to the repository, process engineers have to check that a similar model does not already exist, in order...
Source: Artificial Intelligence in Medicine - July 18, 2014 Category: Bioinformatics Authors: Stefania Montani, Giorgio Leonardi, Silvana Quaglini, Anna Cavallini, Giuseppe Micieli Source Type: research

Interactive web service system for exploration of biological pathways
Due to rapid advances in the biotechnology and systems biology fields, a huge amount of experimental data is now available regarding the interactions between the components of biological systems and the manner in which these interactions determine the function and behavior of the system. Many bioinformatics resources have been developed to store this information and to facilitate its sharing amongst national and international bodies. Amongst such resources, the Kyoto Encyclopedia of Genes and Genomes (KEGG), developed jointly by the Bioinformatics Center of Kyoto University and the Human Genome Center of the University of ...
Source: Artificial Intelligence in Medicine - July 18, 2014 Category: Bioinformatics Authors: Zong-Xian Yin, Sin-Yan Li Source Type: research

Improving structural medical process comparison by exploiting domain knowledge and mined information
Process model comparison and similar process retrieval is a key issue to be addressed in many real-world situations. For example, when two companies are merged, process engineers need to compare processes originating from the two companies, in order to analyze their possible overlaps, and to identify areas for consolidation. Moreover, large companies build over time huge process model repositories, which serve as a knowledge base for their ongoing process management/enhancement efforts. Before adding a new process model to the repository, process engineers have to check that a similar model does not already exist, in order...
Source: Artificial Intelligence in Medicine - July 18, 2014 Category: Bioinformatics Authors: Stefania Montani, Giorgio Leonardi, Silvana Quaglini, Anna Cavallini, Giuseppe Micieli Source Type: research

Improving structural medical process comparison by exploitingdomain knowledge and mined information
Process model comparison and similar process retrieval is a key issue to be addressed in many real-world situations. For example, when two companies are merged, process engineers need to compare processes originating from the two companies, in order to analyze their possible overlaps, and to identify areas for consolidation. Moreover, large companies build over time huge process model repositories, which serve as a knowledge base for their ongoing process management/enhancement efforts. Before adding a new process model to the repository, process engineers have to check that a similar model does not already exist, in order...
Source: Artificial Intelligence in Medicine - July 18, 2014 Category: Bioinformatics Authors: Stefania Montani, Giorgio Leonardi, Silvana Quaglini, Anna Cavallini, Giuseppe Micieli Source Type: research

Interactive web service system for exploration of biological pathways
Due to rapid advances in the biotechnology and systems biology fields, a huge amount of experimental data is now available regarding the interactions between the components of biological systems and the manner in which these interactions determine the function and behavior of the system. Many bioinformatics resources have been developed to store this information and to facilitate its sharing amongst national and international bodies. Amongst such resources, the Kyoto Encyclopedia of Genes and Genomes (KEGG), developed jointly by the Bioinformatics Center of Kyoto University and the Human Genome Center of the University of ...
Source: Artificial Intelligence in Medicine - July 18, 2014 Category: Bioinformatics Authors: Zong-Xian Yin, Sin-Yan Li Source Type: research

Recommendations for the ethical use and design of artificial intelligent care providers
Nearly half a century ago Joseph Weizenbaum introduced ELIZA, the first simulation of a psychotherapist [1]. ELIZA, also known as DOCTOR, was a simple computer program that was capable of mimicking the question and response conversation of a psychotherapeutic interview. A few years later, psychiatrist Kenneth Colby developed a program called PARRY that simulated a person with paranoid schizophrenia [2]. Advancements in artificial intelligence (AI) and associated technologies, such as virtual reality, natural language processing, and affective computing have enabled the creation of artificial intelligent agents in the form ...
Source: Artificial Intelligence in Medicine - July 3, 2014 Category: Bioinformatics Authors: David D. Luxton Source Type: research

Recommendations for the ethical use and design of artificial intelligent care providers
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 3, 2014 Category: Bioinformatics Authors: David D. Luxton Source Type: research

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

Cross-hospital portability of information extraction of cancer staging information
As new technologies for health care are deployed, increasing access to electronic information opens opportunities for improved productivity and decision support. Pathology reports are one rich source of valuable patient information: these contain cell and tissue data and are often critical in determining presence of certain diseases and performing diagnosis. Pathology reports are typically semi-structured, containing distinguishable components but with most information in free text (though often abbreviated or terse). (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 21, 2014 Category: Bioinformatics Authors: David Martinez, Graham Pitson, Andrew MacKinlay, Lawrence Cavedon Source Type: research

