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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics Source Type: research

Intensity-based image registration using scatter search
Conclusions With a proper, problem-specific design, scatter search is able to provide a robust, global optimization. The accuracy and reliability of the registration process are superior to those of classic gradient-based techniques. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics 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 a...
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 be...
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 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 - October 12, 2014 Category: Bioinformatics 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 - October 12, 2014 Category: Bioinformatics Source Type: research

Adaptation of machine translation for multilingual information retrieval in the medical domain
Conclusions Most of the MT techniques employed in our experiments improve MT of medical search queries. Especially the intelligent training data selection proves to be very successful for domain adaptation of MT. Certain improvements are also obtained from German compound splitting on the source language side. Translation quality, however, does not appear to correlate with the IR performance – better translation does not necessarily yield better retrieval. We discuss in detail the contribution of the individual techniques and state-of-the-art features and provide future research directions. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Twitter mining for fine-grained syndromic surveillance
Conclusions Our approach yields a very high level of correlation with flu trends derived from traditional surveillance systems. Compared with Google Flu, another popular tool based on query search volumes, our method is more flexible and less sensitive to changes in web search behaviors. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

De-identification of health records using Anonym: Effectiveness and robustness across datasets
Conclusion Findings show that Anonym compares to the best approach from the 2006 i2b2 shared task. It is easy to retrain Anonym with new datasets; if retrained, the system is robust to variations of training size, data type and quality in presence of sufficient training data. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Cue-based assertion classification for Swedish clinical text—Developing a lexicon for pyConTextSwe
Conclusions We have successfully ported pyConTextNLP to Swedish (pyConTextSwe). We have created an extensive and useful assertion lexicon for Swedish clinical text, which could form a valuable resource for similar studies, and which is publicly available. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Statistical parsing of varieties of clinical Finnish
Conclusions In order to develop a good syntactic parser for clinical language variants, a general language resource is not mandatory, while data from clinical fields is. However, in addition to the exact same clinical domain, also data from other clinical domains is useful. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Text mining and information analysis of health documents
Publication date: July 2014 Source:Artificial Intelligence in Medicine, Volume 61, Issue 3 Author(s): Hanna Suominen (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Relationship between preparation of cells for therapy and cell quality using artificial neural network analysis
Conclusion CD9 surface marker loss was the most sensitive indicator of the effects of shear stress followed by loss of membrane integrity and then HLA A-C, while CD147 remained unaffected by shear stress or even prone to increase. Also greater stability of cell surface marker presence was noted for cells generated at greater passage numbers or generation numbers or for reduction in hold time in formulation buffer. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Evaluating the effects of cognitive support on psychiatric clinical comprehension
Conclusions Cognitive support impacts upon clinical comprehension. This appears to be largely helpful, but may also lead to neglect of information (such as the psychosocial history) that the system does not highlight. The results have implications for the design of CSSs for clinical narratives including the role of information organization and textual embellishments for more efficient clinical case presentation and comprehension. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

From spoken narratives to domain knowledge: Mining linguistic data for medical image understanding
Conclusions Physicians’ spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics
Conclusion Our results show that the accurate classification of syndromes is feasible using ML techniques. Thus, a large number of syndromes with characteristic facial anomaly patterns could be diagnosed with similar diagnostic DSSs to that described in the present study, i.e., visual diagnostic DSS, thereby demonstrating the benefits of using hybrid image processing and ML-based computer-aided diagnostics for identifying facial phenotypes. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Interactive web service system for exploration of biological pathways
Conclusion A system is proposed for converting the static pathway maps in KEGG into interactive maps such that they can be explored at will. The results of a preliminary trial confirm that the system is straightforward to use and provides a versatile and effective tool for examining and comparing biological pathways. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Optimization of anemia treatment in hemodialysis patients via reinforcement learning
Conclusion Although prospective validation is required, promising results demonstrate the potential of RL to become an alternative to current protocols. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Improving structural medical process comparison by exploiting domain knowledge and mined information
Conclusions The paper shows that process mining and process comparison, through a similarity metric tailored to medical applications, can be applied successfully to clinical data to gain a better understanding of different medical processes adopted by different hospitals, and of their impact on clinical outcomes. In the future, we plan to make our metric even more general and efficient, by explicitly considering various methodological and technological extensions. We will also test the framework in different domains. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Cancer survival classification using integrated data sets and intermediate information
Conclusion Among the approaches used, the integrated miRNA and mRNA data set yielded better results than the individual data sets. The best performance was achieved using the FSCOX_SVM method with independent feature selection, which uses intermediate survival information between short-term and long-term survival time and the combination of the 2 different data sets. The results obtained using the combined data set suggest that there are some strong interactions between miRNA and mRNA features that are not detectable in the individual analyses. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Cross-hospital portability of information extraction of cancer staging information
Conclusions Our performance results compare favourably to the best levels reported in the literature, and—most relevant to our aim here—the cross-corpus results demonstrate the portability of the models we developed. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Recommendations for the ethical use and design of artificial intelligent care providers
Conclusion The ethical and moral aspects regarding the use of AICP systems must be well thought-out today as this will help to guide the use and development of these systems in the future. Topics presented are relevant to end users, AI developers, and researchers, as well as policy makers and regulatory boards. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Parametric model of human body shape and ligaments for patient-specific epidural simulation
Conclusions A patient-specific epidural simulator is presented using the developed body shape model, able to simulate needle insertion procedures on a 3D model of any patient size and shape. The developed ANN gave the most accurate results for body shape, size and ligament thickness. The resulting simulator offers the experience of simulating needle insertions accurately whilst allowing for variation in patient body mass, height or age. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

