Decision Support Systems in Gastrointestinal Oncology

  • R. Maceratini
  • S. Crollari
Conference paper


In ancient times a medix was not a doctor at all, but a judge, a magistrate of Osci (ancient Italian people); in ancient Greek µεδω had meant to manage, to take care of someone, to produce rules, to make decisions, and to arbitrate between possible alternatives. Nowadays the medical person, a physician, is a decision maker as regards quod vitam and quod valitudinem (quality and expectancy of life). The hallmark of a good physician is his ability to make sound clinical judgments. Traditionally this has been considered an artful and intuitive process, neither subject to theoretical analysis nor to be captured in a formal quantitative model [5]. Elstein et al. [19] described four major components of the reasoning process with deductive method: cue acquisition, which includes the acquisition of a history, performance of a physical examination, and a request for diagnostic procedures; hypothesis generation, in which alternative hypotheses are retrived from the physician’s memory; cue interpretation, in which the data are considered in view of their contribution to alternative hypotheses; and hypothesis evaluation, in which the data are weighted and combined to determine which hypotheses are confirmed or rejected. The final step, the decision, depends on the clinical environment; it is related to social, economic, demographic, cultural, and organizing contexts.


Pancreatic Cancer Expert System Decision Support System Diagnostic Strategy Gastric Cancer Diagnosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Adlassnig KP (1986) Computer-based diagnostic screening and consultation in hospital. In: Salomon R, Blum B, Joergensen M (eds) Proc MEDINFO, pp 101–105Google Scholar
  2. 2.
    Adlassnig KP, Kolarz G (1982) CADIAG-2: computer assisted medical diagnosis using fuzzy subset. In: Gupta MM, Sanchez E (eds) Approximate reasoning in decision analysis. North-Holland, Amsterdam, pp 219–247Google Scholar
  3. 3.
    Adlassnig KP, Kolarz G, Scheithaner W (1985) Present state of the medical expert system Cadiag-2. Methods Inf Med 24: 13–20PubMedGoogle Scholar
  4. 4.
    Bartels PH, Paplanus S, Graham A, Bibbo M (1988) Image understanding in expert system in histopathology. Proc IEEE Press, New York 10: 1373–1374Google Scholar
  5. 5.
    Bergman DA, Pantell RH (1984) The art and science of medical decision making. J Pediatr 104: 649–656PubMedCrossRefGoogle Scholar
  6. 6.
    Berner ES, Brooks CM (1988) Needs assessment for computer-based medical decision support systems. Proc SCAMC, pp 232–236Google Scholar
  7. 7.
    Boom R, Gonzalez C, Fridman L, Ayala JF, Realpe JL Morales P, Quintero R (1986) Looking for “indicants” in the differential diagnosis of jaundice. Med Decis Making 6: 36–41PubMedCrossRefGoogle Scholar
  8. 8.
    Brandeau ML, Eddy DM (1987) The workup of the asymptomatic patient with a positive fecal occult blood test. Med Decis Making 7: 32–46PubMedCrossRefGoogle Scholar
  9. 9.
    Chandrasekaran B, Gomez F, Mittal S, Smith JW (1979) An approach to medical diagnosis based on conceptural structures. Proc IJCAI, Tokyo, 1: 134–142Google Scholar
  10. 10.
    Chandrasekaran B, Mittal S, Smith JW (1980) RADEX — towards a computer-based radiology consultant. In: Gelsema ES, Kanal LN (eds) Pattern recognition in practice. North-Holland, Amsterdam, pp 463–477Google Scholar
  11. 11.
    Chou TC (1987) New computerized quantitative approach to combination therapy. Proc AACR Waverly Press, Baltimore 28: 1645Google Scholar
  12. 12.
    Coldman AJ, Goldie JH (1985) Role of mathematical modeling in protocol formulation in cancer chemotherapy. Cancer Treat Rep 69: 1041–1045PubMedGoogle Scholar
  13. 13.