Cancer survival classification using integrated data sets and intermediate information
Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 21, 2014 Category: Bioinformatics Authors: Shinuk Kim, Taesung Park, Mark Kon Source Type: research

Cross-hospital portability of information extraction of cancer staging information
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 21, 2014 Category: Bioinformatics Authors: David Martinez, Graham Pitson, Andrew MacKinlay, Lawrence Cavedon Source Type: research

Cancer survival classification using integrated data sets and intermediate information
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 21, 2014 Category: Bioinformatics Authors: Shinuk Kim, Taesung Park, Mark Kon Source Type: research

Text mining and information analysis of health documents
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 13, 2014 Category: Bioinformatics Authors: Hanna Suominen Tags: Guest Editorial Source Type: research

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

Advanced portable remote monitoring system for the regulation of treadmill running exercises
Conclusion: In contrast with conventional control approaches, the proposed adaptive controller achieves better heart rate tracking performance under inter- and intra-model uncertainty and external disturbances. The developed system can automatically adapt to various individual exercisers and a range of exercise intensity. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 30, 2014 Category: Bioinformatics Authors: Tuan Nghia Nguyen, Steven Su, Branko Celler, Hung Nguyen Tags: Research Articles Source Type: research

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images
Conclusions: In this work we analyze the joint capability of FCFM images and scattering features for lung cancer diagnosis. The proposed method achieves a good recognition rate for such a diagnosis problem. It also performs well when used in conjunction with other features for other classical medical imaging classification problems. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 29, 2014 Category: Bioinformatics Authors: Alain Rakotomamonjy, Caroline Petitjean, Mathieu Salaün, Luc Thiberville Tags: Research Articles Source Type: research

Noninvasive evaluation of mental stress using by a refined rough set technique based on biomedical signals
Conclusions: In this study, crucial attributes in stress evaluation were successfully recognized using biomedical signals, thereby enabling the conservation of medical resources and elucidating the mapping relationship between levels of mental stress and candidate attributes. In addition, we developed a prototype system for mental stress evaluation that can be used to provide benefits in medical practice. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 29, 2014 Category: Bioinformatics Authors: Tung-Kuan Liu, Yeh-Peng Chen, Zone-Yuan Hou, Chao-Chih Wang, Jyh-Horng Chou Tags: Research Articles Source Type: research

Noninvasive evaluation of mental stress using by a refined rough set technique based on biomedical signals
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 23, 2014 Category: Bioinformatics Authors: Tung-Kuan Liu, Yeh-Peng Chen, Zone-Yuan Hou, Chao-Chih Wang, Jyh-Horng Chou Tags: Research Articles Source Type: research

Advanced portable remote monitoring system for the regulation of treadmill running exercises
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 23, 2014 Category: Bioinformatics Authors: Tuan Nghia Nguyen, Steven Su, Branko Celler, Hung Nguyen Tags: Research Articles Source Type: research

Scattering features for lung cancer detection in fibered confocal fluorescence microscopy images
(Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 23, 2014 Category: Bioinformatics Authors: Alain Rakotomamonjy, Caroline Petitjean, Mathieu Salaün, Luc Thiberville Tags: Research Articles Source Type: research

A methodology for the characterization and diagnosis of cognitive impairments—Application to specific language impairment
Conclusions: The results show that our methodology is able to find relevant information on the underlying cognitive mechanisms and to use it appropriately to provide better diagnosis than existing techniques. It is also worth noting that the individualized characterization obtained using our methodology could be extremely helpful in designing individualized therapies. Moreover, the proposed methodology could be easily extended to other languages and even to other cognitive impairments not necessarily related to language. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 9, 2014 Category: Bioinformatics Authors: Jesús Oliva, J. Ignacio Serrano, M. Dolores del Castillo, Ángel Iglesias Tags: Research Articles Source Type: research

A token centric part-of-speech tagger for biomedical text
Conclusion: Our analysis of tagger performance suggests that lexical differences between corpora have more effect on tagging accuracy than originally considered by previous research work. Biomedical POS tagging algorithms may be modified to improve their cross-domain tagging accuracy without requiring extra training or large training data sets. Future work should reexamine POS tagging methods for biomedical text. This differs from the work to date that has focused on retraining existing POS taggers. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 7, 2014 Category: Bioinformatics Authors: Neil Barrett, Jens Weber-Jahnke Tags: Research Articles Source Type: research

Scalable approximate policies for Markov decision process models of hospital elective admissions
Conclusion: Sample-based planners are a viable alternative to state-based planners for large Markov decision process models of elective admissions scheduling. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 5, 2014 Category: Bioinformatics Authors: George Zhu, Dan Lizotte, Jesse Hoey Tags: Research Articles Source Type: research

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