User-defined functions in the Arden Syntax: an extension proposal
Conclusions It is possible to add user-defined functions to the Arden Syntax in a way that remains coherent with the standard. We believe that this enhances the readability and the robustness of MLMs. A detailed proposal will be submitted by the end of the year to the HL7 workgroup on Arden Syntax. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - December 11, 2015 Category: Bioinformatics Source Type: research

Clinical decision support systems at the Vienna General Hospital using Arden Syntax: Design, implementation, and integration
Conclusion Since the inception of the AKIM project at the VGH and its ability to support standards such as Arden Syntax and integrate CDSSs into clinical routine, the clinicians’ interest in, and demand for, decision support has increased substantially. The use of Arden Syntax as a standard for CDSSs played a substantial role in the ability to rapidly create high-quality CDSS systems, whereas the ability to integrate these systems into the HIS made CDSSs more popular among physicians. Despite these successes, challenges such as lack of (consistent and high-quality) electronic data, social acceptance among healthcare ...
Source: Artificial Intelligence in Medicine - December 2, 2015 Category: Bioinformatics Source Type: research

A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis
Conclusion Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 18, 2015 Category: Bioinformatics Source Type: research

The feature selection bias problem in relation to high-dimensional gene data
Conclusions This work provides evidence that using the same dataset for feature selection and learning is not appropriate. We recommend using cross-validation for feature selection in order to reduce selection bias. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 18, 2015 Category: Bioinformatics Source Type: research

Analyzing depression tendency of web posts using an event-driven depression tendency warning model
Conclusions This paper presents an E3 method to automatically extract negative event terms in web posts. We also proposed a new EDDTW model to predict the depression tendency of web posts and possibly help bloggers or post authors to early detect major depressive disorder. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - November 3, 2015 Category: Bioinformatics Source Type: research

A Generalized Procedure for Analyzing Sustained and Dynamic Vocal Fold Vibrations from Laryngeal High-Speed Videos using Phonovibrograms
Conclusions The incorporation of parameters describing the temporal evolvement of vocal fold vibration clearly improves the automatic identification of pathologic vibration patterns. Furthermore, incorporating a dynamic phonation paradigm provides additional valuable information about the underlying laryngeal dynamics that cannot be derived from sustained conditions. The proposed generalized approach provides a better overall classification performance than the previous approach, and hence constitutes a new advantageous tool for an improved clinical diagnosis of voice disorders. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 30, 2015 Category: Bioinformatics Source Type: research

Data-driven knowledge acquisition, validation, and transformation into HL7 Arden Syntax
Conclusion Data-driven knowledge acquisition and validation against published guidelines were used to help a team of physicians and knowledge engineers create executable clinical knowledge. The advantages of the R-CKM are twofold: it reflects real practices and conforms to standard guidelines, while providing optimal accuracy comparable to that of a PM. The proposed approach yields better insight into the steps of knowledge acquisition and enhances collaboration efforts of the team of physicians and knowledge engineers. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 28, 2015 Category: Bioinformatics Source Type: research

Assessing the feasibility of a mobile health-supported clinical decision support system for nutritional triage in oncology outpatients using Arden Syntax
Conclusion : Despite strict protection of the clinical data domain, a CDSS employing patient-generated data can be integrated into clinical routine. The CDSS discussed in this report combined the information entered into a smartphone application with clinical data in order to inform the physician of a patient's nutritional status and thus permit suitable and timely intervention. The initial results show that the smartphone application was well accepted by patients, who considered it useful, but not many oncological outpatients were willing to participate in the clinical study because they did not possess an Android phone o...
Source: Artificial Intelligence in Medicine - October 23, 2015 Category: Bioinformatics Source Type: research

Using Arden Syntax for the creation of a multi-patient surveillance dashboard
Conclusion Our study demonstrated the general feasibility of creating multi-patient CDS routines in Arden Syntax. We believe that our prototypical dashboard also suggests that such implementations can be relatively easy, and may simultaneously hold promise for sharing dashboards between institutions and reusing elementary components for additional dashboards. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 9, 2015 Category: Bioinformatics Source Type: research