A systems approach to healthcare: Agent-based modeling, community mental health, and population well-being
Conclusions The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Leucocyte classification for leukaemia detection using image processing techniques
Conclusions The proposed method permits the analysis of blood cells automatically via image processing techniques, and it represents a medical tool to avoid the numerous drawbacks associated with manual observation. This process could also be used for counting, as it provides excellent performance and allows for early diagnostic suspicion, which can then be confirmed by a haematologist through specialised techniques. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Elie Sanchez, 1944–2014
Publication date: Available online 18 September 2014 Source:Artificial Intelligence in Medicine Author(s): Rudolf Seising (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

Fuzzy logic-based diagnostic algorithm plus ventricles depolarization morphology algorithm for implantable cardioverter-defibrillators
Publication date: Available online 7 October 2014 Source:Artificial Intelligence in Medicine Author(s): Andrzej Cacko , Grzegorz Opolski , Marcin Grabowski (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 12, 2014 Category: Bioinformatics Source Type: research

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

Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics
Dysmorphology is an area of clinical genetics that is concerned with abnormal patterns of human development and syndrome diagnosis in patients who possess congenital malformations and unusual facial features, often with delayed motor and cognitive development [1]. A high degree of experience and expertise is required to diagnose a dysmorphic patient correctly [2] because most of these syndromes are very rare. However, in some parts of the world, the diagnosis of syndromes is generally performed by medical professionals who are not well trained in dysmorphology, such as general practitioners, pediatricians, or dermatol...
Source: Artificial Intelligence in Medicine - August 23, 2014 Category: Bioinformatics Authors: Kaya Kuru, Mahesan Niranjan, Yusuf Tunca, Erhan Osvank, Tayyaba Azim Source Type: research

From spoken narratives to domain knowledge: Mining linguistic data for medical image understanding
Image understanding is an important topic studied in imaging, computing, and the cognitive sciences and incorporates the domain knowledge of target images, human vision and psychophysics, and data mining. In order to better perform computational image understanding tasks, such as object detection [1–3], shape estimation [4], or depth estimation [5], common knowledge from humans is borrowed and injected into a variety of algorithms. However, hard-coded human knowledge cannot be easily and directly applied for complex tasks such as image classification and retrieval, which involve a wide range of images and require hum...
Source: Artificial Intelligence in Medicine - August 19, 2014 Category: Bioinformatics Authors: Xuan Guo, Qi Yu, Cecilia Ovesdotter Alm, Cara Calvelli, Jeff B. Pelz, Pengcheng Shi, Anne R. Haake Source Type: research

Evaluating the effects of cognitive support on psychiatric clinical comprehension
In complex clinical environments, clinicians must cope with and manage multiple, voluminous, heterogeneous data sources to solve clinical problems [1,2]. Both comprehension and problem solving capabilities of physicians affect their efficiency, as comprehension is a prerequisite to problem solving [3]. Previous studies have suggested that the process of clinical comprehension differs between expert and novice clinicians with respect to selective filtering, pattern recognition and accuracy of inferences generated [4]. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 18, 2014 Category: Bioinformatics Authors: Venkata V. Dalai, Sana Khalid, Dinesh Gottipati, Thomas Kannampallil, Vineeth John, Brett Blatter, Vimla L. Patel, Trevor Cohen Source Type: research

Relationship between preparation of cells for therapy and cell quality using artificial neural network analysis
The successful preparation of cells for therapy depends on the characterization of causal factors affecting cell quality. Ultra scale-down methods are used to characterize cells in terms of their response to process engineering causal factors of hydrodynamic shear stress and time. This response is in turn characterized in terms of causal factors relating to variations as may naturally occur during cell preparation i.e., passage number, generation number, time of the final passage stage and hold time in formulation medium. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 19, 2014 Category: Bioinformatics Authors: Gopal Krishna Dhondalay, Katherine Lawrence, Stephen Ward, Graham Ball, Michael Hoare Source Type: research

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

Relationship between preparation of cells for therapy and cell quality using artificial neural network analysis
The successful preparation of cells for therapy depends on the characterization of causal factors affecting cell quality. Ultra scale-down methods are used to characterize cells in terms of their response to process engineering causal factors of hydrodynamic shear stress and time. This response is in turn characterized in terms of causal factors relating to variations as may naturally occur during cell preparation i.e., passage number, generation number, time of the final passage stage and hold time in formulation medium. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 19, 2014 Category: Bioinformatics Authors: Gopal Krishna Dhondalay, Katherine Lawrence, Stephen Ward, Graham Ball, Michael Hoare Source Type: research

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