72 research outputs found

    Representing time and space for the semantic web

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    Representation of temporal and spatial information for the Semantic Web often involves qualitative defined information (i.e., information described using natural language terms such as "before" or "overlaps") since precise dates or coordinates are not always available. This work proposes several temporal representations for time points and intervals and spatial topological representations in ontologies by means of OWL properties and reasoning rules in SWRL. All representations are fully compliant with existing Semantic Web standards and W3C recommendations. Although qualitative representations for temporal interval and point relations and spatial topological relations exist, this is the first work proposing representations combining qualitative and quantitative information for the Semantic Web. In addition to this, several existing and proposed approaches are compared using different reasoners and experimental results are presented in detail. The proposed approach is applied to topological relations (RCC5 and RCC8) supporting both qualitative and quantitative (i.e., using coordinates) spatial relations. Experimental results illustrate that reasoning performance differs greatly between different representations and reasoners. To the best of our knowledge, this is the first such experimental evaluation of both qualitative and quantitative Semantic Web temporal and spatial representations. In addition to the above, querying performance using SPARQL is evaluated. Evaluation results demonstrate that extracting qualitative relations from quantitative representations using reasoning rules and querying qualitative relations instead of directly querying quantitative representations increases performance at query time

    Exploiting Parallelism for Hard Problems in Abstract Argumentation

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    Abstract argumentation framework (AF) is a unifying framework able to encompass a variety of nonmonotonic reasoning approaches, logic programming and computational argumentation. Yet, efficient approaches for most of the decision and enumeration problems associated to AF s are missing, thus potentially limiting the efficacy of argumentation-based approaches in real domains. In this paper, we present an algorithm for enumerating the preferred extensions of abstract argumentation frameworks which exploits parallel computation. To this purpose, the SCC-recursive semantics definition schema is adopted, where extensions are defined at the level of specific sub-frameworks. The algorithm shows significant performance improvements in large frameworks, in terms of number of solutions found and speedup

    Anticoagulants utilization in Portugal: are there inequalities?

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    Communication presented at the 2nd International Congress of CiiEM: Translational Research and Innovation in Human and Health Sciences. 11-13 June 2017, Campus Egas Moniz, Caparica, PortugalN/

    Current Situation of Medication Adherence in Hypertension

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    Despite increased awareness, poor adherence to treatments for chronic diseases remains a global problem. Adherence issues are common in patients taking antihypertensive therapy and associated with increased risks of coronary and cerebrovascular events. Whilst there has been a gradual trend toward improved control of hypertension, the number of patients with blood pressure values above goal has remained constant. This has both personal and economic consequences. Medication adherence is a multifaceted issue and consists of three components: initiation, implementation, and persistence. A combination of methods is recommended to measure adherence, with electronic monitoring and drug measurement being the most accurate. Pill burden, resulting from free combinations of blood pressure lowering treatments, makes the daily routine of medication taking complex, which can be a barrier to optimal adherence. Single-pill fixed-dose combinations simplify the habit of medication taking and improve medication adherence. Re-packing of medication is also being utilized as a method of improving adherence. This paper presents the outcomes of discussions by a European group of experts on the current situation of medication adherence in hypertension

    Diagnosing attention-deficit hyperactivity disorder (ADHD) using artificial intelligence: a clinical study in the UK

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    Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting a large percentage of the adult population. A series of ongoing efforts has led to the development of a hybrid AI algorithm (a combination of a machine learning model and a knowledge-based model) for assisting adult ADHD diagnosis, and its clinical trial currently operating in the largest National Health Service (NHS) for adults with ADHD in the UK. Most recently, more data was made available that has lead to a total collection of 501 anonymized records as of 2022 July. This prompted the ongoing research to carefully examine the model by retraining and optimizing the machine learning algorithm in order to update the model with better generalization capability. Based on the large data collection so far, this paper also pilots a study to examine the effectiveness of variables other than the Diagnostic Interview for ADHD in adults (DIVA) assessment, which adds considerable cost in the screenining process as it relies on specially trained senior clinicians. Results reported in this paper demonstrate that the newly trained machine learning model reaches an accuracy of 75.03% when all features are used; the hybrid model obtains an accuracy of 93.61%. Exceeding what clinical experts expected in the absence of DIVA, achieving an accuracy of 65.27% using a rule-based machine learning model alone encourages the development of a cost effective model in the future

    The Role of the Pharmacy Team in Atrial Fibrillation Detection in Nonclinical Settings

