Mosquito-borne diseases are rapidly spreading in all regions of the world with an estimation of 2.5 billion people globally are at risk. The recent surge in dengue outbreaks has caused severe affliction to Malaysian society. Hence, the ability to predict a dengue outbreak and mitigate its damage and loss proactively is very critical. In this paper, we study the possibility of applying machine learning (ML) and deep learning (DL) approaches to predict the number of confirmed dengue fever (DF) cases in Kuala Lumpur. We identified several contribution factors correlate to a dengue outbreak. In addition to the two frequently used factors (daily mean temperature and daily rainfall), we also took into account the enhanced vegetation index (EVI), humidity and wind speed as input factors to our prediction engines. We collected and cleansed data on these factors and the daily DF incidents in Kuala Lumpur from 2002 to 2012. We then used these data to train and evaluate our 3 ML/DL models. Among the three models, GA_RNN was the best performer and achieved a MAE of 10.95 for DF incidence prediction.

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Objective- To evaluate and compare the level of TSH in premenopausal women (reproductive age group) and post-menopausal women. Material And Methods- The study was carried out on 100 premenopausal and 100 post-menopausal women attending Out Patient Departments at RIMS, Ranchi, during the period of January 2018- October 2019. Study Design: - Observational Study. Statistics- Statistical analysis was done using SPSS software. The data were represented by counts, percentage and mean ± standard deviation. Statistical analysis of TSH was done by t-test to compare these parameters in premenopausal and post-menopausal women. A p-value of <0.05 was considered statistically signicant. Result- In the present study, we found that the mean serum TSH level in postmenopausal women 2.72 (± 1.06) uIU/ml was comparatively higher than premenopausal women 2.29 (±1.12) uIU/ml and the difference between the two was statistically signicant (p<0.001). Conclusion- Thyroid hormones play an important role in maintaining normal reproductive behaviour by directly effecting on gonadal function and indirectly interacting with sex hormone binding protein. Alteration of thyroid hormone level leads to menstrual irregularities and infertility. The present study clearly demonstrated that there was signicant increase in TSH levels in post-menopausal women and was statistically signicant. Thus, it proved that postmenopausal women are more prone to subclinical hypothyroidism.