INTRODUCTION As the dust clears from the Food and Drug Administration’s (FDA) release of its longanticipatedFinalGuidanceonMobileMedicalApplications inSeptember2013(MMA Final Guidance),1 the attention of industry and regulatory actors may turn to a significant health technology area explicitly excluded from the MMA Final Guidance— clinical decision support (CDS) software.TheFDAplans to release ...

Early diagnosis of skin cancer is one of the greatest challenges due to lack of experience of general practitioners (GPs). This paper presents a clinical decision support system aimed to save lives, time and resources in the early diagnostic process. Segmentation, feature extraction, and lesion classification are the important steps in the proposed system. The system analyses the images to extr...

Both clinical management of patients and clinical research are essentially time-oriented endeavors. In this paper, I emphasize the crucial role of temporal-reasoning and temporal-maintenance tasks for modern medical information and decision support systems. Both tasks are important for management of clinical data, but the first is often approached mainly through artificial-intelligence methodol...

The European STREP project HEARTFAID aims at defining an innovative platform of services able to intelligently support clinical operators in the daily management of heart failure patients. The core of the platform intelligence is a Clinical Decision Support System, developed by integrating innovative knowledge representation techniques and hybrid reasoning methods, and including advanced tools ...

Biology in general and medicine and healthcare in particular are facing the critical challenge of exponentially increasing data availability. The core of this challenge is putting these data to work through computer-based knowledge extraction methods. In the medical context this could take the form of medical decision support systems for diagnosis, prognosis or general management. Arguably, one...

Clinical decision support systems are important healthcare systems that help in improving healthcare quality and in reducing cost. These systems have multiple levels of outcomes on the individual, group, organization, and society levels. However, despite the abundant studies conducted to evaluate CDSS, most of these studies failed to recognize these multiple levels of impact and mostly focused ...

Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (...

A lack of acceptance has hindered the widespread adoption and implementation of clinical prediction rules (CPRs). The use of clinical decision support systems (CDSSs) has been advocated as one way of facilitating a broader dissemination and validation of CPRs. This requires computable models of clinical evidence based on open standards rather than closed proprietary content. The on-going TRANSF...

In the daily routine of a clinical microbiological laboratory, pathogens can be detected in several ways. Diagnostics of infectious diseases require a strategic approach, since the etiological agent can be of bacterial, viral, fungal or protozoan origin, frequently sharing an identical syndrome. A complicating factor is that the clinical sample, sent to the laboratory, can be severely contamina...