Machine learning in orthopedics: a literature review

In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic problem or purpose. By searching both in the Scopus and Medline databases, we retrieved, screened and analyzed the content of 70 journal articles, and coded these resources following an iterative method within a Grounded Theory approach. We report the survey findings by outlining the articles\u2019 content in terms of the main machine learning techniques mentioned therein, the orthopedic application domains, the source data and the quality of their predictive performance

Interacting with More Than One Chart: What Is It All About?

Visual objects made of multiple views, e.g., dashboards and small multiples, are taking the scene in information communication and visual patterns design, but still vague are the studies that try to abstract away from characterizing them at the level of their single charts, and rather focus on their structural characteristics and the resulting interactions with their multi-view ensemble seen as a whole. In this paper, we are proposing this unified view through a multi-dimensional wheel, on the strand of Cairo\u2019s wheel made for infographics, devised for the identification, the analysis, and the evaluation of design patterns for multiple views

Repetita Iuvant: Exploring and Supporting Redundancy in Hospital Practices

This paper discusses the role of redundancy in hospital work, especially in facilitating the cognitive and coordinative tasks of health practitioners in clinical settings. It also investigates the ways in which health information technology can preserve, support and even enhance this role by being grounded in the observations and analyses that two research groups in Italy and Norway carried out in independent studies. In the present study, this previous research is reassessed and shaped into a unified and coherent design-oriented framework. This framework considers four kinds of data redundancy and outlines their peculiarities and the typical conditions in which they occur. In particular, the paper reports how these kinds of redundancies are exploited in both written artifacts and oral communications and how they affect each other. The paper also reports the impact of redundancies on the articulation work of physicians and nurses by playing either a negative or, more often, a positive role depending on the context. A series of lessons learnt are then proposed for the design of suitable coordination mechanisms that could preserve or even utilize this neglected phenomenon, which is strongly related to the interpretative and coordinative practices that are articulated in the patient\u2019s record

Characterisation of Alpine lake sediments using multivariate statistical techniques

A recent type of receptor modelling technique the Positive Matrix Factorization (PMF) has been applied to a geochemical dataset obtained by XRF analysis on sediments from 11 alpine lakes located in Italy. Also, two usual pattern recognition techniques, Principal Component Analysis (PCA) and Cluster Analysis (CA), were investigated. Four interpretable factors were identified through PMF analysis, in connection with the mineralogical/chemical features of lake sediments in the catchment areas: phosphate and sulphur source, carbonates, silicates and heavy metal-bearing minerals. Also, to properly modify individual uncertainty estimates, a new PMF factor was identified, explaining a possible Pb contamination source

Characterization of the Danube River sediments using the PMF multivariate approach

Chemical composition data for the Danube River and its tributaries sediments were analyzed using positive matrix factorization (PMF). The objective was to identify both natural and anthropogenic sources affecting Danube Basin. During the Joint Danube Survey 2 (JDS2) campaign 148 bottom sediments samples were collected. The following elements were analyzed using the X-ray fluorescence technique: Al, As, Ca, Cd, Cl, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Si, Ti, V and Zn. Mercury was determined by cold vapour atomic absorption spectrometry. Three factors were obtained considering the whole dataset (Danube and tributaries), identified as: (i) carbonate component characterized by Ca and Mg; (ii) alumino- silicate component dominated by Si and Al content and the presence of some metals attributed to natural processes; (iii) anthropogenic source identified by Hg, S, P and some heavy metals load. To better characterize the role of tributaries, the Danube and tributaries datasets, were also analyzed separately. The same three factor structures were identified in the Danube dataset. For the tributaries, a four-factor source model gave one further factor dominated by S and P, which could be attributed to the use of fertilizers in agriculture

The Indiana MAS project: Goals and preliminary results

The Indiana MAS project, funded by the Italian Ministry of Education, University and Research "Futuro in Ricerca 2010" program, aims at providing a framework for the digital protection and conservation of rock art natural and cultural heritage sites, by storing, organizing and presenting information about them in such a way to encourage scientific research and to raise the interest and sensibility towards them from the common people. The project involves two research units, namely Genova (Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi) and Salerno (Dipartimento di Matematica e Informatica), for a period of 36 months, starting from march 8th, 2012. The technologies adopted in the project range from agents to ontologies, as requested by the complex nature of the platform, where each module is devoted to a specific task: sketch and symbol recognition, semantic interpretation of complex visual scenes, multi-language text understanding, storing, classification and indexing of multimedia and heterogeneous digital objects. All of them should cooperate and coordinate in order to enable higher level components to reason on them and to detect relationships among different digital objects, hence providing new hypothesis based on such relationships

Laboratory intercomparison study for the analysis of nonylphenol and octylphenol in river water

7 pages, 4 figures, 2 tables.-- Available online Oct 30, 2007.In support of the implementation of the European Union (EU) Water Framework Directive (WFD), the European Commission (EC) Joint Research Centre (JRC) organized a laboratory and sampling intercomparison study for the chemical monitoring of polyaromatic hydrocarbons (PAHs), polybrominated diphenyl ethers (PBDEs), and nonylphenol and octylphenol (NP/OP), priority substances of the WFD, in river water. EU Member State laboratories were invited to analyze a standard solution with unknown concentration levels and a river-water extract, as well as a real water sample from the River Po (Italy). For the standard solution and the river-water extract, good agreement was achieved for five laboratories. Triple-quadrupole liquid chromatography with tandem mass spectrometry (LC-MS2) and gas chromatography with MS (GC-MS) with or without derivatization proved to be comparable methods for the analysis of NP and OP. Fluorescence detection can also be used to analyze NP and OP, but it is less specific. The results of the River Po water sample showed that some laboratories have problems in analyzing NP at concentration levels below 100 ng/L due to contamination of laboratory blanks. Plastics materials should not be used during extraction and sample preparation.Without the effort of the participating laboratories, this article would not have been possible. Susanne Boutrup, Stefano Polesello and Joan Staeb have given very helpful comments on the manuscript. Stefano Polesello is especially thanked for the help with the OP standards. Moreover, we would like to thank the “Servizio Risorse Idriche e Tutela Ambientale della Provincia di Ferrara” (Silvano Bencivelli, Paola Magri), Lars Håkanson, Graziella Leroy and Madeleine Rizzi.Peer reviewe