    Crean GP, Card WJ, Beattie AD, Holden RJ, James WB, Knill-Jones RP, Lucas RW, Spiegelhalter D (1982) Ulcer-like dyspepsia. Scand J Gastroenterol [Suppl 79] 17: 9–15Google Scholar
  14. 14.
    CRI Directory of Expert Systems (1986) Learned Information Ltd, OxfordGoogle Scholar
  15. 15.
    De Dombal FT (1988) The OMGE acute abdominal pain survey. Progress report, 1986. Scand J Gastroenterol [Suppl 144] 23: 35–42Google Scholar
  16. 16.
    De Vita VT jr, Hellman S, Rosemberg SA (1985) Cancer principles and practice on oncology. Lippincott, PhiladelphiaGoogle Scholar
  17. 17.
    Dunwoodie WM (1987) Computer-aided diagnosis in dyspepsia. Practitioner 231: 162–168PubMedGoogle Scholar
  18. 18.
    Eddy DM (1987) CAN*TROL: a computer model for designing national cancer control strategies. Bull Cancer 74: 323–332PubMedGoogle Scholar
  19. 19.
    Eistein AS, Shulman LS, Sprafka SA (1978) Medical problem solving: an analysis of clinical reasoning. Harvard University Press, Cambridge, pp 65–121Google Scholar
  20. 20.
    Erlbaum MS (1984) Micro-RECONSIDER: a differential diagnostic prompting aid for the IBM PC XT. Proc SCAMC GS Cohen (ed) Washington, IEEE Press, New York, pp 318–320Google Scholar
  21. 21.
    Fieschi M, Joubert M, Fieschi D, Roux M (1982) SPHINX — a system for computer-aided diagnosis. Methods Inf Med 21 (3): 143–148PubMedGoogle Scholar
  22. 22.
    Friedmam RH, Frank AD (1984) Automation of formal rules for clinical decision-making support imbedded in an information system. Proc SCAMC GS Cohen (ed) Washington, IEEE Press, New York Washington, pp 258–262Google Scholar
  23. 23.
    Fu LM, Buchanan BG (1984) Enhancing performance of expert systems by automated discovery of meta-rules. Proc IEEE/AAAI IEEE Press, New York Denver, 107–116Google Scholar
  24. 24.
    Gage TP (1982) Screening colonscopy or colectomy to prevent cancer in colitis? A decision-analytic approach (Abstr). Gastroenterology 82: 1062Google Scholar
  25. 25.
    Gevarter WB (1983) Expert systems: limitated but powerful. IEEE Spectrum 25: 39–45Google Scholar
  26. 26.
    Gorry A, Scott-Morton M (1971) A framework for information system. Sloan, FallGoogle Scholar
  27. 27.
    Greenes RA (1979) A goal directed model for investigation of thresholds for medical action. Proc SCAMC RA Dum (ed) IEEE Press, New York, pp 47–51Google Scholar
  28. 28.
    Habbema JDF, van der Maas PJ, Dippel DWJ (1986) A perspective on the role of decision analysis in clinical practice. Ann Med Interne (Paris) 137: 267–273Google Scholar
  29. 29.
    Hessel SJ, Sielmann SS, McNeil BJ (1982) A prospective evaluation of computed tomography and ultrasound of the pancreas. Radiology 143: 129–133PubMedGoogle Scholar
  30. 30.
    Hildebrandt J, Klar R, Weyland A, Wieding JW (1987) A computerized information system for a pain clinic. Methods Inf Med 26: 97–101PubMedGoogle Scholar
  31. 31.
    Horvitz EJ, Heckrman DE, Natwani BN, Fagan LM (1984) Diagnostic strategies in the hypothesis-directed PATHFINDER system. 1st Conference on Artificial Intelligence Application, IEEE/AAAI, Denver, 630, IEEE Press, New YorkGoogle Scholar
  32. 32.
