Gesteme-free context-aware adaptation of robot behavior in human-robot cooperation
Conclusion The provided system is able to dynamic assist the operator during cooperation in the presented scenario. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 28, 2016 Category: Bioinformatics Source Type: research

Analysis of correlation between pediatric asthma exacerbation and exposure to pollutant mixtures with association rule mining
Conclusions The proposed method can be used to analyze risk variations caused by single and multiple exposures. The method is reliable and requires fewer assumptions on the data than parametric approaches. Rules including more than one pollutant highlight interactions that deserve further investigation, while helping to limit the search field. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 26, 2016 Category: Bioinformatics Source Type: research

Web-video-mining-supported workflow modeling for laparoscopic surgeries
Conclusion With the webSWM method, abundant web videos were selected and a reliable SWM was modeled in a short time with low labor cost. Satisfied performances in mining web videos and learning surgery-related knowledge show that the webSWM method is promising in scaling knowledge for intelligent surgical systems. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 19, 2016 Category: Bioinformatics Source Type: research

An adaptive large neighborhood search procedure applied to the dynamic patient admission scheduling problem
Conclusion The proposed ALNS procedure is an efficient and flexible method for solving the DPAS problem. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 17, 2016 Category: Bioinformatics Source Type: research

Non-obvious correlations to disease management unraveled by Bayesian artificial intelligence analyses of CMS data
Conclusion Potential clinical and molecular pathways defining the relationship between commonly used asthma medications and renal disease are discussed. The study underscores the need for further epidemiological research to validate this novel hypothesis. Validation will lead to advancement in clinical treatment of asthma & bronchitis, thereby, improving patient outcomes and leading to long term cost savings. In summary, this study demonstrates that application of advanced artificial intelligence methods in healthcare has the potential to enhance the quality of care by discovering non-obvious, clinically relevant r...
Source: Artificial Intelligence in Medicine - November 17, 2016 Category: Bioinformatics Source Type: research

An algorithm for direct causal learning of influences on patient outcomes
Conclusion Our results show that DCL outperforms FGS, PC, CPC, and FCI in almost every case, demonstrating its potential to advance causal learning. Furthermore, our DCL algorithm effectively identifies direct causes in the LOAD and Metabric GWAS datasets, which indicates its potential for clinical applications. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 6, 2016 Category: Bioinformatics Source Type: research

Prediction of anti-cancer drug response by kernelized multi-task learning
Conclusion The results show that the proposed method is a strong candidate to predict drug response of cancer cell lines in silico for pre-clinical studies. The source code of the algorithm and data used can be obtained from http://mtan.etu.edu.tr/Supplementary/kMTrace/. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 4, 2016 Category: Bioinformatics Source Type: research

Out of hours workload management: Bayesian inference for decision support in secondary care
Conclusions The work exhibits potential contributions of electronic tasking alternatives for the purpose of data-driven support systems design; for scheduling, prioritisation and management of care delivery. Electronic tasking technologies provide means to design intelligent systems specific to a ward, speciality or task-type; hence, the paper emphasizes the importance of replacing traditional pager-based approaches to management for modern alternatives. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 2, 2016 Category: Bioinformatics Source Type: research

Automated segmentation of white matter fiber bundles using diffusion tensor imaging data and a new density based clustering algorithm
Conclusions NDEC can find clusters with arbitrary shapes and densities and consequently can be used for WM fiber bundle segmentation where there is no distinct boundary between various bundles. NDEC may also be used as an effective tool in other pattern recognition and medical diagnostic systems in which discovering natural clusters within data is a necessity. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 1, 2016 Category: Bioinformatics Source Type: research

A comparative analysis of chaotic particle swarm optimizations for detecting single nucleotide polymorphism barcodes
Conclusion The Sinai chaotic map was found to effectively enhance the fitness values (χ2) of PSO method, indicating that the Sinai chaotic map combined with PSO method is more effective at detecting potential SNP barcodes in both the XOR and ZZ disease models. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 1, 2016 Category: Bioinformatics Source Type: research

