Your SlideShare is downloading. ×
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Abel Hinkf6230 Cbr Hypo Km Health Informatics Report
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Abel Hinkf6230 Cbr Hypo Km Health Informatics Report

854

Published on

The widely used definition of Case Based Reasoning (CBR) is similar cases of a certain problem has related solutions. Likewise, it is widely assumed that similar differences among case descriptions …

The widely used definition of Case Based Reasoning (CBR) is similar cases of a certain problem has related solutions. Likewise, it is widely assumed that similar differences among case descriptions imply similar differences among their solutions. In this case, CBR looks to be a best solution to many unresolved medical questions and medical knowledge based systems, like in the case of hypothyroidism treatment. The main challenge, however, in finding the best solution in treating hypothyroidism with the exact dosage of levothyroxine therapy is each case is unique and difficult to derive conclusions from the previous cases (reasons). Some researches imply that case based reasoning through adaptation has a challenge in treating hypothyroidism. Nevertheless, CBR would be successful if the adaptation issue is solved. Adaptation is one of the most problematic steps in the design and development of case-based reasoning (CBR) systems. Recently, some researches have been done and scientific discussions are emerging to solve the adaptation issue. So, in this paper, I would discuss the role of adaptation in the design and development of case-based reasoning in treating hypothyroidism as well as assess the recently emerged CBR adaptation techniques and their implication to the hypothyroid treatment.

Published in: Health & Medicine, Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
854
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Case Based Reasoning (CBR) Adaptation Problem and its Solution in Treating Hypothyroidism Abel M. Gebreyesus abel@cs.dal.ca ABSTRACT: The widely used definition of Case Based Reasoning (CBR) is similar cases of a certain problem has related solutions. Likewise, it is widely assumed that similar differences among case descriptions imply similar differences among their solutions. In this case, CBR looks to be a best solution to many unresolved medical questions and medical knowledge based systems, like in the case of hypothyroidism treatment. The main challenge, however, in finding the best solution in treating hypothyroidism with the exact dosage of levothyroxine therapy is each case is unique and difficult to derive conclusions from the previous cases (reasons). Some researches imply that case based reasoning through adaptation has a challenge in treating hypothyroidism. Nevertheless, CBR would be successful if the adaptation issue is solved. Adaptation is one of the most problematic steps in the design and development of case-based reasoning (CBR) systems. Recently, some researches have been done and scientific discussions are emerging to solve the adaptation issue. So, in this paper, I would discuss the role of adaptation in the design and development of case-based reasoning in treating hypothyroidism as well as assess the recently emerged CBR adaptation techniques and their implication to the hypothyroid treatment. KEYWORDS Case-Based Reasoning (CBR), Adaptation, Hypothyroidism, Case Structure, levothyroxine therapy 1. INTRODUCTION TO HYPOHYROIDISM Hypothyroidism refers to any state that results in a deficiency of thyroid hormone, including hypothalamic or pituitary disease and generalized tissue resistance to thyroid hormone, and disorders that affect the thyroid gland directly. The clinical manifestations of hypothyroidism emerge insidiously, are nonspecific, and often are attributed to aging. They include a general slowing down, mental depression, modest weight gain, intolerance of cold, constipation, vague aches and pains, dryness of the skin, and brittleness of the scalp hair. [1] 1. 1 Differential Diagnosis
  • 2. Figure 1. Differential Diagnosis for hypothyroidism [2] Hypothyroidism is the clinical syndrome resulting from deficient thyroid hormone action. Overt hypothyroidism is found in 2% of women aged more than 70 years and in 0.5% of women aged 40 to 60 years. Hypothyroidism is present in 0.8% of men older than 60 years and is rare in women younger than 40 years and men younger than 60 years. [3] In primary hypothyroidism, the thyroid-stimulating hormone (TSH) level is elevated, and free thyroid hormone levels are depressed. In secondary hypothyroidism, the TSH level is low or undetectable. A follow-up assessment of the free thyroxine level can help distinguish between primary and secondary hypothyroidism.[4] The evaluation of patients with new-onset hypothyroidism is quite limited. In patients with primary hypothyroidism, the thyroid stimulating hormone (TSH) level is elevated, indicating that thyroid hormone production is insufficient to meet metabolic demands, and free thyroid hormone levels are depressed.[4] In contrast, patients with secondary hypothyroidism have a low or undetectable TSH level. TSH results have to be interpreted in light of the patient‟s clinical condition. A low TSH level should not be misinterpreted as hyperthyroidism in the patient with clinical manifestations of hypothyroidism. When symptoms are nonspecific, a follow-up assessment of the free thyroxine (T4) level can help distinguish between primary and secondary hypothyroidism. [4]