Information extraction from multi-institutional radiology reports
Conclusions Our machine learning information extraction approach provides an effective automatic method to annotate and extract clinically significant information from a large collection of free text radiology reports. This information extraction system can help clinicians better understand the radiology reports and prioritize their review process. In addition, the extracted information can be used by researchers to link radiology reports to information from other data sources such as electronic health records and the patient's genome. Extracted information also can facilitate disease surveillance, real-time clinical decis...
Source: Artificial Intelligence in Medicine - October 4, 2015 Category: Bioinformatics Source Type: research

Pediatric decision support using adapted arden syntax
Conclusions Our results show that the Arden Syntax standard provided us with an effective way to represent pediatric guidelines for use in routine care. We only required minor modifications to the standard to support our clinical workflow. Additionally, Arden Syntax implementation in CHICA facilitated the study of many pediatric guidelines in real clinical environments. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - October 2, 2015 Category: Bioinformatics Source Type: research

Using Arden Syntax Medical Logic Modules to reduce overutilization of laboratory tests for detection of bacterial infections - success or failure?
Conclusion We observed an 18% reduction of PCT tests within the first four weeks of CDSS support in the investigated ICU. This reduction may have been influenced by raised awareness of the overutilization problem; the extent of this influence cannot be determined in our study design. No reduction of PCT tests could be observed during the second ON phase. The physician interviews indicated that time critical ICU situations can prevent extensive reflection about the necessity of individual tests. In order to achieve an enduring effect on PCT utilization, we will have to proceed to electronic order entry. (Source: Artificial ...
Source: Artificial Intelligence in Medicine - September 25, 2015 Category: Bioinformatics Source Type: research

Sparse deconvolution of higher order tensor for fiber orientation distribution estimation
Conclusions Results of testing the deconvolution technique demonstrate that it allows HOTs to obtain increasingly clean and sharp FOD, which in turn significantly increases the angular resolution of current HOT methods. With sparsity on FOD domain, this method efficiently improves the ability of HOT in resolving crossing fibers. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 17, 2015 Category: Bioinformatics Source Type: research

Accessing complex patient data from Arden Syntax Medical Logic Modules
Conclusion The most promising approach by far was to map arbitrary XML structures onto congruent complex data types of Arden Syntax through deserialization. This approach is generic insofar as a data mapper based on this approach can transform any patient data provided in appropriate XML format. Therefore it could help overcome a major obstacle for integrating clinical decision support functions into clinical information systems. Theoretically, the deserialization approach would even allow mapping entire patient records onto Arden Syntax objects in one single step. We recommend extending the Arden Syntax specification with...
Source: Artificial Intelligence in Medicine - September 13, 2015 Category: Bioinformatics Source Type: research

On local anomaly detection and analysis for clinical pathways
Conclusion: Substantial experimental results show that the proposed approach can effectively detect local anomalies in CPs, and also provide diagnostic information on the detected anomalies in an informative manner. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - September 9, 2015 Category: Bioinformatics Source Type: research

Value of Information Analysis for Interventional and Counterfactual Bayesian Networks in Forensic Medical Sciences
Conclusions We have shown how the method becomes useful for decision makers, not only when decision making is subject to amendments on the basis of some unknown risk factors, but also when it is not. Knowing that a decision outcome is independent of one or more unknown risk factors saves us from the trouble of seeking information about the particular set of risk factors. Further, we have also extended the assessment of this implication to the counterfactual case and demonstrated how answers about interventional actions are expected to change when some unknown factors become known, and how useful this becomes in forensic me...
Source: Artificial Intelligence in Medicine - September 9, 2015 Category: Bioinformatics Source Type: research

Interpretative reading of the antibiogram – a semi-naïve Bayesian approach
Conclusion A practical method for predicting probability for antimicrobial susceptibility could be developed based on a semi-naïve Bayesian approach using statistical data on cross-susceptibilities and cross-resistances. The reduction in Brier distance from 37.7% to 25.3%, indicates a significant advantage to the proposed min2max2 method (p<10 99). (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 29, 2015 Category: Bioinformatics Source Type: research

Predicting readmission risk with institution-specific prediction models
Conclusions The institution-specific readmission risk prediction framework is more flexible and more effective than the one-size-fit-all models like the LACE, sometimes twice and three-time more effective. The admission-time models are able to give early warning signs compared to the discharge-time models, and may be able to help hospital staff intervene early while the patient is still in the hospital. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 23, 2015 Category: Bioinformatics Source Type: research