    Hubbard SM (1987) When cancer information is needed PDQ. Hosp 15: 84–90Google Scholar
  33. 33.
    Hunter JRW, Sinnhuber RKEW (1983) Representation of disease development. In: Mevvey (ed) Expert systems 83, Churchill College, Cambridge. 3rd annual conference of the British Computer Society Specialist Group on Expert Systems, pp 174–183Google Scholar
  34. 34.
    Hyödynmaa S, Kolary P, Näriäinen K, Ojala A, Rantaney J, Saranummi N (1988) Decision support system in oncology. In: Lindberg DAB (ed) Lecture notes in medical informates, vol 36. Springer, Berlin Heidelberg New York, pp 65–68Google Scholar
  35. 35.
    Iriyama K, Suzuki K (1986) Prediction of post-operative survival time by multivariate analysis in patient with advanced cancer of the stomach. 25th International Congress of the College of Surgeons, Madrid (abstract)Google Scholar
  36. 36.
    Jagoe R, Sowter C, Dandy S, Slavin G (1982) Morphometric study of liver cell nuclei in hepatomas using interactive computer techniques. I. Nuclear size and shape. Clin Pathol 35: 1057–1062Google Scholar
  37. 37.
    Karouji S, Hayashi K, Morita T, Konn M, Onto K (1987) Personal computér program for processing data from patients with colo-rectal cancer. Med Inf (Lond) 12 (1): 33–42Google Scholar
  38. 38.
    Kinney EL, Brafman D, Wright II RJ (1988) An expert system in the diagnosis of ascites. Comput Biomed Res 21: 169–173PubMedCrossRefGoogle Scholar
  39. 39.
    Knill-Jones RP (1987) Diagnostic systems as an aid to clinical decision making. Br Med J 295: 1392–1396CrossRefGoogle Scholar
  40. Decision Support Systems in Gastrointestinal Oncology 175Google Scholar
  41. 40.
    Knill-Jones RP, Stern RB, Girmes DH, Maxwell JD, Thompson RPH, Williams R (1973) Use of sequential model in diagnosis of jaundice by computer. Br Med J 1: 530–533PubMedCrossRefGoogle Scholar
  42. 41.
    Ledley RS, Lusted LB (1959) Reasoning foundation of medical diagnosis. Science 130: 9–21PubMedCrossRefGoogle Scholar
  43. 42.
    Lind SE, Singer DE (1986) Diagnosing liver metastases: a Bayesian analysis. J Clin Oncol 4: 379–388PubMedGoogle Scholar
  44. 43.
    Lindberg G, Nilsson LH, Thulin L (1983) Decision theory as an aid in the diagnosis of cholestatic jaundice. Acta Chir Scand 149: 521–529PubMedGoogle Scholar
  45. 44.
    Lindberg G, Thomsen C, Malchow-M¢ller A, Matzen P, Hilden J (1987) Differential diagnosis of jaundice: applicability of the Copenhagen Pocket Chart proved in Stockholm patients. Liver 7: 43–49PubMedGoogle Scholar
  46. 45.
    Lindberg G, Seensalu R, Nilsson LH, Forsell P, Kager L, Knill-Jones RP (1988) Transferability of a computer system of medical history taking and decision support in dyspepsia. A comparison of indicants for peptic ulcer disease. Scand J Gastroenterol [Suppl] 129: 190–196Google Scholar
  47. 46.
    Maceratini R, Rafanelli M, Crollari S, Pisanelli DM (1988) Knowledge based systems: a support to the diagnosis and the therapy in the pancreatic cancer problem. In: Joly (ed) Expert systems in medicine. EC2, Nanterre, pp 269–293Google Scholar
  48. 47.
    Maceratini R, Rafanelli M, Pisanelli DM, Croilari S (1989) Expert system and the pancreatic cancer problem: the decision support in the pre-operative diagnosis. J Biomed Eng 11: 487–510PubMedCrossRefGoogle Scholar
  49. 48.
