Volume 11 | Issue 1 |

 Abstract

Background: Women are diagnosed with breast cancer every year more than 1.3 million. The most common consequences of breast cancer diagnosis and treatment is psychological stress with the symptoms of anxiety and depression. During the early postsurgical period leading to limitation in daily activities it has been reported that pain, fatigue, decreased range of motion (ROM) and decreased muscle strength have developed. Virtual reality (VR) that allows users to immerse themselves in a three-dimensional computer generated word has found a variety of application in health care over the last two decade and in particular has been shown efficacy as distraction to alleviate and pain including chemotherapy during medical procedure. Purpose of Study: The purpose of this study was to find out the effect of Virtual Reality Exercises on Handgrip strength, Pain, Anxiety and Depression in Post-mastectomy Patients. Material And Methodology: Following an explanation of the study to participants, signed agreement was obtained. 60 participants female were included. Pre assessment (Anxiety measured by using IES; Depression measured by using CES-D; Pain measured by using VAS; Hand grip strength measured by using electronic hand dynamometer) were done. Post assessment (after 6 weeks Anxiety measured by using IES; Depression measured by using CES-D; Pain measured by using VAS; Hand grip strength measured by using electronic hand dynamometer) were done.Treatment was given one session daily, 6 days a week for 6 consecutive weeks. Results: The statistical analysis was done using paired t test, which showed significant improvement in post exercise protocol. Conclusion: The result of the study shows that VR exercises has excellent improvement in terms of hand grip strength, pain, anxiety and depression.

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 Keywords

Virtual reality (VR), The impact of events scale (IES), The center for epidemiological studies depression scale (CES-D), Visual analogue scale (VAS), Handgrip strength (HGS), Range of motion (ROM), Electronic Hand Dynamometer (EHD).

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Lagenaria sicerari has been traditionally used in Indian medicine as a result of its curative results of hepatitis, gonorrhea and diabetes, it is probably not proof-founded. However folklore has given us many powerful therapies, based on plant sources. So claims which can be made for the protective efficacy of Lagenaria sicerari (family: Cucurbitaceae) to treat hepatic diseases. The present study focused on investigating the role of alcoholic extract of Lagenaria sicerari. It appreciably prevented the increased in serum Aspartate amino transferase (AST), Alanine amino transferase (ALT), alkaline phosphatase (ALP) and total serum bilirubin (SB) level in acute liver damage by Acetaminophen and elevated the activities of lipid peroxidation (LPO) and glutathione (GSH) in the liver. Histopathological observation of the liver used to be additionally performed to further support the evidence from the biochemical analysis. The observation that these significant protective effect against acute hepatotoxicity induced by acetaminophen of Lagenaria sicerari.

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Hepatoprotective Activity of Lagenaria sicerari Extract against Paracetamol Induced Hepatic Damage in Rats

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Fruit disease detection is vital at early stage since it will affect the agricultural field. In this paper, mainly consider the detection and analysis of fruit infections which is available in the plant areas and storage of data about the agricultural filed and details of farmers in database and recovering the data using Cloud computing. There are more fruit diseases which occur due to the surrounding conditions, mineral levels, insects in the farm area and other factors. The detected data from the plant area is determined by image processing and stored in the database.

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 Keywords

K-Means clustering; Support Vector Machine

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Lung cancer is one of the deadliest types of cancer; thousands of people are infected with this type of cancer, and if it is not detected in the early stages of the disease, then the patient's chance of survival will be very small. For the above reasons and to help overcome this terrible early diagnosis with the help of artificial intelligence procedures are most needed. It is also one of the most common and contributing to death among all cancers. Cases of lung cancer are increasing rapidly. There are about 70,000 cases a year in India. In the past decade, cancer detection using deep learning models has been a hot topic, especially in medical image classification. It is worth noting that CNN models are more advanced in dealing with the diagnosis of diseases such as lung cancer due to the higher performance and capabilities of CNNs. This system presents an approach that uses a convolutional neural network (CNN) to classify tumors located in the lungs as malignant or benign. The accuracy obtained by CNN is 99%, which is more efficient compared to the accuracy achieved by traditional existing systems. This is done by applying a convolutional neural network technique to a dataset of lung cancer CT scans.

