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Lab Chip ; 19(1): 59-67, 2018 12 18.
Article in English | MEDLINE | ID: mdl-30534677

ABSTRACT

The ability to accurately predict ovulation at-home using low-cost point-of-care diagnostics can be of significant help for couples who prefer natural family planning. Detecting ovulation-specific hormones in urine samples and monitoring basal body temperature are the current commonly home-based methods used for ovulation detection; however, these methods, relatively, are expensive for prolonged use and the results are difficult to comprehend. Here, we report a smartphone-based point-of-care device for automated ovulation testing using artificial intelligence (AI) by detecting fern patterns in a small volume (<100 µL) of saliva that is air-dried on a microfluidic device. We evaluated the performance of the device using artificial saliva and human saliva samples and observed that the device showed >99% accuracy in effectively predicting ovulation.


Subject(s)
Ovulation Detection/instrumentation , Point-of-Care Testing , Smartphone , Adult , Artificial Intelligence , Equipment Design , Female , Humans , Models, Biological , Ovulation Detection/methods , Saliva/chemistry , Young Adult
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