  • 3. Causes of Hypothyroidism Common Signs and Symptoms of Hypothyroidism Sign or symptom Affected patients (%) Primary hypothyroidism (95% of cases)  Idiopathic hypothyroidism*  Weakness 99  Hashimoto‟s thyroiditis  Skin changes 97  Irradiation of the thyroid subsequent  (dry or coarse skin)  Lethargy 91 to Graves‟  disease  Slow speech 91  Surgical removal of the thyroid  Eyelid edema 90  Late-stage invasive fibrous  Cold sensation 89  Decreased sweating 89 thyroiditis  Iodine deficiency  Cold skin 83  Drug therapy (e.g., lithium,  Thick tongue 82  Facial edema 79 interferon)  Infiltrative diseases (e.g.,  Coarse hair 76  Skin pallor 67 sarcoidosis, amyloidosis,  scleroderma, hemochromatosis)  Forgetfulness 66  Constipation 61 Secondary hypothyroidism (5% of cases)  Pituitary or hypothalamic neoplasms  Congenital hypopituitarism  Pituitary necrosis (Sheehan‟s syndrome) Table 1. Causes as well as signs and symptoms of hypothyroidism Source: Rosenfeld JA, Alley N, Acheson LS, Admire JB, eds. Women’s health in primary care. Baltimore: Williams & Wilkins, 1997:617-31 Once the diagnosis of primary hypothyroidism is made, additional imaging or serologic testing is unnecessary if the thyroid gland is normal on examination. In patients with secondary hypothyroidism, further investigation with provocative testing of the pituitary gland can be performed to determine if the underlying cause is a hypothalamic or pituitary disorder. In patients with pituitary dysfunction, imaging is indicated to detect microadenomas, and levels of other hormones that depend on pituitary stimulation should also be measured. In general, evidence of decreased production of more than one pituitary hormone is indicative of panhypopituitary problems. [4] 1. 2 Hypothyroidism and depression One of the common characteristics of hypothyroidism is depression. Depression in hypothyroidism and the cause for many disorders as well as an effect many disorders. Due to the change of metabolic hormone, food is not easily metabolized. As a result, since blood is not getting enough oxygen, feeling of dizziness is the main sign for hypothyroid patients. Generally, hypothyroidism and depression have in common. So, this depression, which caused by hypothyroidism can treated by:  Choice of medication
  • 4.  Adjustment of therapy  Follow-up care 2. CASE-BASED REASONING SYSTEMS CBR is a problem-solving method that stores the past solved problems and remembers them when solving future problems. A case represents knowledge at an operational level and comprises of problem description, associated solution to resolve the problem and the possible outcome of the solution. [4] It is a reasoning technology that uses specific knowledge from the past cases to interpret new case or to determine solution to a new problem. Various synonyms are used for CBR like instance-based, exemplary-based, memory-based and analogy-based reasoning. Case-Based Reasoning (CBR), a form of problem solving in which the problem solver reuses a past case to solve a new problem. CBR is both a model of human cognition and a paradigm for computer- based problem solvers. CBR is a process of “remember and compare” or “remember and adapt” The two types of CBR are Interpretive CBR in which the past cases are interpreted and justified on the new solution and Problem Solving CBR in which the retrieved past solution is altered to suit the new case.[5] Figure 2. Classical case-based reasoning cycle[6] CBR fulfils two main tasks: the first is the retrieval, which means to search for or to calculate the most similar cases. The second task, the adaptation (reuse and revision), means a modification of solutions of former similar cases to fit for a current one. If there are no important differences between a current and a similar case, a simple solution transfer is sufficient. Sometimes only few substitutions are required, but in other situations the adaptation is a very complicated process. So far, no general adaptation methods or algorithms have been developed. The adaptation is still absolutely domain dependent. [7] Case-based reasoning is a problem solving paradigm that in many respects is fundamentally different from other major AI approaches. Instead of relying solely on general knowledge of a problem domain, or making associations along generalized relationships between problem descriptors and conclusions, CBR is able to utilize the specific knowledge of previously experienced, concrete problem
