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AI for Public Health: Self-Screening for Eye Diseases
September/October 1998 (vol. 13 no. 5)
pp. 28-35
How can AI help transfer sophisticated medical technology to primary health care? Certain screening tests can be performed on PCs using clinically orientated software, instead of relying on specially designed instruments. This will result in the efficient use of existing computing resources and the convenient delivery of medical care to the community. The authors describe the development of a software-based visual-field testing system that incorporates several AI components, including machine learning, an intelligent user interface, and pattern discovery. This system has been successfully used for self-screening in different public environments; the authors describe a case study of glaucoma testing in a general practice.
Index Terms:
artificial intelligence, glaucoma, public health, visual-field test
Citation:
Xiaohui Liu, Gongxian Cheng, John X. Wu, "AI for Public Health: Self-Screening for Eye Diseases," IEEE Intelligent Systems, vol. 13, no. 5, pp. 28-35, Sept.-Oct. 1998, doi:10.1109/5254.722349
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