An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

A funny thing happened on the way to the forum: Electronic discussion and foreign language learning

Amongst the opportunities for cross-cultural contact created by the burgeoning use of the Internet are those provided by electronic discussion lists. This study looks at what happens when language students venture out of the classroom (virtual or otherwise) to participate in on-line discussion groups with native speakers. Responses to messages and commentary by moderators and other participants on the (in) appropriateness of contributions allow us to determine what constitutes successful participation and to make suggestions regarding effective teaching strategies for this medium. A case study examines the threads started by four anglophone students of French when they post messages to a forum on the Web site of the French newspaper Le Monde. Investigation of these examples points to the ways in which electronic discussion inflects and is inflected by cultural and generic expectations. We suggest that successful participation on Internet fora depends on awareness of such cultural and generic mores and an ability to work within and/or with them. Teachers therefore need to find ways in which students can be sensitized to such issues so that their participation in such electronic discussion is no longer seen as linguistic training, but as engagement with a cultural practice.