A High-Performance FPGA-Based Fuzzy Processor Architecture for Medical Diagnosis

Authors:
Shubhajit Roy Chowdhury;Hiranmay Saha
Affiliations:
Jadavpur University;Jadavpur University
Venue:
IEEE Micro
Year:
2008

Citing 0
Cited 3

Improving fuzzy knowledge integration with particle swarmoptimization

Expert Systems with Applications: An International Journal
ASIC Design of a Digital Fuzzy System on Chip for Medical Diagnostic Applications

Journal of Medical Systems
Accuracy Enhancement in a Fuzzy Expert Decision Making System Through Appropriate Determination of Membership Functions and Its Application in a Medical Diagnostic Decision Making System

Journal of Medical Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

An auto-decision-making system for medical diagnosis could help make up for the lack of physicians in rural areas of many third-world countries. This high-performance, low-power, pipelined parallel fuzzy processor based on a dedicated single-chip architecture performs high-speed fuzzy inferences with processing speed up to 5.0 Mflips at a clock frequency of 40 MHz using 256 rules having one consequent each, 16 input variables, and 16-bit resolution. The processor operates in real time producing results within an interval of 1.92μs. The processor implemented on board consumes as low as 70 milliwatt power. The processor performs medical diagnosis with 97.5 percent accuracy.