The Experts below are selected from a list of 153 Experts worldwide ranked by ideXlab platform
Henry P. Lundsgaarde - One of the best experts on this subject based on the ideXlab platform.
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Evaluating medical Expert Systems.
Social Science & Medicine, 2002Co-Authors: Henry P. LundsgaardeAbstract:Approximately 90% of all computerized medical Expert Systems have not been evaluated in clinical environments. This paper: (1) identifies the principal methods used to assess the performance of medical Expert Systems in both laboratory and clinical settings, (2) describes the different research strategies used in the evaluation of medical Expert Systems at different development stages, and (3) discusses past evaluation efforts in relationship to future applications of different decision support technologies and Expert Systems in health care.
Randolph A. Miller - One of the best experts on this subject based on the ideXlab platform.
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Desiderata for product labeling of medical Expert Systems
International Journal of Medical Informatics, 1997Co-Authors: Antoine Geissbühler, Randolph A. MillerAbstract:The proliferation and increasing complexity of medical Expert Systems raise ethical and legal concerns about the ability of practitioners to protect their patients from defective or misused software. Appropriate product labeling of Expert Systems can help clinical users to understand software indications and limitations. Mechanisms of action and knowledge representation schema should be explained in layperson's terminology. User qualifications and resources available for acquiring the skills necessary to understand and critique the system output should be listed. The processes used for building and maintaining the system's knowledge base are key determinants of the product's quality, and should be carefully documented. To meet these desiderata, a printed label is insufficient. The authors suggest a new, more active, model of product labeling for medical Expert Systems that involves embedding 'knowledge of the knowledge base', creating user-specific data, and sharing global information using the Internet.
Antoine Geissbühler - One of the best experts on this subject based on the ideXlab platform.
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Desiderata for product labeling of medical Expert Systems
International Journal of Medical Informatics, 1997Co-Authors: Antoine Geissbühler, Randolph A. MillerAbstract:The proliferation and increasing complexity of medical Expert Systems raise ethical and legal concerns about the ability of practitioners to protect their patients from defective or misused software. Appropriate product labeling of Expert Systems can help clinical users to understand software indications and limitations. Mechanisms of action and knowledge representation schema should be explained in layperson's terminology. User qualifications and resources available for acquiring the skills necessary to understand and critique the system output should be listed. The processes used for building and maintaining the system's knowledge base are key determinants of the product's quality, and should be carefully documented. To meet these desiderata, a printed label is insufficient. The authors suggest a new, more active, model of product labeling for medical Expert Systems that involves embedding 'knowledge of the knowledge base', creating user-specific data, and sharing global information using the Internet.
Haris Pandza - One of the best experts on this subject based on the ideXlab platform.
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Expert Systems in pulmonology
Medicinski arhiv, 1999Co-Authors: Izet Masic, Ridanović Z, Haris PandzaAbstract:Expert Systems are software Systems that can successfully compare to human Experts. Their purpose is mostly advisory. Besides, they give explanation and advices to human Experts when performing certain tasks. They are intelligent information Systems, and are capable to explain and justify their conclusions. Knowledge Systems are smaller software Systems, and are usually less successful than human Experts. Main reasons for Expert Systems development in medicine are: need for justification of decisions, need for enhancing performances in many uncertain relations; need for explaining of decision making process++ etc. One of the reasons of developing knowledge-based Systems was that conventional statistic formalisms have not provided satisfactory solutions in medical decision making (MDM). Also, today, the relations between cases and conclusions are not universally valid. So, few causes can provide the same conclusion. Besides, data are not necessarily absolutely accurate. The area of applying Expert Systems is very wide: diagnosis, prognosis, education, managing etc. Basic structure of Expert system consists of: knowledge, data base, inferring mechanism, explaining mechanism and user-interface. In this paper we presented several Expert Systems which are actually used in practice, especially in internal disciplines: Internist, Mycin, Onkocyn, DXplain.
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Expert Systems in medicine
Medicinski arhiv, 1999Co-Authors: Haris Pandza, I MasićAbstract:Expert Systems are software Systems developed using different techniques of artificial intelligence that can act parallel to the "human" Experts. The main role is consultative These are intelligent information Systems that use more then 2000 different rules and that are capable to explain their decisions. Databases of such Systems can contain huge number of data about different diseases and therapy modalities. In development of Medical Expert Systems the rule of human Experts is crucial. The teams of such Experts are developing Expert system considering the changes in medicine. Several modes of work are available. Consultation mode is used in cases when the diagnosis and treatment is uncertain. The human enter data about symptoms and signs of some medical disorder and computer creates a list of possible diagnosis and additional diagnostic test. Therapy for condition is also suggested. Simulation mode can simulate virtual patient and allows students and doctors to learn mode about some medical conditions. Some Expert system as HEPAT can make "Decision Tree" for new-born jaundice. Similar Expert system will be available in future for other fields in medicine. Some of Expert Systems are described in article.
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Medical Expert Systems
Medicinski arhiv, 1995Co-Authors: Izet Masic, Ridanović Z, Haris PandzaAbstract:Expert Systems are software Systems that can successfully compare to human Experts. Their purpose is mostly advisory. Besides, they give explanation and advice to human Experts when performing certain tasks. They are intelligent information Systems, and are capable to explain and justify their conclusions. Knowledge Systems are smaller software Systems, and are usually less successful than human Experts. Main reasons for Expert Systems development in medicine are: need for justification of decisions, need for enhancing performances in many uncertain relations; need for explaining of decision making process etc. One of the reasons of developing knowledge-based Systems was that conventional statistic formalisms have not provided satisfactory solutions in medical decision making (MDM). Also, today, the relations between cases and conclusions are not universally valid. So, few causes can provide the same conclusion. Besides, data are not necessarily absolutely accurate. The area of applying Expert Systems is very wide: diagnosis, prognosis, self-education, directing etc. Basic structure of Expert system consists of: knowledge, data base, inferring mechanism, explaining mechanism and user-interface. Though, Expert Systems also have certain bad features: primarily, they are not physicians i.e. they can not examine a patient. Furthermore, Expert system that is good for one certain area is often not good for another one. There are some cases, when these Systems can confuse a physician and make him to make a wrong decision. This occurs very often in two specific cases: when the clinical situation is urgent; and when accuracy of clinical information is not definite.
Lorrie Schultz - One of the best experts on this subject based on the ideXlab platform.
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Expert Systems in process control
Isa Transactions, 2003Co-Authors: David Rehbein, Steve Thorp, Dave Deitz, Lorrie SchultzAbstract:Abstract This paper discusses the history of Expert Systems, their migration to the process control room, and their application in process industries. Two case studies that discuss the justification, development, and implementation of Expert system applications are presented. The authors' views on the future of Expert Systems in the process control environment are introduced in the Summary/Conclusions section of the report.
