Explainable Model-specific Algorithm Selection for Multi-Label Classification

Multi-label classification (MLC) is an ML task of predictive modeling in which a data instance can simultaneously belong to multiple classes. MLC is increasingly gaining interest in different application domains such as text mining, computer vision, and bioinformatics. Several MLC algorithms have been proposed in the literature, resulting in a meta-optimization problem that the user needs to address: which MLC approach to select for a given dataset? To address this algorithm selection problem, we investigate in this work the quality of an automated approach that uses characteristics of the datasets - so-called features - and a trained algorithm selector to choose which algorithm to apply for a given task. For our empirical evaluation, we use a portfolio of 38 datasets. We consider eight MLC algorithms, whose quality we evaluate using six different performance metrics. We show that our automated algorithm selector outperforms any of the single MLC algorithms, and this is for all evaluated performance measures. Our selection approach is explainable, a characteristic that we exploit to investigate which meta-features have the largest influence on the decisions made by the algorithm selector. Finally, we also quantify the importance of the most significant meta-features for various domains

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

Matrix metalloproteinases (MMP-1, -8, -13) in chronic periapical lesions

Background/Aim. Matrix metalloproteinases (MMPs) are proteolytic enzymes capable of degrading almost all extracellular matrix and basement membrane components in many destructive pathological processes, such as chronic inflammation and bone-destructive lesions. The aim of this study was to determinate the correlation between concentration of collagenases (MMP-1, -8, -13) in chronic periapical lesions and their dimension calculated with software predilection through X-ray. Metods. Chronic periapical tissues were collected by periapical surgery from 60 teeth with clinically and radiographically verified different chronic periapical lesions (20 granulomas, 20 diffuse periapical lesions, 10 cysts). Ten normal pulps used as controls were obtained by extirpation of the pulp of impacted third molars after their surgery. For rapid analysis of MMP-1, -8, -13 collagenase activities in the examined material Chemicon Collagenase Activity Assay Kit were used. From the X-ray trough software predilection (Image Tool3 Program) of the volume of chronic periapical tissue, correlation between concentration of MMPs in the periapical lesions and their dimension was confirmed. Results. Different concentrations of collagenases (MMP-1, -8 and -13) in chronic periapical process from different inflammation types showed different activity of MMPs. The obtained results showed the highest values of collagenases concentration (MMP-1, -8, -13) in chronic diffuse lesions (5.39 ng/ml). Low values of concentration of MMPs accompanied less serious lesions, whereas chronical periapical lesions of large dimension had high concentration of MMPs, which was proportional to progression of the lesion and destruction of bone tissue. Conclusions. This study confirmed the destructive role of collagenases (MMP-1, -8 and -13) in inflammation process, which directly depends on the concentration of MMPs in pathologically changed tissue. Key words: periapical diseases; matrix metalloproteinases; collagen

Concentration of collagenases (MMP-1, -8, -13) in patients with chronically inflamed dental pulp tissue

Matrix metalloproteinases (MMPs) form an enzyme family capable of degrading almost all extracellular matrix (ECM) and basement membrane (BM) components. They play an important role in normal tissue remodelling and growth, as well as in many destructive pathological conditions such as inflammation, tumour growth and metastasis. The role of MMPs in the breakdown of pulp tissue of teeth with pulpitis has not yet been directly elucidated. The purpose of this study was to evaluate the tissue levels of collagenases (MMP-1, -8, -13) and their distributions in the clinically healthy and chronically inflamed human dental pulps of 30 patients, aged 15–70 years. Twenty pulps were collected from subjects diagnosed with chronic pulpitis, and 10 control pulps were obtained from 10 subjects following molar extraction for orthodontic reasons. The levels of collagenases were determined with an enzyme-linked immunosorbent assay (ELISA). Results reveal that levels of collagenases were significantly higher in chronically inflamed vs. clinically normal pulps. Overall, these results show that MMPs play an important role in ECM destruction during the inflammatory processes of pulpitis, as well as reflecting the special characteristics of them. This investigation opens a new opportunity for one contemporarymethod for the diagnosis of pulp inflammations and monitoring of the inflammatory processes. Key words: matrix metalloproteinases, collagenases, pulp tissue, pulpitis

Identification of pre-core and basal core promoter mutants in patients with chronic hepatitis b in the Republic of Macedonia

Background: Recent development of molecular techniques has improved our understanding of the role of various mutations of the HBV genome. Most common are mutations in the precore (PC) and basal core promoter (BCP) region, responsible for more serious course of chronic hepatitis. Aim of the study: was to evaluate the prevalence of PC and BCP mutants in patients with chronic hepatitis B in the Republic of Macedonia. METODI Material and methods: Serum samples from 69 patients with chronic hepatitis B (47 males and 22 females, average age 49±20y.) were collected in the period from 2002-2012. All serum samples were tested for HBV, HCV and HDV infection and immediately frozen at -70#C. According to the HBeAg status, these patients were divided in two groups: HBeAg positive (15/69 pts or 21, 74%), and HBeAg-negative (54/69 pts or 78,26%). Molecular examination including extraction and amplification of HBV DNA was performed. To establish if HBeAgnegative status is related to sero-conversion, or as a consequence of viral mutations, we have used INNO-Lipa hybridization assay from Innogenetics to identify the presence of mutations in precore and BCP region of HBV DNA. Molecular analysis was done in 38/54 HBeAg-negative patients (28 males and 10 females). RISULTATI Results: The prevalence of PC mutants in 84,21% (p=0,0000) and BCP mutants in 68,42% (P=0,0033) were extremely high in 38 examined HBeAg-negative patients. Combination of PC and BCP mutants was detected in HBV DNA of 25/38 HBeAg-negative patients (65,78%). CONCLUSIONI As a conclusion, HBeAg-negative stage was predominant in our patients with chronic hepatitis B and was related to mutations in PC and BCP region