  • 5. [Type text] situations (cases). A new problem is solved by finding a similar past case, and reusing it in the new problem situation. A second important difference is that CBR also is an approach to incremental, sustained learning, since a new experience is retained each time a problem has been solved, making it immediately available for future problems. The CBR field has grown rapidly over the last few years, as seen by its increased share of papers at major conferences, available commercial tools, and successful applications in daily use.[8] 2.1 Case Retrieval This first step comprises of description of the patient problem where a detailed patient history (that includes the signs and symptoms) has been recorded. When a user inputs this new case, the „closer match‟ past cases which contain similar possible symptoms and the conclusions drawn from them are retrieved from the case library as a reference to solve the new problem.[9] 2.2 Case reuse, Adaptation When the reference cases show a strong similarity with the new case, the respective diagnosis is reused as a solution for the current case and if the recommended solution obtained from the previous similar cases has to be altered to match the current problem then an adaptation technique is used. In this instance there is either a transformed new case solution or a derived new case solution. One such case adaptation strategy is the compositional adaptation technique where the broad base of medical information is adapted to individual personalized content.[10] 2.3 Case Revision, Verification Once an appropriate solution to the current case has been obtained then the case is evaluated to confirm the accuracy of the proposed new solution. If the generated case solution is successful then it‟s used as an important reference case for future application and if unsuccessful then the case solution is repaired by identifying the potential problems. [5] 2.4. Case Repartition When the retrieved case description is an exact match as the new case description then the same solution is used and this new case is not stored in the case base .If there are better solutions than the retrieved past solution to solve the new problem, then a repartition of world of solutions and world of problems takes place . The current case either has a new partition in the case base or based on the similarity relations the new problem is included to the partition of the past problems, so it‟s a form of partition based reasoning. [5] 2.5 Case Retention and Learning The useful experience gained by solving the current case is retained to solve future problems and the outdated cases are erased or modified in the case base to increase the accuracy of cases. [5]
  • 6. [Type text] 3. ADAPTATION IN MEDICINE: THE BOTTLENECK OF CBR According to the assumption of adaptation theory in CBR, similar problems have similar solutions. Thus, the effort required to adapt a retrieved solution will be less the more similar it is to the required solution. In medicine, CBR has mainly been applied for diagnostic and partly for therapeutic tasks. Cased- Based Reasoning seems to be a suitable technique for medical knowledge based systems. However, the adaptation task is the bottleneck that has to be solved. Still, different researchers described their reservation about the limitation of adaptation. Macura et al, for instance said: “to use Cased-Based Reasoning a few problems have to be solved: a representation form for cases has to be determined, and an appropriate retrieval algorithm has to be selected. Moreover, an infinite growth of the case base should be avoided e.g. by clustering cases into prototypes and removing redundant ones, or by restricting the case base to a fixed number of cases and updating it during expert consultation sessions[11]. However, according to Bergmann and Wilke, “the main problem of the CBR method is the adaptation task. Little research has been undertaken on this topic and only formal adaptation models” [12], but no general methods have been developed so far. As Gierl and Stengel_Rutkowski clearly elaborated, the adaptation still depends on domain and application characteristics. “Sometimes no adaptation is necessary, because e.g. the field and the cases are as unspecialised as in FLORENCE. Sometimes the adaptation is a simple solution transfer or only a little bit more, sometimes just a few constraints have to be checked”, [13] they noted. As Schmidt et al underlined, adaptation is not only a problem for medical applications. However, in medicine it increases, because cases often consist of an extremely large number of features. In non-medical CBR applications, the adaptation is usually solved by a set of specific adaptation rules, which usually have to be acquired during expert consultation sessions. As these rule sets have to consider all possible important differences between current and former similar cases, for medical applications it is mostly impossible to generate such sets. So, some adaptation solutions have been developed that are not limited to, but are rather typical for medical domains.