An efficient data hiding method in images

Data Hiding has a huge range of applications in the medical field for transmission. It is helpful in securing the documentation of the patients from the violator with good storage space. The medical images of different modalities like CT, MRI, and PET with the digitized clinical information can be sent to the doctors across the world for the treatment. Due to the bandwidth and storage constraints, medical images along with the clinical information must be compressed before transmission and storage. This paper gives a technique for hiding the digitized clinical information along with the DICOM images in Complex Contourlet Transform (CCT) Domain. It also analyses the compression method by using an Entropy Encoder method. Hence, this work suggests that the data hiding method based on Complex Contourlet Transform (CCT) is efficient and also it has a high hiding capacity. The improved value of Compression Ratio (CR), Space Saving (SS), Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) shows that the new method satisfies the properties of the data hiding method

Trial of scar in post caesarean pregnancies

Background: The term caesarean delivery used to describe the delivery of a fetus through a surgical incision of the intact anterior uterine wall. The objective of this study was to analyse the maternal and perinatal morbidity between successful VBAC and failed vaginal delivery in cases selected for trial of labour.Methods: Prospective study conducted in Government RSRM Lying In Hospital, Government Stanley Medical College, Chennai over a period of one year from January 2017 to December 2017.Results: Trial of labour in previous caesarean section was more successful when the interval between previous caesarean and present pregnancy was between two to four years 86.40%. Conclusions: Most patients with a prior caesarean birth are candidates for VBAC. In properly selected women, a trial of labour after one previous low transverse caesarean section constitutes the best and safest form of obstetric management

A comprehensive study on disease risk predictions in machine learning

Over recent years, multiple disease risk prediction models have been developed. These models use various patient characteristics to estimate the probability of outcomes over a certain period of time and hold the potential to improve decision making and individualize care. Discovering hidden patterns and interactions from medical databases with growing evaluation of the disease prediction model has become crucial. It needs many trials in traditional clinical findings that could complicate disease prediction. Comprehensive survey on different strategies used to predict disease is conferred in this paper. Applying these techniques to healthcare data, has improvement of risk prediction models to find out the patients who would get benefit from disease management programs to reduce hospital readmission and healthcare cost, but the results of these endeavours have been shifted

A Comprehensive Review on Artificial Intelligence Techniques for Covid-19 Pandemic

The pandemic situation due to the emergence of Covid-19 presents various problems physically, economically and mentally for the individuals world-wide, therefore faster solutions with wider access is essential to solve the problems which aids as a support to the healthcare. This is made possible through the incorporation of Artificial Intelligence (AI) technology to handle the situation of pandemic. This paper aims to present a comprehensive re-view of the applications employed using AI for the problems faced during Covid-19 pandemic. The AI applications involved in screening, predicting, forecasting, neighborhood contact tracing and drug discovery of Covid-19 are addressed in this review. This review also presents detailed working of AI algorithms in each application. This paper helps the researchers with vivid information of AI applications of Covid-19 pandemic

ASSESSMENT OF ANTIOXIDANT ACTIVITIES, PHENOL AND FLAVONOID CONTENTS OF DIFFERENT EXTRACTS OF LEAVES, BARK AND ROOT FROM THE Abutilon indicum (L.) SWEET

Objective: This study evaluated the antioxidant properties of petroleum ether, chloroform, ethyl acetate and methanol extracts of Abutilon indicum (L).Methods: The different extracts of A. indicum leaves, bark and roots  were antioxidant potential by using 1,1-diphenyl-2-picryl-hydrazyl (DPPH), 2, 2-Azino-bis-3-ethyl benzthiazoline-6-sulphonic acid (ABTS•+) , Hydrogen peroxide scavenging, Superoxide anions scavenging,  Hydroxyl radical scavenging, Ferric reducing antioxidant power, Total antioxidant activity (Phosphomolybdic acid) and total phenol and flavonoid contents.                      Results: The highest total phenol and flavonoid contents in leaves extracts of A. indicum. The total phenol (3.08 ± 0.06) mg/ml and flavonoid (7.16 ± 0.15) mg/ml were found to be higher in ethyl acetate extract of A. indicum and free radical scavenging activities IC50 values were calculated and compare to standard for L- ascorbic acid, (BHT) butylated hydroxytoluene and gallic acid    Conclusion:  The results of the study revealed that the ethyl acetate extract of A. indicum leaves can be used for the biological characterization and importance of the compounds identified and creates a platform to screen many bioactive compounds to treat many diseases.Keywords: Abutilon indicum, Free radical scavenging activity, 1,1-diphenyl-2-picryl-hydrazyl, 2-azino-bis-3-ethyl benzthiazoline-6-sulfonic acid,Ferric reducing antioxidant power