A review on brain structures segmentation in magnetic resonance imaging
Conclusions There is not yet a single automatic segmentation approach that can emerge as a standard for the clinical practice, providing accurate brain structures segmentation. Future trends need to focus on combining multi-atlas methods with learning-based or deformable approaches. Employing atlases to provide spatial robustness and modeling the structures appearance with supervised classifiers or Active Appearance Models could lead to improved segmentation results. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 30, 2016 Category: Bioinformatics Source Type: research

Brain tumor segmentation from multimodal magnetic resonance images via sparse representation
Conclusions The experimental results show that the proposed algorithm is valid and ranks 2 nd compared with the state-of-the-art tumor segmentation algorithms in the MICCAI BRATS 2013 challenge. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 7, 2016 Category: Bioinformatics Source Type: research

A mixed-ensemble model for hospital readmission
Conclusions The mixed-ensemble model enables easy and fast exploratory knowledge discovery of the database, and a control of the classification error for positive readmission instances. Implementation of this ensembling method for predicting all-cause hospital readmissions of CHF patients allows overcoming some of the limitations of the classifiers considered individually, and of other traditional ensembling methods. It also increases the classification accuracy for positive readmission instances, particularly when strong predictors are not available. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 1, 2016 Category: Bioinformatics Source Type: research

Efficient processing of multiple nested event pattern queries over multi-dimensional event streams based on a triaxial hierarchical model
Conclusion The experimental results demonstrated that our proposal was able to process complex queries efficiently which can support health information systems and further decision-making. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 20, 2016 Category: Bioinformatics Source Type: research

Corrigendum to “Defocus-aware Dirichlet particle filter for stable endoscopic video frame recognition” [Artif. Intell. Med. 68 (March 2016) 1–16]
Publication date: Available online 9 August 2016 Source:Artificial Intelligence in Medicine Author(s): Tsubasa Hirakawa, Toru Tamaki, Bisser Raytchev, Kazufumi Kaneda, Tetsushi Koide, Shigeto Yoshida, Yoko Kominami, Shinji Tanaka (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 18, 2016 Category: Bioinformatics Source Type: research

Evolution of the Arden Syntax: Key technical issues from the standards development organization perspective
Conclusion In response to user demand and to reflect its growing role in clinical decision support, the Arden Syntax has evolved to include a number of powerful features. These depart somewhat from the original vision of the syntax as simple and easily understandable but from the SDO perspective increase the utility of this standard for implementation of CDS. Backwards compatibility has been maintained, allowing continued support of the earlier, simpler decision support models. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 12, 2016 Category: Bioinformatics Source Type: research

Executable medical guidelines with Arden Syntax —Applications in dermatology and obstetrics
Discussion Today, with the latest versions of Arden Syntax and the application of contemporary software development methods, Arden Syntax has become a powerful and versatile medical knowledge representation and processing language, well suited to implement a large range of CDSSs, including clinical-practice-guideline-based CDSSs. Moreover, such CDS is provided and can be shared as a service by different medical institutions, redefining the sharing of medical knowledge. Arden Syntax is also highly flexible and provides developers the freedom to use up-to-date software design and programming patterns for external patient dat...
Source: Artificial Intelligence in Medicine - August 12, 2016 Category: Bioinformatics Source Type: research

META-GLARE: A meta-system for defining your own computer interpretable guideline system —Architecture and acquisition
Conclusions META-GLARE is a meta-system for CIGs supporting fast prototyping. Since META-GLARE provides acquisition and execution engines that are parametric over the specific CIG formalism, it supports easy update and construction of CIG systems. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 7, 2016 Category: Bioinformatics Source Type: research

