Abstract Objective Clinicians and medical researchers alike require useful, intuitive, and intelligent tools to process large amounts of time-oriented multiple-patient data from multiple sources. For ...analyzing the results of clinical trials or for quality assessment purposes, an aggregated view of a group of patients is often required. To meet this need, we designed and developed the VISualizatIon of Time-Oriented RecordS (VISITORS) system, which combines intelligent temporal analysis and information visualization techniques. The VISITORS system includes tools for intelligent retrieval, visualization, exploration, and analysis of raw time-oriented data and derived (abstracted) concepts for multiple patient records. To derive meaningful interpretations from raw time-oriented data (known as temporal abstraction s), we used the knowledge-based temporal-abstraction method. Methods The main module of the VISITORS system is an interactive, ontology-based exploration module, which enables the user to visualize raw data and abstract (derived) concepts for multiple patient records, at several levels of temporal granularity; to explore these concepts; and to display associations among raw and abstract concepts. A knowledge-based delegate function is used to convert multiple data points into one delegate value representing each temporal granule. To select the population of patients to explore, the VISITORS system includes an ontology-based temporal-aggregation specification language and a graphical expression-specification module. The expressions, applied by an external temporal mediator, retrieve a list of patients, a list of relevant time intervals, and a list of time-oriented patients’ data sets, by using an expressive set of time and value constraints. Results Functionality and usability evaluation of the interactive exploration module was performed on a database of more than 1000 oncology patients by a group of 10 users—five clinicians and five medical informaticians. Both types of users were able in a short time (mean of 2.5 ± 0.2 min per question) to answer a set of clinical questions, including questions that require the use of specialized operators for finding associations among derived temporal abstractions, with high accuracy (mean of 98.7 ± 2.4 on a predefined scale from 0 to 100). There were no significant differences between the response times and between accuracy levels of the exploration of the data using different time lines, i.e., absolute (i.e., calendrical) versus relative (referring to some clinical key event). A system usability scale (SUS) questionnaire filled out by the users demonstrated the VISITORS system to be usable (mean score for the overall group: 69.3), but the clinicians’ usability assessment was significantly lower than that of the medical informaticians. Conclusions We conclude that intelligent visualization and exploration of longitudinal data of multiple patients with the VISITORS system is feasible, functional, and usable.
Objective To test the feasibility of classifying emergency department patients into severity grades using data mining methods.
Design Emergency department records of 402 patients were classified ...into five severity grades by two expert physicians. The Naïve Bayes and C4.5 algorithms were applied to produce classifiers from patient data into severity grades. The classifiers' results over several subsets of the data were compared with the physicians' assessments, with a random classifier, and with a classifier that selects the maximal‐prevalence class.
Measurements Positive predictive value, multiple‐class extensions of sensitivity and specificity combinations, and entropy change.
Results The mean accuracy of the data mining classifiers was 52.94 ± 5.89%, significantly better (P < 0.05) than the mean accuracy of a random classifier (34.60 ± 2.40%). The entropy of the input data sets was reduced through classification by a mean of 10.1%. Allowing for classification deviations of one severity grade led to mean accuracy of 85.42 ± 1.42%. The classifiers' accuracy in that case was similar to the physicians' consensus rate. Learning from consensus records led to better performance. Reducing the number of severity grades improved results in certain cases. The performance of the Naïve Bayes and C4.5 algorithms was similar; in unbalanced data sets, Naïve Bayes performed better.
Conclusions It is possible to produce a computerized classification model for the severity grade of triage patients, using data mining methods. Learning from patient records regarding which there is a consensus of several physicians is preferable to learning from each physician's patients. Either Naïve Bayes or C4.5 can be used; Naïve Bayes is preferable for unbalanced data sets. An ambiguity in the intermediate severity grades seems to hamper both the physicians' agreement and the classifiers' accuracy.
•GoldNet- guides the user step-by-step when performing online operations•A user study was conducted on 30 novice older adults attending a daycare center•GoldNet was effective as a human tutor and ...significantly better than video guidance•GoldNet accelerated the learning process, providing visual cues and instructions•Learning was faster for the younger age group and most of it resulted from practice
Internet use by older adults is increasing and has the potential to improve their mental and social wellbeing, however it is still low compared to other age groups for various online activities. The objective of this study was to develop and evaluate a computerized expert system, GoldNet, which functions as a human expert and guides the user, step-by-step and in real time, when performing online operations. A user study was conducted on 30 older adults (over 65 years old) that attend an adult daycare center. The participants were all novice users with no prior experience using the Internet. A stratified randomized between participants experimental design was used to evaluate users' performance and satisfaction before and after receiving guidance, after practice, and after a two-week period without controlled practice. Participants were assigned to one of three study groups according to the guidance they received: GoldNet guides, video guidance, or guidance from a personal human tutor. During the experiment participants’ eye movements were monitored. The results indicate that by using GoldNet's automated guides, older adults can perform online tasks with high effectiveness, efficiency, and user satisfaction, performing comparably to users trained by a personal human tutor and significantly better than users relying on video guidance. GoldNet was also found beneficial as a refresher tool after a period without controlled training.
