https://grdspublishing.org/index.php/life/issue/feed LIFE: International Journal of Health and Life-Sciences 2021-12-12T03:55:09+00:00 Prof. Dr. A J Halim editor@grdspublishing.org Open Journal Systems <p><strong>ISSN 2454-5872</strong></p> https://grdspublishing.org/index.php/life/article/view/1893 SCREENING TESTS FOR THYROID DYSFUNCTION; IS TSH SUFFICIENT? 2021-12-12T03:49:02+00:00 Dorina Minxuri editor@grdspublshing.org Anila Mitre editor@grdspublshing.org Silva Bino editor@grdspublshing.org Entela Kostrista editor@grdspublshing.org Kejsi Hysaj editor@grdspublshing.org <p>There are different recommendations on how to screen for thyroid gland problems and TSH is the most ordered test. Anti TPO antibodies are usually tested when TSH is not within the normal range, but their presence before TSH changes has not been appreciated. This study aims to evaluate the role of anti-TPO and thyroid ultrasound for the early detection of thyroid pathologies, especially in the subclinical phase. This is a cross-sectional study in 458 individuals (80% females and 20% males). Thyroid laboratory tests and thyroid ultrasound was done. Statistical analysis was performed to assess the prevalence of thyroid dysfunction, thyroid antibodies and their correlation with thyroid ultrasound changes. 88.6 % (406) of subjects resulted in euthyroid. Subclinical hypothyroidism and hyperthyroidism were observed in 5.5% and 1.7% of the population, respectively. The prevalence of positive thyroid antibodies was 26.5% in females and 11.8 % in males. Hypoechoic structure, heterogenicity and micronodular pattern in ultrasound were associated with significantly higher TPO antibodies activity p&lt;.001. Undiagnosed biochemical thyroid dysfunctions were common in our country. Measurement of anti-TPO in individuals with normal TSH is valuable in determining individuals at risk for thyroid pathologies.</p> 2021-11-15T00:00:00+00:00 Copyright (c) 2021 Authors https://grdspublishing.org/index.php/life/article/view/1894 A MACHINE LEARNING LINEAR REGRESSION MODEL TO PREDICT FUTURE GIANT PANDA POPULATION 2021-12-12T03:55:09+00:00 Kumud Dave editor@grdspublshing.org Satyendra Barber editor@grdspublshing.org Pooja Verma editor@grdspublshing.org <p>Increasingly used as the insignia of China, the zaftig and enchanting Giant Panda lives on mountains of southwest China. The Giant Panda is on the WWF logo and is known as “National Treasure” in China. In this study, we predict the future Giant Panda population by using machine learning algorithms of the simple linear regression model. We take different variables to predict the next 30 years of the Giant Panda population. Focusing on the factors which affect the Giant Panda population. We take several parameters for this research like Bamboo Population, Annual Rainfall in China, Carbon Stock in Bamboo Stems, Deforestation, and Human Influence and Population of Giant Panda. Despite their peak status and relative deficiency of natural predators, pandas are still at risk and multiple intimidations from human influence have left just over 1,800 Pandas in the forest. To be ready for future troubles it is mandatory to have a pre-look of some conditions so that we can be prepared for that. Substantially, Endangered species at the edge of extinction are kept in extra special conservation. The machine learning algorithms developed with a wide-ranging of training datasets that help to find results faster and accurately.</p> 2021-11-17T00:00:00+00:00 Copyright (c) 2021 Authors