[7] 4. THE PROBLEM OF ADAPTATION IN MEDICINE Many researchers are working on medical CBR with many diverse applicationsranging from psychiatry and epidemiology to clinical diagnosisMost of them aim for a successful implementation of CBR methods to enhance the work of health experts to improve the efficiency and quality of health care [14] A number of techniques are emerging from the adaptation research areas in different sectors, like in auto factories, pharmaceutical companies and others. However, in medicine it is not yet successful, mainly it deals with perfection. Since it deals with human beings, any adaptation technique should be perfect or near to perfect, which is one of the main challenges of adaptation in medicine. 4.1 Adaptation Problem in Hypothyroidism However, the only treatment at present, levothyroxine therapy has a number of problems associated with it. Due to these problems, hypothyroid patients need continuous treatment and follow-up. Some of the problems:
  • 7. [Type text]  Actual content of thyroid hormone varies considerably from manufacturer to manufacturer and even within product.  Patients switched from one product to another showed insignificance variations in thyroid function  Life long Treatment – Needs to be monitored continuously for better treatment results  Thus, we need to solve this treatment problem Figure 2. The cycle of hypothyroidism treatment in a CBR cycle 5 ADAPTATION TECHNIQUES FOR HYPOTHYROIDISM Depending on the type of the patients, hypothyroid patients treated with different doses of levothyroxine therapy. In our case, in order to give better treatment with successful adaptation technique, different techniques can be used. In this specific case of hypothyroidism treatment by adaptation technique, Schmidt et al, are the leaders. According to them, there can be done four kinds of techniques. Although they suggest those four techniques, still there is no complete solution to the adaptation problem. 7.1 Abstraction and Hypothyroidism Such CBR system decomposes a complex problem into a hierarchy of several levels of abstraction. These abstraction levels can be stored as abstract cases or stored in a single case Abstract cases can be helpful as case indices and can also be helpful to define the semantics of similarity. A case is preferred over a less concrete one because the more concrete the case is, the more details it has, and thus easier to apply its solution for the problem of the query case because less solution refinement is needed.[15]
  • 8. [Type text] 7.2 Compositional Adaptation and Hypothyroidism In compositional adaptation, solutions from multiple cases are combined to produce a new composite solution.[16] For instance, in in TA3-IVF [22], a system to modify in vitro fertilisation treatment plans, relevant similar cases are retrieved (the relevance has to be specified by the user) and Compositional Adaptation computes weighted averages for the solution attributes. The weights per retrieved case are determined by the similarity to the current patient; the values of the solution attributes are nominal valued.[17] According to Arshadi and Badie research in adaptation results, they developed a system solves new problems first the user request (including keyword, searching area, the current knowledge level of the user and the desired status of knowledge) is presented to the system as the input information. The system then retrieves the most similar cases from the case library, and tries to adapt the corresponding solutions such that it could best fit the ongoing situation.[18] There are three types of compositional adaptation:  Substitution  Compensation  Calculation 7.3 Constraints and Hypothyroidism A more successful technique is the application of constraints. The technique is just a reduction of a list of solutions (therapies) by constraints (contraindications). The provided list of prototypes is checked by a set of explicit constraints. These constraints state that some features of the patient either contradict or support specific prototypes (diagnoses). So the provided list of prototypes is reduced by contradictions and sorted anew because of evidences. [18] 7.4 Adaptation Rules and Operators Adaptation rules and operators is not successful technique, according to CBR analysts. One of the reason is, “the development of complete adaptation rule bases never became a successful technique to solve the adaptation problem in medical CBR systems, because the bottleneck for rule-based medical expert systems, the knowledge acquisition, not only occurs again, but also seems to be more difficult to overcome.”