An ontological approach to personalized medical knowledge recommendation

Knowledge recommendation has become a promising method in supporting the clinicians decisions and improving the quality of medical services in the constantly changing clinical environment. However, current medical knowledge management systems cannot understand users requirements accurately and realize personalized recommendation. Therefore this paper proposes an ontological approach based on semiotic principles to personalized medical knowledge recommendations. In particular, healthcare domain knowledge is conceptualized and an ontology-based user profile is built. Furthermore, the personalized recommendation mechanism is illustrated.

Redefinition of the kilogram, ampere, kelvin and mole: a proposed approach to implementing CIPM recommendation 1 (CI-2005)

The International System of Units (SI) is founded on seven base units, the metre, kilogram, second, ampere, kelvin, mole and candela corresponding to the seven base quantities of length, mass, time, electric current, thermodynamic temperature, amount of substance and luminous intensity. At its 94th meeting in October 2005, the International Committee for Weights and Measures (CIPM) adopted a recommendation on preparative steps towards redefining the kilogram, ampere, kelvin and mole so that these units are linked to exactly known values of fundamental constants. We propose here that these four base units should be given new definitions linking them to exactly defined values of the Planck constant h, elementary charge e, Boltzmann constant k and Avogadro constant NA, respectively. This would mean that six of the seven base units of the SI would be defined in terms of true invariants of nature. In addition, not only would these four fundamental constants have exactly defined values but also the uncertainties of many of the other fundamental constants of physics would be either eliminated or appreciably reduced. In this paper we present the background and discuss the merits of these proposed changes, and we also present possible wordings for the four new definitions. We also suggest a novel way to define the entire SI explicitly using such definitions without making any distinction between base units and derived units. We list a number of key points that should be addressed when the new definitions are adopted by the General Conference on Weights and Measures (CGPM), possibly by the 24th CGPM in 2011, and we discuss the implications of these changes for other aspects of metrology.

Current intakes of EPA and DHA in European populations and the potential of animal-derived foods to increase them

The beneficial effects of long-chain (C chain >= 20) n-3 PUFA are well documented and, overall, increased intake reduces risk of CVD. Recent evidence also points to a role in reducing, age-related decline in cognitive function. The two key fatty acids are EPA (20:5) and DHA (22:6), with current UK recommendation for adults being 450 mg EPA + DHA/d. Whilst some EPA and DHA can be synthesised in vivo from alpha-linolenic acid, recent data indicate this source to be very limited, Suggesting that EPA and DHA should be classified as dietary essentials. In many parts of Europe the daily intake of EPA + DHA by adults and especially young adults (18-24 years) is < 100 mg/d, since many never eat oily fish. Poultry meat contributes small but worthwhile amounts of EPA+DHA. Studies to enrich the EPA+DHA content of animal-derived foods mainly use fish oil in the diet of the animal. Recent work has shown that such enrichment has the potential to provide to the UK adult diet a daily intake of EPA+DHA of about 230 mg, with poultry meat providing the largest amount (74 mg). There are. however. concerns that the Continued and possibly increased use of fish oils in animals diets is not Sustainable and alternative approaches are being examined, including the genetic modification of certain plants to allow them to synthesise EPA and DHA from shorter-chain precursors.

Using what we know: consequences of intentionally retrieving gist versus item-specific information

The effect of a prior gist-based versus item-specific retrieval orientation on recognition of objects and words was examined. Prior item-specific retrieval increased item-specific recognition of episodically related but not previously tested objects relative to both conceptual- and perceptual-gist retrieval. An item-specific retrieval advantage also was found when the stimuli were words (synonyms) rather than objects but not when participants overtly named objects during gist-based recognition testing, which suggests that they did not always label objects under general gist-retrieval instructions. Unlike verbal overshadowing, labeling objects during recognition attenuated (but did not eliminate) test- and interference-related forgetting. A full understanding of how retrieval affects subsequent memory, even for events or facts that are not themselves retrieved, must take into account the specificity with which that retrieval occurs.

An item response analysis of the motor and behavioral subscales of the unified Huntington's disease rating scale in huntington disease gene expansion carriers

Although the Unified Huntington's Disease Rating Scale (UHDRS) is widely used in the assessment of Huntington disease (HD), the ability of individual items to discriminate individual differences in motor or behavioral manifestations has not been extensively studied in HD gene expansion carriers without a motor-defined clinical diagnosis (ie, prodromal-HD or prHD). To elucidate the relationship between scores on individual motor and behavioral UHDRS items and total score for each subscale, a nonparametric item response analysis was performed on retrospective data from 2 multicenter longitudinal studies. Motor and behavioral assessments were supplied for 737 prHD individuals with data from 2114 visits (PREDICT-HD) and 686 HD individuals with data from 1482 visits (REGISTRY). Option characteristic curves were generated for UHDRS subscale items in relation to their subscale score. In prHD, overall severity of motor signs was low, and participants had scores of 2 or above on very few items. In HD, motor items that assessed ocular pursuit, saccade initiation, finger tapping, tandem walking, and to a lesser extent, saccade velocity, dysarthria, tongue protrusion, pronation/supination, Luria, bradykinesia, choreas, gait, and balance on the retropulsion test were found to discriminate individual differences across a broad range of motor severity. In prHD, depressed mood, anxiety, and irritable behavior demonstrated good discriminative properties. In HD, depressed mood demonstrated a good relationship with the overall behavioral score. These data suggest that at least some UHDRS items appear to have utility across a broad range of severity, although many items demonstrate problematic features.

Collaborative personal profiling for web service ranking and recommendation

Web service is one of the most fundamental technologies in implementing service oriented architecture (SOA) based applications. One essential challenge related to web service is to find suitable candidates with regard to web service consumer’s requests, which is normally called web service discovery. During a web service discovery protocol, it is expected that the consumer will find it hard to distinguish which ones are more suitable in the retrieval set, thereby making selection of web services a critical task. In this paper, inspired by the idea that the service composition pattern is significant hint for service selection, a personal profiling mechanism is proposed to improve ranking and recommendation performance. Since service selection is highly dependent on the composition process, personal knowledge is accumulated from previous service composition process and shared via collaborative filtering where a set of users with similar interest will be firstly identified. Afterwards a web service re-ranking mechanism is employed for personalised recommendation. Experimental studies are conduced and analysed to demonstrate the promising potential of this research.

Multi-attribute collaborative filtering recommendation based on improved group decision-making

Currently researchers in the field of personalized recommendations bear little consideration on users' interest differences in resource attributes although resource attribute is usually one of the most important factors in determining user preferences. To solve this problem, the paper builds an evaluation model of user interest based on resource multi-attributes, proposes a modified Pearson-Compatibility multi-attribute group decision-making algorithm, and introduces an algorithm to solve the recommendation problem of k-neighbor similar users. Considering the characteristics of collaborative filtering recommendation, the paper addresses the issues on the preference differences of similar users, incomplete values, and advanced converge of the algorithm. Thus the paper realizes multi-attribute collaborative filtering. Finally, the effectiveness of the algorithm is proved by an experiment of collaborative recommendation among multi-users based on virtual environment. The experimental results show that the algorithm has a high accuracy on predicting target users' attribute preferences and has a strong anti-interference ability on deviation and incomplete values.