Biomedical subjects

O R Sheng

Publications and source records attributed to O R Sheng.

4 recordsLinked to original sources

PubMed2001

A knowledge-based system for patient image pre-fetching in heterogeneous database environments--modeling, design, and evaluation.

When performing primary reading on a newly taken radiological examination, a radiologist often needs to reference relevant prior images of the same patient for confirmation or comparison purposes. Support of such image references is of clinical importance and may have significant effects on radiologists' examination reading efficiency, service quality, and work satisfaction. To effectively support such image reference needs, we proposed and developed a knowledge-based patient image pre-fetching system, addressing several challenging requirements of the application that include representation and learning of image reference heuristics and management of data-intensive knowledge inferencing. Moreover, the system demands an extensible and maintainable architecture design capable of effectively adapting to a dynamic environment characterized by heterogeneous and autonomous data source systems. In this paper, we developed a synthesized object-oriented entity- relationship model, a conceptual model appropriate for representing radiologists' prior image reference heuristics that are heuristic oriented and data intensive. We detailed the system architecture and design of the knowledge-based patient image pre-fetching system. Our architecture design is based on a client-mediator-server framework, capable of coping with a dynamic environment characterized by distributed, heterogeneous, and highly autonomous data source systems. To adapt to changes in radiologists' patient prior image reference heuristics, ID3-based multidecision-tree induction and CN2-based multidecision induction learning techniques were developed and evaluated. Experimentally, we examined effects of the pre-fetching system we created on radiologists' examination readings. Preliminary results show that the knowledge-based patient image pre-fetching system more accurately supports radiologists' patient prior image reference needs than the current practice adopted at the study site and that radiologists may become more efficient, consultatively effective, and better satisfied when supported by the pre-fetching system than when relying on the study site's pre-fetching practice.

Artificial Intelligence↗

PubMed1999

A knowledge-based patient image prefetching system: design, evaluation and management.

One fundamental clinical role of radiologists is to provide attending physicians with interpretations of an individual patient's radiological images essential to a treatment plan or overall patient management. Interpreting images from a newly taken radiological examination often requires reference to prior images of the same patient to establish a baseline from which to confirm a suspected pathological process or injury or to evaluate the progression of one that has been identified. Such image references are crucial to the radiologist's examination reading and when inappropriately supported can result in prolonged reading time, decreased report quality, and frustration. To address the problem of inadequate image prefetching methods used by many health care organizations, we took a knowledge-based approach and developed Image Retrieval Expert System (IRES), which incorporates relevant medical/radiological knowledge and contains image retrieval heuristics commonly shared by radiologists. This article describes the design of IRES, highlights its preliminary evaluation results, and discusses issues important for managing this and similar technologies in a health care organization.

Artificial Intelligence↗

PubMed1998

A survey of physicians' acceptance of telemedicine.

Physicians' acceptance of telemedicine is an important managerial issue facing health-care organizations that have adopted, or are about to adopt, telemedicine. Most previous investigations of the acceptance of telemedicine have lacked theoretical foundation and been of limited scope. We examined technology acceptance and usage among physicians and specialists from 49 clinical departments at eight public tertiary hospitals in Hong Kong. Out of the 1021 questionnaires distributed, 310 were completed and returned, a 30% response rate. The preliminary findings suggested that use of telemedicine among clinicians in Hong Kong was moderate. While 18% of the respondents were using some form of telemedicine for patient care and management, it accounted for only 6.3% of the services provided. The intensity of their technology usage was also low, accounting for only 6.8% of a typical telemedicine-assisted service. These preliminary findings have managerial implications.

Attitude of Health Personnel↗

PubMed1997

Urban teleradiology in Hong Kong.

We investigated four major teleradiology programmes in Hong Kong. We analysed the overall organizational background of each programme, the context of its implementation, the choice of technology and the decision-making process, and the subsequent dissemination of the technology. Our review suggests that the success of a telemedicine programme is contingent not only on good technology but also on effective management of issues pertaining to human and organizational factors. At the departmental level, the context of the implementation of telemedicine is crucial. At the institutional level, success depends on planning and management. At the professional level, continued education, periodic meetings and seminars are all effective means of promoting telemedicine among health-care professionals and administrators. At the national level, the Hong Kong experience suggests that telemedicine can be effectively developed by starting with urban-based programmes.

Hong Kong↗