Prediction of Length of Hospital Stay in Preterm Infants - A Case-Based Reasoning View

The length of stay of preterm infants in a neonatology service has become an issue of a growing concern, namely considering, on the one hand, the mothers and infants health conditions and, on the other hand, the scarce healthcare facilities own resources. Thus, a pro-active strategy for problem solving has to be put in place, either to improve the quality-of-service provided or to reduce the inherent financial costs. Therefore, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a case-based problem solving methodology to computing, that caters for the handling of incomplete, unknown, or even contradictory in-formation. The proposed model has been quite accurate in predicting the length of stay (overall accuracy of 84.9%) and by reducing the computational time with values around 21.3%.

A Case-Based Approach to Nosocomial Infection Detection

The nosocomial infections are a growing concern because they affect a large number of people and they increase the admission time in healthcare facilities. Additionally, its diagnosis is very tricky, requiring multiple medical exams. So, this work is focused on the development of a clinical decision support system to prevent these events from happening. The proposed solution is unique once it caters for the explicit treatment of incomplete, unknown, or even contradictory information under a logic programming basis, that to our knowledge is something that happens for the first time.

Waiting Time Screening in Diagnostic Medical Imaging - A Case-Based View

Due to the high standards expected from diagnostic medical imaging, the analysis of information regarding waiting lists via different information systems is of utmost importance. Such analysis, on the one hand, may improve the diagnostic quality and, on the other hand, may lead to the reduction of waiting times, with the concomitant increase of the quality of services and the reduction of the inherent financial costs. Hence, the purpose of this study is to assess the waiting time in the delivery of diagnostic medical imaging services, like computed tomography and magnetic resonance imaging. Thereby, this work is focused on the development of a decision support system to assess waiting times in diagnostic medical imaging with recourse to operational data of selected attributes extracted from distinct information systems. The computational framework is built on top of a Logic Programming Case-base Reasoning approach to Knowledge Representation and Reasoning that caters for the handling of in-complete, unknown, or even self-contradictory information.

A Case Based approach to assess Waiting Time Prediction at an Intensive Care Unity

Waiting time at an intensive care unity stands for a key feature in the assessment of healthcare quality. Nevertheless, its estimation is a difficult task, not only due to the different factors with intricate relations among them, but also with respect to the available data, which may be incomplete, self-contradictory or even unknown. However, its prediction not only improves the patients’ satisfaction but also enhance the quality of the healthcare being provided. To fulfill this goal, this work aims at the development of a decision support system that allows one to predict how long a patient should remain at an emergency unit, having into consideration all the remarks that were just stated above. It is built on top of a Logic Programming approach to knowledge representation and reasoning, complemented with a Case Base approach to computing.

A case-based reasoning view of thrombophilia risk

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states that increase the risk of venous and arterial thromboses. Indeed, venous thromboembolism is often a chronic illness, mainly in deep venous thrombosis and pulmonary embolism, requiring lifelong prevention strategies. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a logic programming approach to knowledge representation and reasoning, complemented with a case-based approach to computing. The proposed model has been quite accurate in the assessment of thrombophilia predisposition risk, since the overall accuracy is higher than 90% and sensitivity ranging in the interval [86.5%, 88.1%]. The main strength of the proposed solution is the ability to deal explicitly with incomplete, unknown, or even self-contradictory information.

Chest Breadths to Predict Individuals' Age - A Case Based View

It is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an Artificial Intelligence grounded decision support system to predict individual’s age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The accuracy of the proposed model is satisfactory, close to 90%.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

Age Prediction through Pelvis X-Ray Images - A Case Based approach to Problem Solving

It is well known that the dimensions of the pelvic bones depend on the gender and vary with the age of the individual. Indeed, and as a matter of fact, this work will focus on the development of an intelligent decision support system to predict individual’s age based on pelvis’ dimensions criteria. On the one hand, some basic image processing technics were applied in order to extract the relevant features from pelvic X-rays. On the other hand, the computational framework presented here was built on top of a Logic Programming approach to knowledge representation and reasoning, that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.

Inquiring how a lecturer keeps learning about their teaching:a personal case history on reflective imagination

In order to reverse the use of lecture-based teaching, it is argued that personal reflection can be used as part of the quality assurance process. This paper proposes one response to personal reflection - reflective imagination, which is summarised as an action plan with six activities. It combines two conceptual issues raised in the US, the need to think creatively about learning and the reflective mindset, and one issue raised in the UK, cultivating the entrepreneurial imagination. Reflective imagination is linked to wider social science research, the place of self and reflexivity in scholarship. Finally, a personal history case study is presented which records a visit to Harvard Business School. The visit implements the six activities associated with reflective imagination. This is a method paper exploring reflective imagination.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.