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lung, computed tomography, convolutional neural network, detection, classification

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In the present dynamic financial service environment the role of E-banking occupies a significant position .The post banking sector reforms have transformed the entire banking sector. The emergence of technology in the banking services has made anywhere any time banking. The e banking services has enabled customer to have financial services at their fingertips .It is in this context that the present research paper attempts to analyze the role of E banking towards customer satisfaction and the employees perception in Public and Private Sector Banks in India with reference to Prayagraj District of Uttar Pradesh The present study is based on Primary and Secondary sources . The data indicated that the perception of customer regarding service quality and satisfaction of employee in internet banking services. The present study also attempts to make a comparison between Public and Private sectors banks in respect of SBI and HDFC bank. The findings of the study reveal that the sample respondents have more s account with private banks. The problem faced by the respondents were more in public sector banks. The analysis indicated that the sample respondents were of the view that the employees of the sample banks should have a change in the behavior of the staff of the public sector banks The respondents were more satisfied from the private sector banks due to their better services provided by them. The facility that was availed by most of the people at private sector banks was that of Internet/ Phone banking by ATM/Debit card.

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; e-banking, consumer, internet banking, knowledge management

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According to a recent WHO report, about 450 million people are affected by mental, neurological and behavioural problems in their lives and among these 873,000 people die of suicide every year with mental illnesses. People with mental disorders usually suffer from social isolation, poor quality of life and has an increased change for mortality (WHO report, 2005). Mental illnesses have been found to be precipitated with chronic conditions of cancer, cardiovascular diseases, diabetes and AIDS.

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A STUDY TO ASSESS THE EFFECTIVENESS OF VIDEO ASSISTED TEACHING ON KNOWLEDGE REGARDING IDENTIFICATION AND PREVENTION OF SUICIDE AMONG CAREGIVERS OF MENTALLY ILL PATIENT IN SELECTED HOSPITALS AT MEERUT

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Pharmacists for starters want to expand their dispensing services they want to give patients better and more frequent advice on how to use prescribed medications. Patients will benefits for from the development of domicile any services , particular in terms of collecting and delivering prescriptions for the elderly, mentally ill, and physically disabled. Health is a word very known but it carries a lot of complications and troubles. According to the WHO, health is a state of complete physical, mental and social well-being and not merely absence of any illness. Health care system depends upon a health care team. A health care team is the group of community who contribute to a common health goal and common objectives determined by community needs. India with the greatest cultural diversity, health though an important issue is being neglected due to many hindrances. The condition is more worsened due to inappropriate drug use problems. It is in the hands of the pharmacist particularly the community pharmacist, to take up the challenge for providing better health care and better outcomes reasonably.

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Akkamahadevi Mattu Honnammara Druttiyalli Kutumba-Dampathya

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Akkamahadevi Mattu Honnammara Druttiyalli Kutumba-Dampathya

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The use of images to identify people has become commonplace thanks to the media. It is less resistant to retinal scanning or fingerprint detection, though. The face is described in this report and find in the database using a machine learning project carried out for the module on visual perception and autonomy. The basic emotions that all people experience are universal and are consistently expressed on their faces. Here, an algorithm is described that carries out the detection, extraction, and evaluation of various facial expressions enabling, automatic identification of human emotion in pictures and videos. It outlines the technologies offered by the OpenCV library as well as the process for putting them into practise with Python. Haar-Cascades were utilised for face detection, and Eigenfaces, Fisher faces, and local binary pattern histograms were displayed here for face identification.

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 Keywords

Input Face, Face Detection, Face Recognition, classification, Identify the Face.

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Data analysis and exploration are necessary for machine learning in order to identify significant trends and patterns. Everyone on Earth relies on allopathic therapies and medications in the modern era. Medical datasets can benefit from machine learning techniques since they offer a wide range of opportunities for both textual and visual data. Data mining is the key to extracting insight from these voluminous, enigmatic data that are present in medical services. This paper presents an API for prescribing medications to users with a certain ailment, which would also be diagnosed by the framework through the analysis of the user's symptoms using machine learning techniques. Here, we make use of some insightful data pertaining to the mining process to identify the most precise illness that may be associated with symptoms. The condition is easily identifiable by the sufferer. Patients may clearly identify their disease by merely attributing their symptoms, and the program interface indicates what disease the user may be infected with. The framework will show complacency in urgent instances where the patient cannot go to a doctor's office or in circumstances where professionals are available in the area. By considering numerous features in the database, predictive analysis on the illness would be carried out, leading to the recommendation of drugs to the user. The outcomes of the experiment can also be applied to healthcare tools and future research.

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 Keywords

Machine learning, Drug recommendation, knowledge base, Logistic Regressions, symptoms, Support Vector Machine, Disease Predictions.

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