Benchmarking human epithelial type 2 interphase cells classification methods on a very large dataset
Conclusions We found that highest performance is obtained when using a strong classifier (typically a kernelised support vector machine) in conjunction with features extracted from local statistics. Furthermore, the misclassification profiles of the different methods highlight that some staining patterns are intrinsically more difficult to recognize. We also noted that performance is strongly affected by the fluorescence intensity level. Thus, low accuracy is to be expected when analyzing low contrasted images. Graphical abstract Highlights (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 22, 2015 Category: Bioinformatics Source Type: research

Scalable gastroscopic video summarization via similar-inhibition dictionary selection
Conclusions: For gastroscopic video summarization, we propose an automated annotation method via similar-inhibition dictionary selection. Our model can achieve better performance compared with other state-of-the-art models and supplies more suitable key frames for diagnosis. The developed algorithm can be automatically adapted to various real applications, such as the training of young clinicians, computer-aided diagnosis or medical report generation. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 19, 2015 Category: Bioinformatics Source Type: research

Benchmarking human epithelial type 2 interphase cellsclassification methods on a very large dataset
Conclusions. We found that highest performance is obtained when using a strong classifier (typically a kernelised support vector machine) in conjunction with features extracted from local statistics. Furthermore, the misclassification profiles of the different methods highlight that some staining patterns are intrinsically more difficult to recognize. We also noted that performance is strongly affected by the fluorescence intensity level. Thus, low accuracy is to be expected when analyzing low contrasted images. Graphical abstract Highlights (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 15, 2015 Category: Bioinformatics Source Type: research

Robust feature selection to predict tumor treatment outcome
Conclusions Compared with other feature selection methods, the proposed HFS and pHFS provide the most promising results. For our HFS method, we have empirically shown that the addition of prior knowledge improves the robustness and accelerates the convergence. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 15, 2015 Category: Bioinformatics Source Type: research

Interpretative reading of the antibiogram–a semi-naïve Bayesian approach
Conclusion A practical method for predicting probability for antimicrobial susceptibility could be developed based on a semi-naïve Bayesian approach using statistical data on cross-susceptibilities and cross-resistances. The reduction in Brier distance from 37.7% to 25.3%, indicates a significant advantage to the proposed min2max2 method (p<10 99). (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 15, 2015 Category: Bioinformatics Source Type: research

A fuzzy-ontology oriented case-based reasoning framework for semantic diabetes diagnosis
Conclusion Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 15, 2015 Category: Bioinformatics Source Type: research

Intelligent healthcare informatics in big data era
Publication date: Available online 12 August 2015 Source:Artificial Intelligence in Medicine Author(s): Christopher C. Yang, Pierangelo Veltri (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 13, 2015 Category: Bioinformatics Source Type: research

A hybrid cost-sensitive ensemble for imbalanced breast thermogram classification
Conclusions Our proposed hybrid cost-sensitive ensemble can facilitate a highly accurate early diagnostic of breast cancer based on thermogram features. It overcomes the difficulties posed by the imbalanced distribution of patients in the two analysed groups. Graphical abstract Highlights (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 2, 2015 Category: Bioinformatics Source Type: research

Artificial Intelligence in medicine AIME 2013
Publication date: Available online 30 July 2015 Source:Artificial Intelligence in Medicine Author(s): Niels Peek, Roque Marín Morales, Mor Peleg (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 31, 2015 Category: Bioinformatics Source Type: research

Thirty years of artificial intelligence in medicine (AIME) conferences: A review of research themes
Conclusions There has been a major shift from knowledge-based to data-driven methods while the interest for other research themes such as uncertainty management, image and signal processing, and natural language processing has been stable since the early 1990s. AIME papers relating to guidelines and protocols are among the most highly cited. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 29, 2015 Category: Bioinformatics Source Type: research