    Macrae FA, Williams CB (1982) A prospective colonscopic follow-up study of 500 adenoma patients with multivariate analysis to predict risk of subsequent colorectal tumors (abstr). Gastroenterology 82: 1122Google Scholar
  50. 49.
    Makuch RW, Rosemberg PS (1988) Identifying prognostic factors in binary outcome data: an application using liver function tests and age to predict liver metastases. Stat Med 7: 843–856PubMedCrossRefGoogle Scholar
  51. 50.
    Malchow-M¢ller A, Thomsen C (1987) Algorithmic diagnosis of jaundice. Scand J Gastroenterol [Suppl] 128: 162–168Google Scholar
  52. 51.
    Miller PL, Blumenfrucht SJ, Rose JR, Rothschild M, Swett HE, Weltin G, Mars NJI (1987) A knowledge acquisition tool for expert systems that critique medical workup. Med Decis Making 7: 12–21PubMedCrossRefGoogle Scholar
  53. 52.
    Mishima H, Katoh N, Hattori T, Nomura Y, Nakamura M (1980) A fuzzy decision analysis for the management of pancreatic cancer. Proc MEDINFO 80:830–834, Lindberg/Kuihard (eds ), North-Holland-AmsterdamGoogle Scholar
  54. 53.
    Mittal S, Chandrasekaran B, Sticklen J (1984) PATREC: a knowledge-directed database for a diagnostic expert system. Computer 17 (9): 51–58CrossRefGoogle Scholar
  55. 54.
    Molokova OS, Chernyakovskaja MJ (1984) Results of implementation of the first version of medical expert system “CONSULTANT”. In: Plander I (ed) Artificial intelligence and information-control systems of robots. North-Holland, Amsterdam, pp 269–271Google Scholar
  56. 55.
    North LW, Eiseman B (1986) Surgical decision making. Saunders, PhiladelphiaGoogle Scholar
  57. 56.
    Pollitt AS (1984) A `front-end’ system: an expert system as online search intermediary. ASLIB 36 (5): 229–234CrossRefGoogle Scholar
  58. 57.
    Rafanelli M, Maceratini R, Pisanelli DM, Crollari S (1986) SPES: an expert system in pancreatic cancer surgery. In: Kondraske GV, Robinson CJ (eds) Proc Eight Engineering in Medicine and Biology Society, pp 869–871, Fort Worth, DallasGoogle Scholar
  59. 58.
    Reggia JA (1982) Computer-assisted medical decision making. In: M Schwarz (ed) Applications of Computers in Medicine, IEEE Press, New York, 198–213Google Scholar
  60. 59.
    Richter JM, Barry MJ (1985) Decision analysis for the practing gastroenterologist. II. Insights into the efficacy of diagnostic strategies using decision analysis. Am J Gastroenterol 80 (6): 493497Google Scholar
  61. 60.
    Rozen P, Levy E (1984) Data management in a gastroenterology endoscopy service. Initial experience using a micro-computer. In: Rozen P, de Dombal FT (eds) Computer aid in gastroenterology. Karger, Basel, pp 96–109Google Scholar
  62. 61.
    Safran C, Greenes RA, Kierstead M, Bynum TE (1983) Computer assisted evaluation of the jaundiced patient. Proc SCAMC 135–137, RE Dayhoff (ed), IEEE Press, New YorkGoogle Scholar
  63. 62.
    Scarlett P, Cooke WM, Clarke D, Bates C, Chan M (1986) Computer aided diagnosis of acute abdominal pain at Middlesbrough General Hospital. Ann R Surg Engl 68: 179–181Google Scholar
  64. 63.
    Segaar RW, Wilson JHP, Habbema JDF, Hilden J (1989) A computer aid for early diagnostic classification of jaundice (the COMIP Program). Comput Methods Programs Biomed 28: 131–136PubMedCrossRefGoogle Scholar
  65. 64.
