Case-based medical informatics

BACKGROUND: The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. DISCUSSION: We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging. Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. SUMMARY: Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately

ALBACORE (Thunnus alalunga) REPRODUCTIVE BIOLOGY STUDY FOR THE NORTH ATLANTIC STOCK:YEARS 2020 AND 2021

The ICCAT North Atlantic Albacore (Thunnus alalunga) Research Program was established to enhance knowledge on albacore to provide more accurate scientific advice to the Commission. Funds are provided to the Albacore WG to develop research activities to accomplish several objectives. One of the research objectives is to increase knowledge on reproductive biology for the northern Atlantic stock, maturity schedules (L50) and egg production (size/age related fecundity. In March 2021, Terms of Reference were published by ICCAT. A Consortium integrated by Canada, Venezuela, Chinese-Taipei and Spain presented an offer to collect gonad samples and spines throughout the year and carry out the study of reproductive biology for North Atlantic albacore stock. Results of histological analysis: maturity stages, batch fecundity and seasonal area of spawners are presented as well as the age determined of partially collection of albacore spines. Analysis were done with the total albacore gonads samples collected in 2020 and 2021 for the reproductive biology study of northern albacore.

Clinical case similarity and diagnostic reasoning in medicine

This thesis describes a study of novice problem solving in the domain of medicine. The study attempts to answer questions pertaining to the diagnostic accuracy, the generation and change of diagnostic hypotheses, and the use of clinical findings in the course of solving clinical cases with similar presenting complaints. Two specific issues are addressed: (1) how does the initial case presentation suggesting a common disease schema affect the diagnostic problem solving process of novices and intermediate subjects? (2) what are the processes the subjects used in coordinating hypothesis and evidence during diagnostic problem solving?Medical trainees (students and a resident) were given four clinical cases to solve and think-aloud protocols were collected. The verbal protocols were analyzed using methods of protocol analysis. The results show that second year medical students interpreted clinical cases in terms of the more common disease schema, regardless of the initial presentation of the case. More advanced students, although unable to make a correct diagnosis in most instances, were less susceptible to such confusions. Only the resident was able to interpret the cases in terms of different disease schemata, reflecting knowledge of the underlying disease process. The semantic analysis of the protocols revealed that most students, especially at lower levels of training, misinterpreted or ignored the evidence that contradicted their initial hypotheses and made use of a mixture of forward and backward reasoning; a finding consistent with previous research. Implications for educational training and for a theory of novice problem solving in medicine are presented

Case-based medical informatics

Abstract Background The "applied" nature distinguishes applied sciences from theoretical sciences. To emphasize this distinction, we begin with a general, meta-level overview of the scientific endeavor. We introduce the knowledge spectrum and four interconnected modalities of knowledge. In addition to the traditional differentiation between implicit and explicit knowledge we outline the concepts of general and individual knowledge. We connect general knowledge with the "frame problem," a fundamental issue of artificial intelligence, and individual knowledge with another important paradigm of artificial intelligence, case-based reasoning, a method of individual knowledge processing that aims at solving new problems based on the solutions to similar past problems. We outline the fundamental differences between Medical Informatics and theoretical sciences and propose that Medical Informatics research should advance individual knowledge processing (case-based reasoning) and that natural language processing research is an important step towards this goal that may have ethical implications for patient-centered health medicine. Discussion We focus on fundamental aspects of decision-making, which connect human expertise with individual knowledge processing. We continue with a knowledge spectrum perspective on biomedical knowledge and conclude that case-based reasoning is the paradigm that can advance towards personalized healthcare and that can enable the education of patients and providers. We center the discussion on formal methods of knowledge representation around the frame problem. We propose a context-dependent view on the notion of "meaning" and advocate the need for case-based reasoning research and natural language processing. In the context of memory based knowledge processing, pattern recognition, comparison and analogy-making, we conclude that while humans seem to naturally support the case-based reasoning paradigm (memory of past experiences of problem-solving and powerful case matching mechanisms), technical solutions are challenging. Finally, we discuss the major challenges for a technical solution: case record comprehensiveness, organization of information on similarity principles, development of pattern recognition and solving ethical issues. Summary Medical Informatics is an applied science that should be committed to advancing patient-centered medicine through individual knowledge processing. Case-based reasoning is the technical solution that enables a continuous individual knowledge processing and could be applied providing that challenges and ethical issues arising are addressed appropriately.</p

Cognitive assessment and health education in children from two different cultures

This paper presents research aimed at investigating high level comprehension and problem solving processes in children in two different countries, India and Colombia. To this end, we use a series of health-related cognitive tasks as assessment tools. In one study, we also examine children's performance on these cognitive tasks, in relation to their nutritional status and parasitic load. The ages of the children tested ranged from 2 through 14 years. The tasks were designed to assess comprehension of sequences, organization of concepts, understanding of health routines (hygiene practices) and evaluation of hypothesis and evidence. The results show that children approach the different tasks with a baggage of beliefs and local knowledge of the world which determines their reasoning process, their comprehension and their problems solving. The results are discussed in terms of cognitive assessment approaches, as applied to classroom instruction. Given that children construct their understanding of reality based on what they already know and that education does not take this into account, we recommend that assessment tools should be devised that can tap prior knowledge and understanding, such that this can be analyzed and understood in relation to knowledge taught in the classroom. Current educational assessment fails in such an endeavor.

Cognition and expertise: acquisition of medical competence

Abstract The cognitive study of expertise in knowledge domains has generated a great deal of knowledge that can be used in the education and training of health care providers. This research has looked at the development and characteristics of expert performance. Design of medical and health education systems that are informed by this research can be powerful tools to improve the quality of medical education. Résumé L&apos;étude cognitive de l&apos;expertise dans des domaines de connaissance a produit beaucoup d&apos;information qui peuvent servir à l&apos;éducation et la formation des prestateurs de soins de santé. Dans cette étude, on a examiné le développement et les caractéristiques de la performance des experts. Les systèmes d&apos;éducation en médecine et en santé s&apos;inspirant de ces recherches pourront être des outils puissants pour améliorer la qualité de l&apos;éducation médicale

In this particular example expressions such as: on(a, c), on(c, table), on(b, table), pyramid(a), brick(b), brick(c), ¬same-as(a, c), same-as(b, c), etc

<p><b>Copyright information:</b></p><p>Taken from "Case-based medical informatics"</p><p>BMC Medical Informatics and Decision Making 2004;4():19-19.</p><p>Published online 8 Nov 2004</p><p>PMCID:PMC544898.</p><p>Copyright © 2004 Pantazi et al; licensee BioMed Central Ltd.</p>, are true

Case-Based (Memory-Based) Medical Knowledge Acquisition and Processing

The &quot;frame problem&quot; is at the core of artificial intelligence and decision making research and is directly related to the intelligent agents&apos; ability to learn from experience, to the choice for knowledge representation and to the exhaustiveness of their knowledge bases. Case-based reasoning is an important paradigm in artificial intelligence, in the context of expert system development. A case-based reasoning expert comprises the case base, which can be regarded as a memory of past experiences of problem-solving, and a case matching procedure for the retrieval of cases relevant for a new problem. While humans seem to possess a natural support for these two components, this kind of knowledge acquisition and processing is not directly supported by computers