Rule-based Formalization of Eligibility Criteria for Clinical Trials

Abstract. In this paper, we propose a rule-based formalization of eli-gibility criteria for clinical trials. The rule-based formalization is imple-mented by using the logic programming language Prolog. Compared with existing formalizations such as pattern-based and script-based languages, the rule-based formalization has the advantages of being declarative, ex-pressive, reusable and easy to maintain. Our rule-based formalization is based on a general framework for eligibility criteria containing three types of knowledge: (1) trial-specific knowledge, (2) domain-specific knowledge and (3) common knowledge. This framework enables the reuse of several parts of the formalization of eligibility criteria. We have implemented the proposed rule-based formalization in SemanticCT, a semantically-enabled system for clinical trials, showing the feasibility of using our rule-based formalization of eligibility criteria for supporting patient re-cruitment in clinical trial systems.

Thirty years of artificial intelligence in medicine (AIME) conferences: A review of research themes

Over the past 30 years, the international conference on Artificial Intelligence in MEdicine (AIME) has been organized at different venues across Europe every 2 years, establishing a forum for scientific exchange and creating an active research community. The Artificial Intelligence in Medicine journal has published theme issues with extended versions of selected AIME papers since 1998

Hedging Exchange Rate Risks

Risks associated with fluctuating exchange rates affect investment cost and investor profitability. Approximately 50% of firms in emerging markets have significant exposure to fluctuating exchange rates. Grounded in principal-agent theory (PAT), the purpose of this case study was to explore hedging strategies to mitigate risks of fluctuating exchange rates. The population comprised a census sampling of 12 bank hedgers (risk managers and controllers) in Dar es Salaam in Tanzania, East Africa. Data collection involved semistructured interviews, casual observations of the work environment, and analysis of reports including risk management, internal control, and compliance policies. Data were analyzed by coding and grouping narrative segments and significant statements into themes of participants\u27 experience in hedging exchange rate risks. Method triangulation and member checking were used to increase the trustworthiness of interpretations. Four themes emerged directly related to the PAT conceptual framework: training and skills development, management of hedging strategies and contracts, corporate governance, and benefits to management and the organization through effective compensation programs. A focus on training and skill development helped develop appropriate exchange rate hedging strategies and corporate governance improved compliance with laws, regulations, and policies. The benefits of effective hedging strategies include a reduction in cost and increase in profitability. The findings may help improve the soundness of professional hedging practices, which will increase the stability of the Tanzanian banking system

Rule-based formalization of eligibility criteria for clinical trials (abstract)

In this extended abstract, we propose a rule-based formalization of eligibility criteria for clinical trials. The rule-based formalization is implemented by using the logic programming language Prolog. Compared with existing formalizations such as pattern-based and script-based languages, the rule-based formalization has the advantages of being declarative, expressive, reusable and easy to maintain. Our rule-based formalization is based on a general framework for eligibility criteria containing three types of knowledge: (1) trial-specific knowledge, (2) domain-specific knowledge and (3) common knowledge. This framework enables the reuse of several parts of the formalization of eligibility criteria. We have implemented the proposed rule-based formalization in SemanticCT, a semantically-enabled system for clinical trials, showing the feasibility of using our rule-based formalization of eligibility criteria for supporting patient recruitment in clinical trial systems