Biomedical subjects

D M Pisanelli

Publications and source records attributed to D M Pisanelli.

22 records · Page 2Linked to original sources

PubMed1989

Expert systems and the pancreatic cancer problem: decision support in the pre-operative diagnosis.

In this paper, after reviewing the main issue in artificial intelligence, decision support systems, medical decision-making, expert systems and some of their applications in medicine, we focus on the diagnostic aspect of pancreatic cancer. We briefly examine the most significant applications both from the oncological and from the diagnostic point of view. We discuss the medical problems mentioning incidence and mortality, aetiological factors and diagnosis, considering the roles of surgery and adjuvant therapies. Finally we justify the decision to develop an expert system in such a medical domain and discuss the SPES (Surgical Pancreatic Expert System) project, its parts dealing with the different medical phases of pancreatic cancer diagnosis and therapy: pre-operative, intra-operative and adjuvant therapies. In particular we discuss diagnostic aspects of pancreatic cancer disease, pointing out the aims of the project, methodologies, tools used and future developments.

Decision Support Techniques↗

PubMedDate not supplied

Evaluation stages and design steps for knowledge-based systems in medicine.

After the early experiments in artificial intelligence a methodology is emerging around advanced systems for the management of medical knowledge. The stress is moving away from the implementation of prototypes to the evaluation. It is possible to adapt and to apply this to field evaluation techniques already developed in similar contexts of knowledge management (books, drugs, epidemiology, consultants, etc.). The time is ready for a further step: to envisage a methodology for the design of real systems that cope with the 'knowledge environment' of the user. Every stage of the evaluation process is re-examined here, and considered as a framework to define goals and criteria about a step of design: (1) the impact of the system on the progress of health care provision (priorities, cost-benefit analysis, share of tasks among different media); (2) effectiveness in the end-user's environment and long-term effects on his behaviour (changes in people's role and responsibilities, improvements in the quality of data, acceptance of the system); (3) the intrinsic efficiency of the system apart from the operational context (correctness of the knowledge base, appropriateness of the reasoning). The need to differentiate the test sample into three classes (obvious, typical, atypical) is emphasized, discussing the influence on both evaluation and design. In particular the difficulty of having 'gold standards' on atypical cases, due to the disagreement among the experts, leads to the definition of two alternative attitudes: the 'standardization mode' and the 'brain-storming mode'.

Expert Systems↗

PubMedDate not supplied

Exploitation of statistical tables: conceptual interaction with epidemiologic data.

Health-care applications need flexible data and interaction models capable of dealing with data of different natures coming from different sources. These applications are usually devoted to diverse user groups, often casual or novice. The user interface must help the user to understand the database information content in his or her querying process. The authors synthetically describe FLN, a system featuring an integrated interaction with epidemiologic data. In an integrated model the statistical aspects of data (macro data) are represented, together with the intensional and extensional views of the variables involved in statistical tables.

Database Management Systems↗

PubMedDate not supplied

Semantic standards for the representation of medical records.

Physicians developed their sublanguage (a system to represent medical concepts and their relations) to store and transmit general medical knowledge and patient-related information. Adequate formalisms are needed to obtain a standard representation of semantics of medical expressions for computer use. Comparison of the semantic contents of two expressions is possible only if a unique canonical form is defined; the transmission of medical facts or patient-related information is really meaningful only by defining a set of primitives (semantic categories and links) and the domains of values (concepts). These primitives must be harmonized to yield a "common core subset" of semantic categories and links. This subset provides a common basis; a procedure to register extension sets of primitives must also be defined, to comply with specific representation needs of specialties and classes of application software.

Artificial Intelligence↗