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    Atrial Fibrillation (AF) is a common cardiac/heart disease that increases a person’s risk of death, making early identification significant in overall disease management. Throughout my time in pharmacy school, I [Brian] have developed an interest in cardiology and research. During my last year of pharmacy school, I spent eight weeks at St. Bartholomew’s Hospital, in London, England, one of the largest cardiac centers within Europe, on an experiential training experience. While there, I had the opportunity to study specifics about many cardiac illnesses, with a focus on atrial fibrillation, and provide education to patients living with this disease. In addition to working with patients and expanding my knowledge, I participated in an exciting research project that allowed me to connect with the general population and share my knowledge about arrhythmias, which is something I’d like to continue to do after graduation. Our research project aimed to identify the role pharmacists could play in early detection of arrhythmias, particularly atrial fibrillation, and increase the population’s awareness and understanding of this illness. For our project, a pharmacist or student pharmacist was partnered with nursing staff to provide opportunities for heart rate and rhythm monitoring as well as individualized education to help ensure interested patients were more aware of the risks, signs, and symptoms of atrial fibrillation going forward. When patients met with the team, they had their heart rhythms assessed using the AliveCor Kardia ™ single-lead electrocardiogram (ECG) system. This new technology allows patients to place their fingers on a small strip that is able to accurately assess a person’s heart rate and rhythm to identify any irregularities/arrhythmias. Participants were also provided education about atrial fibrillation in hopes of preventing significant morbidity and mortality, raising awareness about this particular disease and connecting patients with care. Part of this education included us showing the patients how to manually take an accurate pulse reading, and how to differentiate between a normal and irregular rate and rhythm. By teaching the patients these skills, they now know what to look for, how to monitor their own pulse, and when to seek help in the event they, or someone they know, experience symptoms of atrial fibrillation

    A Generalised Approach for Encoding and Reasoning with Qualitative Theories in Answer Set Programming

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    Qualitative reasoning involves expressing and deriving knowledge based on qualitative terms such as natural language expressions, rather than strict mathematical quantities. Well over 40 qualitative calculi have been proposed so far, mostly in the spatial and temporal domains, with several practical applications such as naval traffic monitoring, warehouse process optimisation and robot manipulation. Even if a number of specialised qualitative reasoning tools have been developed so far, an important barrier to the wider adoption of these tools is that only qualitative reasoning is supported natively, when real-world problems most often require a combination of qualitative and other forms of reasoning. In this work, we propose to overcome this barrier by using ASP as a unifying formalism to tackle problems that require qualitative reasoning in addition to non-qualitative reasoning. A family of ASP encodings is proposed which can handle any qualitative calculus with binary relations. These encodings are experimentally evaluated using a real-world dataset based on a case study of determining optimal coverage of telecommunication antennas, and compared with the performance of two well-known dedicated reasoners. Experimental results show that the proposed encodings outperform one of the two reasoners, but fall behind the other, an acceptable trade-off given the added benefits of handling any type of reasoning as well as the interpretability of logic programs. This paper is under consideration for acceptance in TPLP.Comment: Paper presented at the 36th International Conference on Logic Programming (ICLP 2020), University Of Calabria, Rende (CS), Italy, September 2020, 18 pages, 3 figure

    A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

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    Spatial information is often expressed using qualitative terms such as natural language expressions instead of coordinates; reasoning over such terms has several practical applications, such as bus routes planning. Representing and reasoning on trajectories is a specific case of qualitative spatial reasoning that focuses on moving objects and their paths. In this work, we propose two versions of a trajectory calculus based on the allowed properties over trajectories, where trajectories are defined as a sequence of non-overlapping regions of a partitioned map. More specifically, if a given trajectory is allowed to start and finish at the same region, 6 base relations are defined (TC-6). If a given trajectory should have different start and finish regions but cycles are allowed within, 10 base relations are defined (TC-10). Both versions of the calculus are implemented as ASP programs; we propose several different encodings, including a generalised program capable of encoding any qualitative calculus in ASP. All proposed encodings are experimentally evaluated using a real-world dataset. Experiment results show that the best performing implementation can scale up to an input of 250 trajectories for TC-6 and 150 trajectories for TC-10 for the problem of discovering a consistent configuration, a significant improvement compared to previous ASP implementations for similar qualitative spatial and temporal calculi. This manuscript is under consideration for acceptance in TPLP.Comment: Paper presented at the 34th International Conference on Logic Programming (ICLP 2018), Oxford, UK, July 14 to July 17, 2018, 20 pages, LaTeX, 16 figure

    From There to Here: Evaluating the Transition of an International Advanced Pharmacy Practice Experience in London

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    Purdue University College of Pharmacy offers an international advanced pharmacy practice experience (APPE) in London, England, where student pharmacists have the opportunity to work with pharmacy specialists at St. Bartholomew’s Hospital. The COVID-19 pandemic has significantly impacted travel across the world and created the need to transition this experience from in-person to virtual. Virtual interaction with international preceptors and revised research and clinical activities can provide students with a valuable learning experience
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