An Expert System to Diagnose Anemia and Report Results Directly on Hematology Forms

Discriminant indices for distinguishing thalassemia and iron deficiency in patients with microcytic anemia: a meta-analysis

“…It is widely agreed that none of these indices is 100% sensitive or 100% specific. Even more complex approaches including combinations of different simple indices, multivariate discriminant analysis or artificial neural network computing are unable to reach absolute sensitivity and specificity [15][16][17][18][19][20][21][22][23]. It is somewhat surprising that comparative studies of these screening indices do not show a consistent picture: discriminant indices that are superior in one study may perform less well in another study.…”

Expert system in medicine and its application on pulmonary diseases

“…Since then, medical application areas of expert systems have been broadened covering most of its areas, especially the use of reasoning process in decision making with the self-learning ability has improved the reliability and accuracy of the programs such as expert systems for general practice or diabetes mellitus or hematology or prescription or schizophrenic disorders or eye diseases or endocrine disorders or laboratory medicine so on (4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20) In medicine, the reasoning process consists of four major components. These are : cue acquisition, hypothesis generation, cue interpretation, and hypothesis evaluation.…”

Thalassaemia classification by neural networks and genetic programming

“…Later, the implementation protocol has shifted to the expert systems, in which both rule-based [23,24,17] and hybrid neural network/rule-based systems [4] have been successfully tested in clinical trials. Nonetheless, these tools broadly differentiate between a wide range of blood-related diseases including various types of anaemia.…”