Objective: In this paper, we focus on the issue of providing physicians with the capability of representing in a seamless way both temporal aspects of multimedia semistructured data and their temporal presentation requirements.

Background: Semistructured data are data having some structure, that may be irregular or incomplete and does not necessarily conform to a fixed schema. Semistructured data often contain the description of histories of the considered real world. The eXtensible Markup Language (XML) is becoming a cross compatible and standardized means for representing semistructured clinical data. In the field of medical informatics, there are many ongoing activities concerning XML. In the field of multimedia database systems, the topic related to the integration of several media objects (with their temporal aspects) have been considered both for data modeling and querying issues and for modeling multimedia presentations.

Methodology: We first propose the Multimedia Temporal Graphical Model (MTGM), by representing a clinical database for cardiology patients undergoing cardiac angiographies and then describe it in a formal way. We deal with the problem of expressing MTGM data by XML and of managing MTGM clinical data through an XML-based system. We provide both a technique for translating (a part of) an MTGM database into an XML document and some techniques allowing us to obtain presentations defined by means of the Synchronized Multimedia Integration Language (SMIL) from MTGM presentations.

Results: MTGM allows one to represent and store clinical information in a semistructured, temporal, and multimedia database. The physician can define multimedia presentations based on the stored data. Multimedia presentations are then stored in the same MTGM database together with temporal clinical information and are thus represented according to the same data model. A prototype based on an XML native database system has been designed and implemented.

Discussion And Conclusions: In this work we have considered the theoretical and methodological issues concerning the definition of a general data model for describing temporal and multimedia features of semistructured clinical information. Other research and application oriented features, which have not been considered in MTGM, could be investigated for completing MTGM with regard to its applicability to clinical domains: MTGM does not allow one to express times at different levels of granularities, i.e. with different time units, or with indeterminacy; besides the considered valid time, it could be interesting to manage also other temporal dimensions such as the transaction and availability times. Besides being useful for managing multimedia data stored according to widely accepted standards as MPEG and DICOM, nowadays semistructured data, and XML in particular, are becoming the most important way for expressing and exchanging medical knowledge and data: MTGM can be considered as a data model allowing the seamless representation of both (multimedia and temporal) clinical data and knowledge.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.artmed.2004.11.003DOI Listing

Publication Analysis

Top Keywords

data
17
semistructured data
16
multimedia presentations
12
clinical data
12
data model
12
multimedia
11
mtgm
11
temporal
10
clinical
9
semistructured
8

Similar Publications

Background: Social media has become a widely used way for people to share opinions about health care and medical topics. Social media data can be leveraged to understand patient concerns and provide insight into why patients may turn to the internet instead of the health care system for health advice.

Objective: This study aimed to develop a method to investigate Reddit posts discussing health-related conditions.

View Article and Find Full Text PDF

Background: Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.

Objective: This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.

View Article and Find Full Text PDF

Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care.

View Article and Find Full Text PDF

Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.

Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.

View Article and Find Full Text PDF

Importance: A comprehensive lipid panel is recommended by guidelines to evaluate atherosclerotic cardiovascular disease risk, but uptake is low.

Objective: To evaluate whether direct outreach including bulk orders with and without text messaging increases lipid screening rates.

Design, Setting, And Participants: Pragmatic randomized clinical trial conducted from June 6, 2023, to September 6, 2023, at 2 primary care practices at an academic health system among patients aged 20 to 75 years with at least 1 primary care visit in the past 3 years who were overdue for lipid screening.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!