Multilingual event extraction for epidemic detection
Conclusions Most event extraction systems rely on extensive resources that are language-specific. While their sophistication induces excellent results (over 90% precision and recall), it restricts their coverage in terms of languages and geographic areas. In contrast, in order to detect epidemic events in any language, the Daniel system only requires a list of a few hundreds of disease names and locations, which can actually be acquired automatically. The system can perform consistently well on any language, with precision and recall around 82% on average, according to this paper's evaluation. Daniel's character-based appr...
Source: Artificial Intelligence in Medicine - July 18, 2015 Category: Bioinformatics Source Type: research

Corrigendum to “A characterization of electrocardiogram signals through optimal allocation of information granularity” [Artif. Intell. Med. 54 (2012) 125–134]
Publication date: Available online 16 July 2015 Source:Artificial Intelligence in Medicine Author(s): Adam Gacek, Witold Pedrycz (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 17, 2015 Category: Bioinformatics Source Type: research

Removing confounding factors via constraint-based clustering: An application to finding homogeneous groups of multiple sclerosis patients
Conclusions Our method groups data removing the effect of counfounding factors without making any assumptions about the form of the influence of these factors on the other features. We identified clusters of MS patients that have clinically recognizable differences. Because patients more likely to progress are found using this approach, our results have the potential to aid physicians in tailoring treatment decisions for MS patients. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 11, 2015 Category: Bioinformatics Source Type: research

Origins of the Arden Syntax
Publication date: Available online 2 July 2015 Source:Artificial Intelligence in Medicine Author(s): George Hripcsak , Ove B. Wigertz , Paul D. Clayton (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 4, 2015 Category: Bioinformatics Source Type: research

Synthesis of a high resolution social contact network for Delhi with application to pandemic planning
Conclusion A high resolution synthetic network is constructed based on surveyed data. It captures the underlying contact structure of a certain population and can be used to quantitatively analyze public health policy effectiveness. To the best of our knowledge, this study is the first of its kind in the Indian sub-continent. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 4, 2015 Category: Bioinformatics Source Type: research

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network
Conclusions Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 4, 2015 Category: Bioinformatics Source Type: research

Cardiac magnetic resonance image-based classification of the risk of arrhythmias in post-myocardial infarction patients
Conclusion These promising results suggest that the discriminative features introduced in this paper can be used by medical professionals, or in automatic decision support systems, along with the recognized risk markers, to improve arrhythmic risk stratification in post-MI patients. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - July 4, 2015 Category: Bioinformatics Source Type: research

Boosting drug named entity recognition using an aggregate classifier
Conclusion We conclude that gold-standard data are not a hard requirement for drug NER. Combining heterogeneous models build on dictionary knowledge can achieve similar or comparable classification performance with that of the best performing model trained on gold-standard annotations. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 17, 2015 Category: Bioinformatics Source Type: research

Spatiotemporal data visualisation for homecare monitoring of elderly people
Conclusions: In home monitoring systems, spatiotemporal visualization is a useful tool for identifying risk and preventing home accidents in elderly people living alone. The MTA model helps the visualisation in different stages of the temporal data analysis process. In particular, its explicit representation of space and movement is useful for identifying potential scenarios of risk, while the spiral structure can be used for the identification of recurrent patterns. The results of the experiments and the experience using the visualization tool 8VISU proof the potential of the MTA graphical model to mine temporal data and ...
Source: Artificial Intelligence in Medicine - June 14, 2015 Category: Bioinformatics Source Type: research

Protein–protein interaction identification using a hybrid model
Conclusion The experimental evaluations conducted with PPIs in well-known databases showed the effectiveness of our approach that explores context information in PPI identification. This investigation confirmed that within the framework of relational similarity, the word similarity model relieves the data sparseness problem in similarity calculation. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - June 7, 2015 Category: Bioinformatics Source Type: research

An approach to fuzzy soft sets in decision making based on grey relational analysis and Dempster–Shafer theory of evidence: An application in medical diagnosis
Conclusion An approach to fuzzy soft sets in decision making by combining grey relational analysis with Dempster–Shafer theory of evidence is introduced. The advantages of this approach are discussed. A practical application to medical diagnosis problems is given. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 29, 2015 Category: Bioinformatics Source Type: research

An unsupervised feature learning framework for basal cell carcinoma image analysis
Conclusions The proposed UFL-representation-based approach outperforms state-of-the-art methods for BCC detection. Thanks to its visual interpretation layer, the method is able to highlight discriminative tissue regions providing a better diagnosis support. Among the different UFL strategies tested, TICA-learned features exhibited the best performance thanks to its ability to capture low-level invariances, which are inherent to the nature of the problem. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

