Methods for selecting, developing and improving diagnostic tests for pregnancy-related conditions
View Patent ↗Decision-support systems, such as neural networks, for assessing the risk of delivery within a predetermined time or the likelihood of preterm delivery are provided.
1. A decision support system trained for assessing the risk of imminent delivery within in a predetermined time frame or the likelihood of preterm delivery.
2. The decision support system of claim 1 that comprises a neural network.
3. A computer readable medium, comprising the neural network of claim 2 .
4. A computer readable medium, comprising the decision support system of claim 1 .
5. The decision support system of claim 1 that assesses the likelihood of preterm delivery.
6. The decision support system of claim 5 that is a neural network.
7. The decision support system of claim 1 that assesses the risk of delivery within in a predetermined time.
8. The decision support system of claim 7 , wherein the time is 7 days.
9. The decision support system of claim 8 that is a neural network.
10. The decision support system of claim 8 , wherein input variables comprise variables containing at least three and up to all of the responses to the following queries: Ethnic Origin Caucasian; Uterine contractions with or without pain; Parity-abortions; vaginal bleeding at time of sampling; uterine contractions per hour; and No previous pregnancies.
11. The decision support system of claim 10 that is a neural network.
12. The decision support system of claim 10 , wherein the variables further comprise the results from one or more of a biochemical test that detects fetal fibronectin in cervico/vaginal samples, determines the level of a local inflammatory product protein in cervico/vaginal samples; or determines estriol or estretol in saliva.
13. The decision support system of claim 12 that is a neural network.
14. The decision support system of claim 7 , wherein the time is 14 days.
15. The decision support system of claim 14 that is a neural network.
16. The decision support system of claim 14 , wherein input variables comprise variables containing at least three and up to all of the responses to the following queries: Ethnic Origin Hispanic; Marital Status living with partner; Uterine contractions with or without pain; Cervical dilatation; Uterine contractions per hour; and No previous pregnancies.
17. The decision support system of claim 16 that is a neural network.
18. The decision support system of claim 16 , wherein the variables further comprise the results from one or more of a biochemical test that detects fetal fibronectin in cervico/vaginal samples, determines the level of a local inflammatory product protein in cervico/vaginal samples; or determines estriol or estretol in saliva.
19. The decision support system of claim 18 that is a neural network.
20. The decision support system of claim 7 that is a neural network.
21. The decision support system of claim 1 , wherein the risk of delivery before 35 weeks is assessed.
22. The decision support system of claim 21 that is a neural network.
23. The decision support system of claim 21 , wherein input variables comprise variables containing at least three and up to all of the responses to the following queries: Ethnic Origin Caucasian; Marital Status living with partner; EGA by sonogram; EGA at sampling; estimated date of delivery by best; cervical dilatation (CM); parity-preterm; vaginal bleeding at time of sampling; cervical consistency at time of sampling; and previous pregnancy without complication is provided.
24. The decision support system of claim 23 that is a neural network.
25. The decision support system of claim 23 , wherein the variables further comprise the results from one or more of a biochemical test that detects fetal fibronectin in cervico/vaginal samples, determines the level of a local inflammatory product protein in cervico/vaginal samples; or determines estriol or estretol in saliva.
26. The decision support system of claim 25 that is a neural network.