Building interpretable predictive models for pediatric hospital readmission using tree-lasso logistic regression
Conclusions We propose a method for building predictive models applicable for the detection of readmission risk based on Electronic Health records. Integration of domain knowledge (in the form of ICD-9-CM taxonomy) and a data-driven, sparse predictive algorithm (Tree-Lasso Logistic Regression) resulted in an increase of interpretability of the resulting model. The models are interpreted for the readmission prediction problem in general pediatric population in California, as well as several important subpopulations, and the interpretations of models comply with existing medical understanding of pediatric readmission. Finall...
Source: Artificial Intelligence in Medicine - July 30, 2016 Category: Bioinformatics Source Type: research

Survival analysis for high-dimensional, heterogeneous medical data: exploring feature extraction as an alternative to feature selection
Conclusions If the number of samples is insufficient, feature extraction methods are unable to reliably identify the underlying manifold, which makes them of limited use in these situations. For large sample sizes – in our experiments, 2,500 samples or more – feature extraction methods perform as well as feature selection methods. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 30, 2016 Category: Bioinformatics Source Type: research

META-GLARE: a meta-system for defining your own computer interpretable guideline system: architecture and acquisition
Conclusions META-GLARE is a meta-system for CIGs supporting fast prototyping. Since META-GLARE provides acquisition and execution engines that are parametric over the specific CIG formalism, it supports easy update and construction of CIG systems. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 29, 2016 Category: Bioinformatics Source Type: research

Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods
Conclusions Machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, derived from data rather than experts. Research networks and phenotype developers should cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and truly modernize biomedical research and precision medicine. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 28, 2016 Category: Bioinformatics Source Type: research

Prediction of lung cancer incidence on the low-dose computed tomography arm of the National Lung Screening Trial: A dynamic Bayesian network
Conclusion The lung cancer screening DBNs demonstrated high discrimination and predictive power with the majority of cancer and non-cancer cases. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 28, 2016 Category: Bioinformatics Source Type: research

A novel method to use fuzzy soft sets in decision making based on ambiguity measure and Dempster –Shafer theory of evidence: An application in medical diagnosis
Conclusion Three numerical examples and an application in medical diagnosis are provided to demonstrate adequately that, on the one hand, our proposed method is feasible and efficient; on the other hand, our proposed method can reduce uncertainty caused by people's subjective cognition and raise the choice decision level with the best performance. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 21, 2016 Category: Bioinformatics Source Type: research

On the development of conjunctival hyperemia computer-assisted diagnosis tools: influence of feature selection and class imbalance in automatic gradings
Conclusions Machine learning methods are able to perform an objective assessment of hyperemia grading, removing both intra- and inter-expert subjectivity while providing a gain in computation time. SMOTE and oversampling approaches minimise the class imbalance problem, while feature selection reduces the number of features from 25 to 3-5 without worsening the MSE. As the differences between the system and a human expert are similar to the differences between experts, we can therefore conclude that the system behaves like an expert. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 1, 2016 Category: Bioinformatics Source Type: research

Detecting signals of detrimental prescribing cascades from social media
Conclusion: Our study demonstrates the feasibility of generating hypotheses of detrimental PCs from social media to reduce pharmacists’ guesswork. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 30, 2016 Category: Bioinformatics Source Type: research

Predicting overlapping protein complexes from weighted protein interaction graphs by gradually expanding dense neighborhoods
Conclusions In the present manuscript, we introduce a new method for the computational prediction of protein complexes by making the realistic assumption that proteins participate in multiple protein complexes and cellular functions. Our method can detect accurate and functionally homogeneous clusters. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 28, 2016 Category: Bioinformatics Source Type: research

A survey of clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods
Conclusions Machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, derived from data rather than experts. Research networks and phenotype developers should cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and truly modernize biomedical research and precision medicine. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 25, 2016 Category: Bioinformatics Source Type: research