A label fusion method using conditional random fields with higher-order potentials: Application to hippocampal segmentation
Conclusions We introduce a new label fusion method based on a CRF model and on ROIs. The CRF model is characterized by a pseudo-Boolean function defined on unary, pairwise and higher-order potentials. The proposed Boolean function is representable by graphs. A globally optimal binary labeling is found using a st-mincut algorithm in each ROI. We show that the proposed approach is very competitive with respect to recently reported methods. Graphical abstract Highlights (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

An improved I-FAST system for the diagnosis of Alzheimer's disease from unprocessed electroencephalograms by using robust invariant features
Conclusions This new version of I-FAST makes different steps forward: (a) avoidance of pre-processing phase and filtering procedure of EEG data, being the algorithm able to directly process an unprocessed EEG; (b) noise elimination, through the use of a training variant with input selection and testing system, based on naïve Bayes classifier; (c) a more robust classification phase, showing the stability of results on nine well known learning machine algorithms; (d) extraction of spatial invariants of an EEG signal using, in addition to the unsupervised ANN, the principal component analysis and the multi scale entropy,...
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

Semi-online patient scheduling in pathology laboratories
Conclusion The proposed approach has been successfully applied to scheduling patients in a pathology laboratory considering the real-world settings including precedence constraints of tests, constraint on the number of sites or operators for taking tests (i.e. multi-machine problem), and semi-online nature of the problem. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

An approach to fuzzy soft sets in decision making based ongrey relational analysis and Dempster-Shafer theory of evidence: Anapplication in medical diagnosis
Conclusion: An approach to fuzzy soft sets in decision making by combining grey relational analysis with Dempster-Shafer theory of evidence is introduced. The advantages of this approach are discussed. A practical application to medical diagnosis problems is given. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

An empirical evaluation of supervised learning approaches in assigning diagnosis codes to electronic medical records
Conclusions We show that datasets at different scale (size of the EMRs, number of distinct codes) and with different characteristics warrant different learning approaches. For shorter narratives pertaining to a particular medical subdomain (e.g., radiology, pathology), classifier chaining is ideal given the codes are highly related with each other. For realistic in-patient full EMRs, feature and data selection methods offer high performance for smaller datasets. However, for large EMR datasets, we observe that the binary relevance approach with learning-to-rank based code reranking offers the best performance. Regardless o...
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning
Conclusions Most segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmentation and registration accuracy compared to other models. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

Corrigendum to “A computer vision framework for finger-tapping evaluation in Parkinson's disease” [Artif. Intell. Med. 60 (2014) 27–40]
Publication date: Available online 23 May 2015 Source:Artificial Intelligence in Medicine Author(s): Taha Khan , Dag Nyholm , Jerker Westin , Mark Dougherty (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

Protein-protein interaction identification using a hybrid model
Conclusion The experimental evaluations conducted with PPIs in well-known databases showed the effectiveness of our approach that explores context information in PPI identification. This investigation confirmed that within the framework of relational similarity, the word similarity model relieves the data sparseness problem in similarity calculation. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 27, 2015 Category: Bioinformatics Source Type: research

Learning from healthy and stable eyes: a new approach for detection of glaucomatous progression
Conclusion: The use of the dependency measurement in the SVDD framework increased the robustness of the proposed change-detection scheme with comparison to the classical support vector machine and SVDD methods. The validation using clinical data of the proposed approach has shown that the use of only healthy and non-progressing eyes to train the algorithm led to a high diagnostic accuracy for detecting glaucoma progression compared to other methods. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 1, 2015 Category: Bioinformatics Source Type: research

An unsupervised feature learning framework for basal cell carcinomaimage analysis
Conclusions The proposed UFL-representation-based approach outperforms state-of-the-art methods for BCC detection. Thanks to its visual interpretation layer, the method is able to highlight discriminative tissue regions providing a better diagnosis support. Among the different UFL strategies tested, TICA-learned features exhibited the best performance thanks to its ability to capture low-level invariances, which are inherent to the nature of the problem. (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - May 1, 2015 Category: Bioinformatics Source Type: research