High blood pressure prediction based on AAA++ using machine-learning algorithms

The heart pumps the blood around the body to supply energy and oxygen for all the tissues of the body. In order to pump the blood, heart pushes the blood against the walls of arteries, which creates some pressure inside the arteries, called as blood pressure (BP). If this pressure is more than the desired level, we treat it as high blood pressure (HBP). Present days, HBP victims are growing in number across the globe. BP may be elevated because of change in biological or psychological state of a person. In this paper, we considered attributes such as age, anger, and anxiety (AAA) and obesity (+), cholesterol level (+) of a person to predict whether a person is prone to HBP or not. Obesity and cholesterol levels are considered as post-increment of AAA, where obesity as one +, and total blood cholesterol as another + because experimental results reveal that their impact is less comparatively AAA. In our technique, we used different classifiers for prediction, where each classifier considers the impact of each A in AAA along with obesity and cholesterol level of a person to predict whether a person becomes a victim of HBP or not. Random forest algorithm has shown 87.5% accuracy in prediction

Hepatic cholesterol content in nutritional disorders

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Automatic disease diagnosis using optimised weightless neural networks for low-power wearable devices

Low-power wearable devices for disease diagnosis are used at anytime and anywhere. These are non-invasive and pain-free for the better quality of life. However, these devices are resource constrained in terms of memory and processing capability. Memory constraint allows these devices to store a limited number of patterns and processing constraint provides delayed response. It is a challenging task to design a robust classification system under above constraints with high accuracy. In this Letter, to resolve this problem, a novel architecture for weightless neural networks (WNNs) has been proposed. It uses variable sized random access memories to optimise the memory usage and a modified binary TRIE data structure for reducing the test time. In addition, a bio-inspired-based genetic algorithm has been employed to improve the accuracy. The proposed architecture is experimented on various disease datasets using its software and hardware realisations. The experimental results prove that the proposed architecture achieves better performance in terms of accuracy, memory saving and test time as compared to standard WNNs. It also outperforms in terms of accuracy as compared to conventional neural network-based classifiers. The proposed architecture is a powerful part of most of the low-power wearable devices for the solution of memory, accuracy and time issues

W.H.O. Sponsored collaborative studies on nutritional anaemia in India. 1. The effects of supplemental oral iron administration to pregnant women

A W.H.O. sponsored collaborative study of the effects of iron supplementation to pregnant women was carried out in Delhi (northern India) and Vellore (southern India). Supplementation was given under supervision from the 26th to the 36th or 38th week of pregnancy. A control group received only placebo; one group received vitamin B12 and folic acid alone; four groups received vitamin B12, folate and a daily iron supplement ranging from 30 to 240 mg of elemental iron as ferrous fumerate, and one further group received 120 mg of iron without B12 or folate. Groups receiving no iron showed a fall in mean haemoglobin concentration. Those receiving iron showed a rise in haemoglobin, the best results being in the groups receiving 120 and 240 mg of iron together with vitamin B12 and folate. Even in these groups however there was still a high prevalence of anaemia and iron deficiency at the end of the trial period. Iron alone did not produce as good results as iron plus vitamin B12 and folate. The supplementation had no detectable effect on the birth weight of the children, nor on the haemoglobin concentration of the infants at three months of age. The daily absorption of iron in the pregnant women, as judged from the increase in haemoglobin mass, was not as satisfactory as expected. Possible reasons for this are discussed. It is concluded that to provide these women with adequate iron a daily oral supplementation of 120 mg of elemental iron or more is needed. This can only be achieved by medicinal means. Before supplementation can be recommended on a public health scale, further information regarding the cost and expected benefits of such measures must be obtained