Body weight prediction using different data mining algorithms in Thalli sheep: A comparative study.

BACKGROUND AND AIM: The Thalli sheep are the main breed of sheep in Pakistan, and an effective method to predict their body weight (BW) using linear body measurements has not yet been determined. Therefore, this study aims to establish an algorithm with the best predictive capability, among the Chi-square automatic interaction detector (CHAID), exhaustive CHAID, artificial neural network, and classification and regression tree (CART) algorithms, in live BW prediction using selected body measurements in female Pakistani Thalli sheep. MATERIALS AND METHODS: A total of 152 BW records, including nine continuous predictors (wither height, body length [BL], head length, rump length, tail length, head width, rump width, heart girth [HG], and barrel depth), were utilized. The coefficient of determination (R2), standard deviation ratio, root-mean-square error (RMSE), etc., were calculated for each algorithm. RESULTS: The R2 (%) values ranged from 49.28 (CART) to 64.48 (CHAID). The lowest RMSE was found for CHAID (2.61), and the highest one for CART (3.12). The most significant predictors were the HG of live BW for all algorithms. The heaviest average BW (41.12 kg) was observed in the subgroup of those having a BL of >73.91 cm (Adjusted p=0.045). CONCLUSION: Among the algorithms, CHAID provided the most appropriate predictive capability in the prediction of live BW for female Thalli sheep. In general, the applied algorithms accurately predicted the BW of Thalli sheep, which can be very helpful in deciding on the standards, available drug doses, and required feed amount for animals.

Health insurance acceptance of female labour force: A special focus on reproductive health.

OBJECTIVE: To measure the demand for health insurance policy with special focus on maternity services among working women. METHODS: The cross-sectional study was conducted in Lahore, Pakistan, from October 15 to November 15, 2018, after approval from the Punjab Economic Research Institute, and comprised public and private school teachers of reproductive age. The primary data was collected using a structured questionnaire. Logit model was used to determine the factors affecting the interest level in maternal health insurance. RESULTS: Of the 110 teachers, 54 (49 %) were from private schools and 56 (51%) from public schools. The overall age range was 21-49 years, with 64 (58%) aged 31-40 years. Also, 79 (72%) teachers had completed 16 years of education. Of the total, 63 (57%) respondents were willing to buy maternal health insurance. Income, age, awareness and the type of preceding delivery were important determinants of the willingness to pay for maternal health insurance. CONCLUSION: Providing full insurance coverage during maternity was expected to give financial relief and to also ensure better health conditions of the teachers on re-joining the work.

Anterior segment epibulbar choristoma containing brain tissue and with aphakia.

We report an unusual case of an epibulbar choristoma in a neonate born with a mass arising from the cornea. Radiologic examination showed focal corneal bulge with absence of the lens. Histologic study revealed the lesion was an epibulbar choristoma composed of only brain tissue.