A shift from passive teaching at medical conferences to more interactive methods improves physician learning

Conferences that deliver interactive sessions designed to enhance physician participation, such as role play, small discussion groups, workshops, hands-on training, problem- or case-based learning and individualised training sessions, are effective for physician education.

Surgical management of glomus jugulare tumors: a proposal for approach selection based on tumor relationships with the facial nerve Clinical article

Object. The goal of this paper is to analyze the extension and relationships of glomus jugulare tumor with the temporal bone and the results of its surgical treatment aiming at preservation of the facial nerve. Based on the tumor extension and its relationships with the facial nerve, new criteria to be used in the selection of different surgical approaches are proposed. Methods. Between December 1997 and December 2007, 34 patients (22 female and 12 male) with glomus jugulare tumors were treated. Their mean age was 48 years. The mean follow-up was 52.5 months. Clinical findings included hearing loss in 88%, swallowing disturbance in 50%, and facial nerve palsy in 41%. Magnetic resonance imaging demonstrated a mass in the jugular foramen in all cases, a mass in the middle ear in 97%, a cervical mass in 85%, and an intradural mass in 41%. The tumor was supplied by the external carotid artery in all cases, the internal carotid artery in 44%, and the vertebral artery in 32%. Preoperative embolization was performed in 15 cases. The approach was tailored to each patient, and 4 types of approaches were designed. The infralabyrinthine retrofacial approach (Type A) was used in 32.5%; infralabyrinthine pre- and retrofacial approach without occlusion of the external acoustic meatus (Type B) in 20.5%; infralabyrinthine pre- and retrofacial approach with occlusion of the external acoustic meatus (Type C) in 41 W. and the infralabyrinthine approach with transposition of the facial nerve and removal of the middle ear structures (Type D) in 6% of the patients. Results. Radical removal was achieved in 91% of the cases and partial removal in 9%. Among 20 patients without preoperative facial nerve dysfunction, the nerve was kept in anatomical position in 19 (95%), and facial nerve function was normal during the immediate postoperative period in 17 (85%). Six patients (17.6%) had a new lower cranial nerve deficit, but recovery of swallowing function was adequate in all cases. Voice disturbance remained in all 6 cases. Cerebrospinal fluid leakage occurred in 6 patients (17.6%), with no need for reoperation in any of them. One patient died in the postoperative period due to pulmonary complications. The global recovery, based on the Karnofsky Performance Scale (KPS), was 100% in 15% of the patients, 90% in 45%, 80% in 33%, and 70% in 6%. Conclusions. Radical removal of glomus jugulare tumor can be achieved without anterior transposition of the facial nerve. The extension of dissection, however, should be tailored to each case based on tumor blood supply, preoperative symptoms, and tumor extension. The operative field provided by the retrofacial infralabyrinthine approach, or the pre- and retrofacial approaches. with or without Closure of the external acoustic meatus, allows a wide exposure of the jugular foramen area. Global functional recovery based on the KPS is acceptable in 94% of the patients. (DOI: 10.3171/2008.10.JNS08612)

Ways of using evidence-based medicine in general practice

General practitioners wanting to practise evidence-based medicine (EBM) are constrained by time factors and the great diversity of clinical problems they deal with. They need experience in knowing what questions to ask, in locating and evaluating the evidence, and in applying it. Conventional searching for the best evidence can be achieved in daily general practice. Sometimes the search can be performed during the consultation, but more often it can be done later and the patient can return for the result. Case-based journal clubs provide a supportive environment for GPs to work together to find the best evidence at regular meetings. An evidence-based literature search service is being piloted to enhance decision-making for individual patients. A central facility provides the search and interprets the evidence in relation to individual cases. A request form and a results format make the service akin to pathology testing or imaging. Using EBM in general practice appears feasible. Major difficulties still exist before it can be practised by all GPs, but it has the potential to change the way doctors update their knowledge.

Short report: Molecular genetic characterization of an unusually severe case of hydatid disease in Alaska caused by the cervid strain of Echinococcus granulosusi

Distinct Echinococcus granulosus life cycle patterns have been described in North America: domestic and sylvatic. Gene sequences of the sylvatic E. granulosus indicate that it represents a separate variant. Case-based data have suggested that the course of sylvatic disease is less severe than that of domestic disease. which led to the recommendation to treat cystic echinococcosis patients in the Arctic by careful medical management rather than by aggressive surgery. We recently reported the first two documented E. granalosus human cases in Alaska with accompanying severe sequelae. Here we describe the results of molecular genetic analysis of the cyst material of one of the subjects that supported identification of the parasite as the sylvatic (cervid) strain and not the domestic (common sheep strain), which was initially thought to be implicated in these unusually severe Alaskan cases.