[17] 8. REPRESENTATION ISSUE IN HYPOTHYRODISM TREATMENT In adaptation technique for the hypothyroidism treatment, as in any cases, there is a challenge, though there are a number of researches are gong on. The case representation process is one of the main steps on the Case Base construction where each decision could condition the rest of the system, but also each technique used could affect on the final design of the case.[19] The basic retrieval algorithms for indexing, Nearest Neighbor match, pre-classification, etc. have already been developed some years ago and have been improved in the recent years. Different researchers use different adaptation representation techniques. Different forms of adaptation exist, such as null adaptation, transformational adaptation (including substitutional and structural adaptation), and generative adaptation. For instance, Juarez et al use structural adaptation. According to them, “It supports the reorganization of solution elements and permits the addition and deletion of such elements under certain
  • 9. [Type text] conditions. Also, structural adaptation systems use a fixed set of adaptation operators and/or transformation rules that modify the structure of the solution depending on the relation between the description of the query and the similar case PERSO develops a solution to a novel case by choosing the most similar case and applying a set of rules.”[19] Lorcan Coyle, Conor Hayes, Pádraig Cunningham, in their research developed a CBML tool. Using a standard XML-based metalanguage, CBML, is a key to enabling CBR applications to integrate with existing information systems. Using XML affords many advantages such as ease of transformation, flexibility of presentation and potential to create hybrid systems easily. The maturity of the XML schema definition has allowed us to develop CBML so that it can handle complex hierarchical case structures as well as the commonly used flat vector format.[20] However, the above tool is mainly used for travelers; and it is personalized. It would be difficult to incorporate for medical purposes. Although the initiative is very productive for travelers, it would be difficult to use it for treatment purposes. May be that is why there are not many researches in the adaptation circle in relation to treatment or in general in medical problem solving areas. 9. DISCUSSION There are two different tasks of determining an appropriate dose. The first one aims to determine the initial dose, while later on the dose has to be updated continuously during a patient's lifetime. Precise determination of the initial dose is most important for newborn babies with congenital hypothyroidism, because for them every week of proper therapy counts.[17] Knowledge in health related domains is complex and constantly evolving as the knowledge is incomplete. The practice in these domains also involves substantial amount of subjective knowledge and personal experience of the practitioners. [21] Adaptation remains a problem in CBR in medicine and only a few systems are used in a clinical setting. As in other domainscase mining is becoming an important area of researchThere are some exciting future areas such as Web-based electronic medical recordsthe concept of well patient care records having access to and monitoring your health even if you are wellpersonalization handheld computing for clinical decision support in hospitals and the nexus of CBR and evidence-based practicewhich all argue well for using CBR in medicine [14] 10. CONCLUSION Generally, case based reasoning is one of suitable topics for medical problem solution. Since many researches were done in the area, it becomes one of well developed research areas. The basic concept of case based reasoning is also matches with the very concept of medicine and treatment. Starting from ancient times, when healers or physicians diagnose, prescribe drugs or lab test and deal with different therapy, they use their natural case based reasoning. So, the essence of case based reasoning correspondence with the essence of medicine. However, as case based reasoning is introduced in computer applications, the adaptation issue becomes a bottle neck. As much as possible, since solutions should be perfect to the problem. In medicine, since the problem solving activity is dealing with human beings, the solutions should be perfect or near to perfect. There are some researches done to challenge such problem in treating hypothyroidism; but still it is a long way to go. As a family of endocrine disease, the challenge to hypothyroidism is a challenge to most endocrine therapy. So, the solution for hypothyroidism could be a solution of endocrine therapy, as well as a big step for medical problems. As hypothyroidism is a common disorder among Canadians and most common to old females, trying to solve a problem means trying to help one in 50 age 60 or over or one in 150 age 20 or over, in a Canadian figure.