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey
Conclusions The development of an unobtrusive and transparent AD detection system should be based on a multimodal system in order to take full advantage of all kinds of symptoms, detect even the smallest changes and combine them, so as to detect AD as early as possible. Such a multimodal system might probably be based on physiological monitoring of MRI or EEG, as well as behavioural measurements like the ones proposed along the article. The mentioned AD datasets and image processing toolboxes are available for their use towards this goal. Issues like “label noise” and multi-site neuroimaging incompatibilities m...
Source: Artificial Intelligence in Medicine - June 23, 2016 Category: Bioinformatics Source Type: research

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction
Conclusions These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought. Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 8, 2016 Category: Bioinformatics Source Type: research

An ensemble method for extracting adverse drug events from social media
Conclusions Our experimental results indicate that ADE extraction from social media can benefit from feature selection. With respect to the effectiveness of different feature subsets, lexical features and semantic features can enhance the ADE extraction capability. Kernel-based approaches, which can stay away from the feature sparsity issue, are qualified to address the ADE extraction problem. Combining different individual classifiers using suitable combination methods can further enhance the ADE extraction effectiveness. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 6, 2016 Category: Bioinformatics Source Type: research

Effective gene expression data generation framework based on multi-model approach
Conclusions Therefore, we show that, we can significantly improve the quality of generated gene expression samples by integrating different computational models into one unified framework without dealing with complex internal details of each individual model. Moreover, the rich set of artificial gene expression samples is able to capture some biological relations that can even not be captured by the original gene expression data set. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 4, 2016 Category: Bioinformatics Source Type: research

A framework for parameter estimation and model selection in kernel deep stacking networks
Conclusions KDSNs are a computationally efficient appoximation of backpropagation-based artificial neural network techniques. Application of the proposed methodology results in a fast tuning procedure that generates KDSN fits having a similar prediction accuracy as other techniques in the field of deep learning. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 31, 2016 Category: Bioinformatics Source Type: research

Detecting borderline infection in an automated monitoring system for healthcare-associated infection using fuzzy logic
Conclusion The study showed that Moni-ICU was effective in classifying patient data as borderline for infection-related concepts and top-level HAI surveillance definitions. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

Evolving classification of intensive care patients from event data
Conclusions Our experimental results have not identified a single optimal approach for evolving classification of ICU episodes. On Days 0 and 1, the IIN algorithm has produced the simplest and the most accurate models, which incorporate the temporal order of feature arrival. However, starting with Day 2, regenerative approaches have reached better performance in terms of predictive accuracy. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

From frames to OWL2: Converting the Foundational Model of Anatomy
Conclusion Because our FMA conversion captures all or most of the information in the Frames version, is the only complete OWL version that classifies under an EL reasoner, and is maintained by the FMA authors themselves, we propose that this version should be the only official release version of the FMA in OWL, supplanting all other versions. Although several issues remain to be resolved post-conversion, release of a single, standardized version of the FMA in OWL will greatly facilitate its use in informatics research and in the development of a global knowledge base within the semantic web. Because of the fundamental natu...
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

A novel method to use fuzzy soft sets in decision making based on ambiguity measure and Dempster–Shafer theory of evidence: An application in medical diagnosis
Conclusion Three numerical examples and an application in medical diagnosis are provided to demonstrate adequately that, on the one hand, our proposed method is feasible and efficient; on the other hand, our proposed method can reduce uncertainty caused by people's subjective cognition and raise the choice decision level with the best performance. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

Transformation of Arden Syntax's medical logic modules into ArdenML for a business rules management system
Conclusion We have demonstrated that ArdenML can replace a compiler for transforming MLMs into commercial rule engine format. While the proposed XSLT stylesheet requires refinement for general use, we anticipate that the development of further XSLT stylesheets will support various rule engines. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

Classification of auditory brainstem responses through symbolic pattern discovery
Conclusion The proposed method effectively reduces dimensionality. Additionally, if the symbolic transformation includes the right domain knowledge, the method arguably outputs a data representation that denotes the relevant domain concepts more clearly. The method is capable of finding patterns in BAEPs time series and is very accurate at correctly predicting whether or not new patients have an auditory-related disorder. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

