E-learning in Medical Diagnosis

Daniela Mayumi Ushizima & Marta Costa Rosatelli

Abstract. The massive amount of data, required to learn how to diagnose, can be organized and turned into information to physicians using computers and Internet. In addition to atlases, the collaboration among professors, researchers, and students are decisive issues to consolidate the diagnostic knowledge. In order to tackle this problem, we propose a collaborative learning environment to support group activity, in the context of e-learning in the medical domain. The pedagogical approach of this environment is learning from case studies. The first step towards e-learning applied to diagnosis is to organize a blood image data base and their metadata available through a digital atlas (e-atlas). To accomplish this, we intend to: (1) collect a number of blood cell images organizing them into an e-atlas and (2) turn numerical measurements (real numbers) into medical reports, with suitable medical jargon.

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Knowledge organization toward leukemia diagnosis: (a) Leuko prototype concluded; (b) E-learning in medical diagnosis: information acquisition and exchange; (c) Future computer decision support system able to output anamnesis.