Tiago José Martins Oliveira

Development and implementation of clinical guidelines: An artificial intelligence perspective

Clinical practice guidelines in paper format are still the preferred form of delivery of medical knowledge and recommendations to healthcare professionals. Their current support and development process have well identified limitations to which the healthcare community has been continuously searching solutions. Artificial intelligence may create the conditions and provide the tools to address many, if not all, of these limitations.. This paper presents a comprehensive and up to date review of computer-interpretable guideline approaches, namely Arden Syntax, GLIF, PROforma, Asbru, GLARE and SAGE. It also provides an assessment of how well these approaches respond to the challenges posed by paper-based guidelines and addresses topics of Artificial intelligence that could provide a solution to the shortcomings of clinical guidelines. Among the topics addressed by this paper are expert systems, case-based reasoning, medical ontologies and reasoning under uncertainty, with a special focus on methodologies for assessing quality of information when managing incomplete information. Finally, an analysis is made of the fundamental requirements of a guideline model and the importance that standard terminologies and models for clinical data have in the semantic and syntactic interoperability between a guideline execution engine and the software tools used in clinical settings. It is also proposed a line of research that includes the development of an ontology for clinical practice guidelines and a decision model for a guideline-based expert system that manages non-compliance with clinical guidelines and uncertainty.

STUDYING THE EFFECTS OF STRESS ON NEGOTIATION BEHAVIOR

Negotiation is a collaborative activity that requires the participation of different parties whose behaviors influence the outcome of the whole process. The work presented here focuses on the identification of such behaviors and their impact on the negotiation process. The premise for this study is that identifying and cataloging the behavior of parties during a negotiation may help to clarify the role that stress plays in the process. To do so, an experiment based on a negotiation game was implemented. During this experiment, behavioral and contextual information about participants was acquired. The data from this negotiation game were analyzed in order to identify the conflict styles used by each party and to extract behavioral patterns from the interactions, useful for the development of plans and suggestions for the associated participants. The work highlights the importance of the knowledge about social interactions as a basis for informed decision support in situations of conflict.

Webifying the computerized execution of Clinical Practice Guidelines

The means through which Clinical Practice Guidelines are disseminated and become accessible are a crucial factor in their later adoption by health care professionals. Making these guidelines available in Clinical Decision Support Systems renders their application more personal and thus acceptable at the moment of care. Web technologies may play an important role in increasing the reach and dissemination of guidelines, but this promise remains largely unfulfilled. There is a need for a guideline computer model that can accommodate a wide variety of medical knowledge along with a platform for its execution that can be easily used in mobile devices. This work presents the CompGuide framework, a web-based and service-oriented platform for the execution of Computer-Interpretable Guidelines. Its architecture comprises different modules whose interaction enables the interpretation of clinical tasks and the verification of clinical constraints and temporal restrictions of guidelines represented in OWL. It allows remote guideline execution with data centralization, more suitable for a work environment where physicians are mobile and not bound to a machine. The solution presented in this paper encompasses a computer-interpretable guideline model, a web-based framework for guideline execution and an Application Programming Interface for the development of other guideline execution systems.

Moving towards a new paradigm of creation, dissemination, and application of computer-interpretable medical knowledge

Computer-interpretable guidelines (CIGs) exploit the scientific strength of evidence-based medicine to make recommendations available in clinical decision support systems. However, systems that deploy them have not been widely successful, in part due to the limitations of CIG frameworks in the adoption of inclusive and open technologies and the use of artificial intelligence techniques as tools to make their systems stronger and more adaptable. In this work, we propose a web-based CIG framework to tackle some of these challenges and facilitate the integration of CIG-based advice not only in the everyday activities of health care professionals, but also in the lives of whoever may need it.

Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

An interpretable guideline model to handle incomplete information

Healthcare institutions are both natural and emotionalstressful environments; indeed, the healthcare professionals may fall intopractices that may lead to medical errors, undesirable variations in clinical doing and defensive medicine. On the other hand, Clinical Guidelines may offer an effective response to these irregularities in clinical practice, if the issues concerning their availability during the clinical process are solved. Hence, in this work it is proposed a model intended to provide a formal representation of Computer-Interpretable Guidelines, in terms of the extensions of the predicates that make their universe of discourse, as well as a Decision Support System framework to handle Incomplete Information. It will be used an extension to the language of Logic Programming, where an assessment of the Quality-of-Information of the extensions of the predicates referred to above is paramount.

CompGuide: Acquisition and Editing of Computer-Interpretable Guidelines

The formalization of Clinical Practice Guidelines (CPGs) as Computer-Interpretable Guidelines (CIGs) has the potential to positively influence the behaviour of health practitioners by being available at the point and time of care. Existing tools for acquiring and editing CIGs for automatic interpretation present limitations in their ease of use and the support they offer to a CIG encoder. Besides characterizing these limitations and identifying improvements to include in future tools, this work describes the CompGuide Editor, a Protege tool for the management of CIGs that guides a user throughout the several steps of CIG encoding, without requiring the user to have programming knowledge, and through the use of interfaces that are simple and intuitive.

An alert mechanism for orientation systems based on Speculative computation

The role of assistive technologies is to help users with diminished capabilities in the fulfillment of their everyday tasks. One of such tasks is orientation. It is crucial for the autonomy of an individual and, at the same time, it is one of the most challenging tasks for an individual with cognitive disabilities. Existing solutions that tackle this problem are mostly concerned with guidance, tracking and the display of information. However, there is a dimension that has not been the object of concern in existing projects, the prediction of user actions. This work presents a Speculative Module for an orientation system that is used to alert the user for potential mistakes in his path, anticipating possible shifts in the wrong direction in critical points of the route. With this module, it becomes possible to issue warnings to the user and increase his attention so as to avoid a deviation from the correct path.

A prognosis system for colorectal cancer

The level of uncertainty and incompleteness in the information upon which healthcare professionals have to make judgments has been a subject of discussion in the past, and more nowadays, with the advent of the so-called Clinical Decision Support Systems. This work addresses uncertainty in the postoperative prognosis for colorectal cancer. The interdependence and synergistic effect of different clinical features comes into play when it is necessary to predict how a patient will react to this type of surgery. Using a probabilistic based knowledge representation, a decision support system was conceived in order to provide support for physicians under these circumstances, in particular to surgeons. The solution proposed is based on machine learning on records of cancer patients, incorporating explicit knowledge of experts about the domain. To facilitate access and thus increase its dissemination in the healthcare community, the system is integrated in a wider platform available through a web application.

Orientation system based on speculative computation and trajectory mining

Assistive technologies help users with disabilities (physical, sensory, intellectual) to perform tasks that were difficult or impossible to execute. Thus, the user autonomy is increased through this technology. Although some adaptation of the user might be needed, the effort should be minimum in order to use devices that convey assistive functionalities. In cognitive disabilities a common diminished capacity is orientation, which is crucial for the autonomy of an individual. There are several research works that tackle this problem, however they are essentially concerned with user guidance and application interface (display of information). The work presented herein aims to overcome these systems through a framework of Speculative Computation, which adds a prediction feature for the next move of the user. With an anticipation feature and a trajectory mining module the user is guided through a preferred path receiving anticipated alerts before a possible shift in the wrong direction.