Purpose
The purpose of this paper is to describe a new ontological content‐based filtering method for ranking the relevance of items for readers of news items, and its evaluation. The method has been ...implemented in ePaper, a personalised electronic newspaper prototype system. The method utilises a hierarchical ontology of news; it considers common and related concepts appearing in a user's profile on the one hand, and in a news item's profile on the other hand, and measures the “hierarchical distances” between these concepts. On that basis it computes the similarity between item and user profiles and rank‐orders the news items according to their relevance to each user.
Design/methodology/approach
The paper evaluates the performance of the filtering method in an experimental setting. Each participant read news items obtained from an electronic newspaper and rated their relevance. Independently, the filtering method is applied to the same items and generated, for each participant, a list of news items ranked according to relevance.
Findings
The results of the evaluations revealed that the filtering algorithm, which takes into consideration hierarchically related concepts, yielded significantly better results than a filtering method that takes only common concepts into consideration. The paper determined a best set of values (weights) of the hierarchical similarity parameters. It also found out that the quality of filtering improves as the number of items used for implicit updates of the profile increases, and that even with implicitly updated profiles, it is better to start with user‐defined profiles.
Originality/value
The proposed content‐based filtering method can be used for filtering not only news items but items from any domain, and not only with a three‐level hierarchical ontology but any‐level ontology, in any language.
Empirical evaluations of visual encodings for analytical tasks inform the design of automatic presentation systems. This study compares anomaly detection effectiveness, efficiency, and user ...satisfaction using tabular visualization and graphical representation of position, size, and color saturation visualizations and the visualizations' relative ranking. In our user study analysts used the visualizations to detect anomalies in bivariate quantitative, ordinal, and nominal real data, before and after training. Consistent with Mackinlay ranking of the visual encodings' effectiveness, the results showed that for all data types, position visualization outperformed size and color saturation visualizations on all measures, before and after training. The use of position visualization after training was as effective as using the table visualization for all data types but significantly easier to use and preferable. Furthermore, the average anomaly detection time was at least three times shorter when using position visualization compared to table visualization for ordinal and quantitative data.
Mining Eye-Tracking Data for Text Summarization Taieb-Maimon, Meirav; Romanovski-Chernik, Aleksandr; Last, Mark ...
International journal of human-computer interaction,
07/2023, Volume:
ahead-of-print, Issue:
ahead-of-print
Journal Article
Peer reviewed
Open access
In this study, we introduce and evaluate a novel extractive text summarization methodology, "SummarEyes," based on the visual interaction of the user with the text, using eye-tracking data, as ...opposed to the traditional approaches based on analysis of textual content only. We conducted a large-scale user study aiming to collect eye-tracking data while reading the text to be summarized. We utilized various user's implicit attention metrics to generate novel eye-tracking-based text summarization models and compared them both to eye-tracking models typically using only a single feature of the gaze duration and to traditional, as well as state-of-the-art summarization methods, based solely on textual features. The models' quality was evaluated in terms of ROUGE scores using intrinsic evaluation on the datasets we had generated, relating gaze behavior to personalized and DUC gold-standard summaries. The experimental results showed that "SummarEyes" significantly outperformed the other summarizers in predicting both the user's personalized summarization and the generic gold standard summaries. With the increasing availability of eye-tracking technology, this research can lead to a new generation of effective user-centric text summarization tools.
An intervention study was conducted to examine the effectiveness of an innovative self-modeling photo-training method for reducing musculoskeletal risk among office workers using computers. Sixty ...workers were randomly assigned to either: 1) a control group; 2) an office training group that received personal, ergonomic training and workstation adjustments or 3) a photo-training group that received both office training and an automatic frequent-feedback system that displayed on the computer screen a photo of the worker’s current sitting posture together with the correct posture photo taken earlier during office training. Musculoskeletal risk was evaluated using the Rapid Upper Limb Assessment (RULA) method before, during and after the six weeks intervention. Both training methods provided effective short-term posture improvement; however, sustained improvement was only attained with the photo-training method. Both interventions had a greater effect on older workers and on workers suffering more musculoskeletal pain. The photo-training method had a greater positive effect on women than on men.
► We present a training method using web-cam photos for reducing musculoskeletal risk. We compared three groups: photo-training, office ergonomic training and control. ► Both training methods provided effective short-term posture improvement. ► Sustained improvement was only attained with the photo-training method. ► The photo-training method had a greater positive effect on women than on men.
► Similan2, a similarity search interface for event sequences ► Similarity measure called M&M measure v.2 for finding similar event sequences. ► Controlled experiment comparing exact match and ...similarity searches ► Summary of advantages and disadvantages of each approach ► Recommendations for the design of a hybrid approach combining exact match and similarity search interfaces.
Specifying event sequence queries is challenging even for skilled computer professionals familiar with SQL. Most graphical user interfaces for database search use an exact match approach, which is often effective, but near misses may also be of interest. We describe a new similarity search interface, in which users specify a query by simply placing events on a blank timeline and retrieve a similarity-ranked list of results. Behind this user interface is a new similarity measure for event sequences which the users can customize by four decision criteria, enabling them to adjust the impact of missing, extra, or swapped events or the impact of time shifts. We describe a use case with Electronic Health Records based on our ongoing collaboration with hospital physicians. A controlled experiment with 18 participants compared exact match and similarity search interfaces. We report on the advantages and disadvantages of each interface and suggest a hybrid interface combining the best of both.
PDF