A Brief Survey on Cluster based Energy Efficient Routing Protocols in IoT based Wireless Sensor Networks

The wireless sensor network (WSN) consists of a large number of randomly distributed nodes capable of detecting environmental data, converting it into a suitable format, and transmitting it to the base station. The most essential issue in WSNs is energy consumption, which is mostly dependent on the energy-efficient clustering and data transfer phases. We compared a variety of algorithms for clustering that balance the number of clusters. The cluster head selection protocol is arbitrary and incorporates energy-conscious considerations. In this survey, we compared different types of energy-efficient clustering-based protocols to determine which one is effective for lowering energy consumption, latency and extending the lifetime of wireless sensor networks (WSN) under various scenarios

Jaundice Complicating Pregnancy – Maternal and Fetal Outcome

INTRODUCTION: Jaundice in pregnancy, whilst relatively rare, has potentially serious consequences for maternal and fetal health. It can be caused by pregnancy or occur intercurrently. It is responsible for 10% of maternal deaths. The incidence of Jaundice in India varies from 0.4 to 0.9 per 1000 deliveries. Acute vital Hepatitis is the most common cause of Jaundice in pregnancy. Jaundice is a clinical term referring to the yellowish discoloration of Sclera, Mucous Membrane and Skin caused by the accumulation of bilirubin in body fluids. Jaundice is clinically detectable when the serum bilirubin concentration exceeds 2.5 mg per dl in the body fluids AIMS AND OBJECTIVES: 1. To analyze the maternal outcome in terms of mode of termination of pregnancy, maternal morbidity and mortality in jaundice complicating pregnancy. 2. To identify the relation of maternal morbidity and mortality in relation to admission serum bilirubin level. 3. To assess fetal outcome by perinatal mortality and morbidity. 4. To identify the various etiologies and distribution of jaundice with reference to age, parity and trimesters. METHODOLOGY: This is a prospective observational study in The Institute of Obstetrics and Gynaecology from January 2018 to February 2019. 79 pregnant women admitted with Jaundice to Government Women and Children Hospital, IOG, were studied in detail. All relevant history were taken in detail in a pre-designed proforma. They were examined in detail. The results were marked in a master chart and the results were analysed. OBSERVATION: ◈ Of the 79 women studied,maximum (n=44,55.7 %) were in the 21-25 years age group followed by 22.8% in 26-30 years age group,15.2% in 18-20 years age group,3.8 % in 31-35 years age group and 2.5% in > 35 years age group. ◈ Of the 79 women studied 57% were multiparous women and the rest 43% were Primi women. ◈ High coloured urine was the most common symptom seen in 44.3% of the women. Second common symptoms were fever and Nausea & vomiting (40.9% each). Other common symptoms in decreasing order of frequency were loss of appetite (37.4%), upper abdominal (12.2%), pruritis and clay coloured stools. ◈ Icterus was the most commonly elicited sign(60.9 %) followed by hepatomegaly (16.5 %), splenomegaly (6.1%), Scratch marks (3.5%) and ascites (0.9%). ◈ Out of the 79 patients, 40.5% had complications: Complications were Anemia (25.4%), pre-eclampsia (7.6%), hepatorenal failure (5.1%), Hemetemesis and encephalopathy (3.8% each). ◈ The duration of symptoms were mostly between 6-10 days (53.2%) followed by less than 5 days (35.4%), 11-30 days (6.3%) and > 30 days (5.1%). CONCLUSION: The development of jaundice during pregnancy is an important health hazard and needs careful monitoring during antepartum, peripartum and postpartum period. As prevention is better than cure, primary prevention by various health programmes and health education to pregnant women will help to live in a healthy environment. This can be achieved with the help of paramedical staff and mass media. At the secondary and tertiary level a team work by obstetricians, gastroenterologist, neurologist, nephrologists, microbiologist will help to achieve good outcome in jaundiced patients during antenatal, perinatal and neonatal period