Traveling on discrete embeddings of gene expression
Conclusion The proposed framework can be successfully exploited to meaningfully visualize the samples; detect medically relevant genes; properly classify samples. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2016 Category: Bioinformatics Source Type: research

Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer
Conclusion It is possible to extract useful predictors from uncoded consultation notes that improve predictive performance. Techniques linking text to concepts in medical ontologies to derive these predictors are shown to perform best for predicting CRC in our EMR dataset. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - April 1, 2016 Category: Bioinformatics Source Type: research

A wearable sensor system for medication adherence prediction
Conclusion Our experimental evaluations confirm the accuracy of the piezoelectric necklace for detecting medicine swallows and disambiguating them from related actions. Further studies in real-world conditions are necessary to evaluate the efficacy of the proposed scheme. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 29, 2016 Category: Bioinformatics Source Type: research

A hybrid genetic algorithm-queuing multi-compartment model for optimizing inpatient bed occupancy and associated costs
Conclusion Encoding the whole information provided by both the queuing system and the cost model through chromosomes, the genetic algorithm represents an efficient tool in optimizing the bed allocation and associated costs. The methodology can be extended to different medical departments with minor modifications in structure and parameterization. Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 23, 2016 Category: Bioinformatics Source Type: research

Defocus-aware Dirichlet particle filter for stable endoscopic video frame recognition
Conclusion The proposed D-DPF is a useful tool for smoothing unstable results of frame-wise classification of endoscopic videos to support real-time diagnosis during endoscopic examinations. Graphical abstract Highlights (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - March 19, 2016 Category: Bioinformatics Source Type: research

A method for the development of disease-specific reference standards vocabularies from textual biomedical literature resources
Conclusions We developed a method for the development of disease-specific reference vocabularies. Expert-curated biomedical literature resources are substantial for acquiring disease-specific medical knowledge. It is feasible to reach near saturation in a disease-specific vocabulary using a relatively small number of literature sources. Graphical abstract (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 29, 2016 Category: Bioinformatics Source Type: research

Cardiorespiratory fitness estimation in free-living using wearable sensors
Conclusions Our investigation showed that HR can be contextualized in free-living using activity primitives and activity composites and robust CRF estimation in free-living is feasible. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 24, 2016 Category: Bioinformatics Source Type: research

Evaluation of a machine learning capability for a clinical decision support system to enhance antimicrobial stewardship programs
Conclusions The learning module was able to extract clinically relevant rules for multiple types of antimicrobial alerts. The learned rules were shown to extend the knowledge base of the baseline system by identifying pharmacist interventions that were missed by the baseline system. The learned rules identified inappropriate prescribing practices that were not supported by local experts and were missing from its knowledge base. However, combining the baseline system and the learning module increased the number of false positives. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 22, 2016 Category: Bioinformatics Source Type: research

Pattern identification of biomedical images with time series: Contrasting THz pulse imaging with DCE-MRIs
Conclusion The proposed complex valued classification methodology enables fusion of entire datasets from a sequence of spatial images taken at different time stamps; this is of interest from the viewpoint of inferring disease proliferation. The approach is also of interest for other emergent multi-channel biomedical imaging modalities and of relevance across the biomedical signal processing community. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 18, 2016 Category: Bioinformatics Source Type: research

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning
Conclusions The obtained empirical results demonstrate that the proposed adaptation methods improve the performance of the existing CBR system in recommending the number of beams to use. However, we also conclude that to be effective, the proposed adaptation of beam angles requires a large number of relevant cases in the case base. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 10, 2016 Category: Bioinformatics Source Type: research

Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease
Conclusion Experimental results showed that an analysis of kinematic and pressure features during handwriting can help assess subtle characteristics of handwriting and discriminate between PD patients and healthy controls. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - February 5, 2016 Category: Bioinformatics Source Type: research