    Shindo H, Yasaka T (1984) Inference structure in a AMHTS environment with regard to artificial intelligence. In: Lindberg DAB, Cohen MF (eds) Proc AAMSI Congress 84, pp 178–182, AAMSI Publ, Bethesda, MDGoogle Scholar
  66. 65.
    Shortliffe EH (1987) Computer program to support clinical decision making. JAMA 258: 61–66PubMedCrossRefGoogle Scholar
  67. 66.
    Shortliffe EH, Buchanan BG, Feigenbaum EA (1979) Knowledge engineering for medical decision making: a review of computer-based clinical decision aids. Proc IEEE 67 (9): 1207–1224CrossRefGoogle Scholar
  68. 67.
    Silverstein MD, Richter JM, Podolsky DK, Warshaw A (1984) Suspected pancreatic cancer presenting as pain or weight loss: analysis of diagnostic strategies. World J Surg 8: 839–845PubMedCrossRefGoogle Scholar
  69. 68.
    Sisson JC, Schoomaker EB, Ross JC (1976) Clinical decision analysis: the hazard of using additional data. JAMA 236 (11): 1259–1263PubMedCrossRefGoogle Scholar
  70. 69.
    Stutt JJ, Didden HW, De Valk JPJ, Bakker AR (1988) Prediction and analysis of PACS performance with the simulation tools, Miracles. Med Inf 13 (4): 349–359CrossRefGoogle Scholar
  71. 70.
    Torasso P, Lesmo L, Saitta L, Molino G, Cravetto C, Milanese M, Frediani S (1985) Sistemi esperti per la diagnosi medica: it progetto “LITO”. Med Inf 2 (2): 43–45Google Scholar
  72. 71.
    Van Bemmel JH (1985) Formalization of medical knowledge: the basis for diagnostic strategies and expert systems. In: van Bemmel JH, Grémy F, Zvarova J (eds) Medical decision-making: diagnostic strategies and expert systems. Nort-Holland, Amsterdam, pp 1–11Google Scholar
  73. 72.
    Van Bemmel JH (1986) Formalization of medical knowledge. Methods Inf Med 25: 191–193PubMedGoogle Scholar
  74. 73.
    Van Bemmel JH (1988) Decision support system in medicine. Comparative methodology and impact on the medical curriculum. In: Lindberg DAB (ed.) Lecture notes in medical informatics, vol 36. Springer, Berlin Heidelberg New York, pp 3–19Google Scholar
  75. 74.
    Van Bemmel JH, Grémy F, Zvarova J (eds) (1985) Medical decision-making: diagnostic strategies and expert systems. North-Holland, AmsterdamGoogle Scholar
  76. 75.
    Zaborowski P, Janecki J, Stencel J, Dziuda D, Grys (1985) Clinical experiments with computer-assisted selection of diagnostic strategies. In: van Bemmel JH, Grémy F, Zvarova J (eds) Medical decision-making: diagnostic strategies and expert systems. North-Holland, Amsterdam, pp 241–244Google Scholar
  77. 76.
    Zeng-lie L, Fu-le H (1982) Computer-aided diagnosis of gastric cancer. Chin Med J 95: 293–296Google Scholar
  78. 77.
    Zhenhan L, Chuan L (1985) Identification of cancer cell by computer with fuzzy method. In: van Bemmel JH, Grémy F, Zvarova J (eds) Medical decision-making: diagnostic strategies and expert systems. North-Holland, Amsterdam, pp 278–281Google Scholar
  79. 78.
    Zoltie N, Horrocks JC, de Dombal FT (1977) Computer assisted diagnosis of dyspepsia: report on transferibility of a system, with emphasis on early diagnosis of gastric cancer. Methods Inf Med 16: 62–89Google Scholar

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© Springer-Verlag Berlin Heidelberg 1991

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  • R. Maceratini
  • S. Crollari

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