  • 10. [Type text] In any scientific research, challenge means opportunity, as long as there is nothing impossible to human knowledge. So, if one takes the adaptation problem, in this case hypothyroidism treatment, a challenge means an opportunity to be solved by dedicated researches. References [1] Kenneth A. Woeber, Update on the Management of Hyperthyroidism and Hypothyroidism. Archives of Family Medicine, Vol. 9(8), 2000 pp. 743-747. [2] Slatosky J., Shipton B., and Wahba H., Thyrodidits Thyroiditis: Differential Diagnosis and Management: American Family Physician: Vol. 61(4), 2000) [3] Helfand M, Redfern CC. Screening for thyroid disease. Ann Intern Med 1998;129: 144–158 [4] Hueston, William J., Treatment of Hypothyroidism. America Family Physician, Vol. 64:1717-24, 2001 [5] Finnie G, Sun Z: R5 model for case-based reasoning. Knowledge-Based Systems 16 (2003) pp. 59–65 [6] Isabelle Bichindaritz , Case-based reasoning in the health sciences; Artificial Intelligence in Medicine ; Vol. 36, Issue 2, February 2006, pp121-125 Schmidt R., Montani S., Bellazzi R., Portinale L. and Gierl L.; Cased-Based Reasoning for medical knowledge-based [7] systems, International Journal of Medical Informatics; Volume 64, Issues 2-3, December 2001, pp 355-367 [8] A. Aamodt, E. Plaza (1994); Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches; AICom - Artificial Intelligence Communications, IOS Press, Vol. 7: 1, pp. 39-59. [9] Chang C-L., Using case-based reasoning to diagnostic screening of children with developmental delay. Expert Systems with Applications, 28(2005) pp 237-247. [10] Abidi SSR, Designing Adaptive Hypermedia for Internet portals: A personalized strategy featuring case base reasoning th with composition adaptation, Artificial Intelligence: 8 Iberamia Conference on Artificial Intelligence, Seville, 2002 [11] R. Macura and K. Macura , MacRad: radiology image resource with a Cased-Based retrieval system. In: M. Veloso and A. Aamodt, Editors, Proceedings of 1st International Conference on CBR, Springer, Berlin (1995), pp. 43–54. [12] R. Bergmann and W. Wilke , Towards a new formal model of transformational adaptation in Cased-Based reasoning. In: L. Gierl and M. Lenz, Editors, Proceedings of 6th German Workshop on CBR, University of Rostock (1998), pp. 43–52 [13] L. Gierl and S. Stengel-Rutkowski , Integrating consultation and semi-automatic knowledge acquisition in a prototype- based architecture: experiences with Dysmorphic Syndromes. ArtificIntell. in Med. 6 (1994), pp. 29–49. [14] Holt, A. Bichindaritz, I., Schimidt, R., and Perner, P., Medical applications in case-based reasoning The Knowledge Engineering Review Vol. 20:3, 289-292. 2006) [15] Kwan-Yu Chen and Alan Liu; Using Hierarchical Case Representation for Software Reuse, pages 110-117 (http://ieeexplore.ieee.org/iel5/7214/19427/00897200.pdf?arnumber=897200) [16] Niloofar Arshadi1 & Kambiz Badie; A Compositional Approach to Solution Adaptation in Case-Based Reasoning and its Application to Tutoring Library (http://www.cs.toronto.edu/~niloofar/Arshadi_Badie_00.pdf) [17] Schmidt, R., Vorobieva, O., & Gierl, L., 2003. Case-Based Adaptation in Medicine Focusing on Hypothyroidism . Second German Workshop on Experience Management (GWEM 2003), 267-274.) [18] N. Arshadi & K. Badie, “A Compositional Approach to Solution Adaptation in Case-based Reasoning and its Application to Tutoring Library”, Proceedings of 8th German Workshop on Case-Based Reasoning, Lammerbuckel (2000) [19] Muarez, J. M., Salort J., Palma J., Marin R.; Case Representation Ontology for Cse Retriefal Systems in Medical Domains; Proceedings of the 25th IASTED International Multi-Conference Artificial Intelligence and Applications Feb 12-14, 2007, Innsbruck, Austria [20] Coyle L., Hayes C., Cunningham P. Representing Cases for CBR in XML. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2002-63, 2002, pp7 [21] Wu, Daniel, Weber, Rosina O., and Abramson, A case-based framework for leveraging nutrigenomics knowledge and personal nutrition counseling Fredric Issue ; 2004; Paper presented at the 7th European Conference in Case-Based Reasoning, Madrid, Spain)

×