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Embedding neural nets and expert systems in diagnostic microbiology laboratories

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2 Author(s)
Ciesielski, V. ; R. Melbourne Inst. of Technol., Vic., Australia ; Spicer, J.

Describes a project for developing a reliable computer vision system that analyzes bacterial growths in real time on inexpensive personal computers, and an expert advising system that adds treatment recommendations to laboratory reports. The system embeds a neural network and multiple expert systems in the normal workflow of a clinical microbiology laboratory. Such laboratories receive specimens from patients with suspected bacterial infections, identify the organisms, determine which antibiotics will kill the bacteria or prevent growth, and convey the results to the treating physician, who can use the findings as a basis for treatment. Clearly this information is critical, since in the more extreme cases, lives are at stake.<>

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IEEE Expert  (Volume:9 ,  Issue: 3 )