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Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Breast cancer has become common cancer which is seen in most of womens. To decrease the related mortality cancer mustbe treated early. But it is hard to detect and diagnose tumor at an early stage. It will take lot of time if we go for manual detection and it is very inefficient. Hence there is need for efficient method that diagnoses the cancer with less time and high accuracy. So in our project we are using technique called ANN as a decision making tool in field of breast cancer. Image Processing plays important role in cancer detection when input data is in the form of images. Feature extraction of image is important in mammogram classification. Features are extracted by using image processing. Different feature extraction methods used for classificationof normal and abnormal patterns in mammogram. This method will give maximum accuracy at a high speed. The parameter include in feature extraction is Mean and Entropy. This parameters are inputs to ANN which will diagnose and give the result whether image is cancerous and non-cancerous.

Solid state decomposition studies of Low and High Density Polyethylene (LDPE and HDPE) have been carried out in the present work. Thermo-gravimetric analysis (TGA) is utilized to determine the degradation kinetics for pure plastic samples at different heating rates. The distribution of activation energy values and rates estimated using various Iso-conversional methods have been selected on basis of correlation coefficients. For LDPE, isoconversional method of Friedman and for HDPE Flynn Wall Ozawa methods are used to estimate the distribution of activation energies having their mean values as 256.5 and 257.2 kJ/mol respectively. The inputs from Isoconversional methods are used to determine decomposition behavior with Criado method. Model based studies performed with Criado method identifies the solid-state degradation follows contracting volume-sphere (R3) model based on lower statistical parameter values. The identified decomposition model is validated by Coats Redfern method which also results in lower statistical parameter values. This is further validated through a best fit of extent of reaction profile against temperature, substantiating the solid-state decomposition model followed by given plastic fractions.

Today’s in the global era of digital word, things are changing and evolving around the health care professional with a patient centricity and a integrated approach for a better and healthier society, the access for accurate information for the patients is crucial to deliver the best solution for the society at large. Tools to engage the health care professionals to make them confident and improve the current practices are always on the priority, through several multi channel engagement tools that allow them to enhance the capability of their diagnostic and treatment pattern for a particular disease area while keeping the patient centricity view in the back of mind and to provide best possible solution for their customers. the purpose of the study is to analyze the impact of multi channel engagement tools on the quality of care provided by a health care professional actively serving the best practice for the community, quality information about the relevant therapy area for health care professional through email, website and conducting scientific webinar. 200 health care professionals from the hospital, private clinics were the part of this study and the given responses were analyzed and treated through statistical parameter for drawing the conclusion. the results showed that the information through the email, website marketing and scientific sessions may contribute the quality practice of health care professionals. Key words: health care professional, multi channel engagement tool, statistical parameter, scientific session., Hoje em dia, na palavra digital global, as coisas que envolvem o cuidado profissional da saúde estão mudando em termos de foco no paciente e abordagem integrada para uma sociedade melhor e mais saudável, o acesso a informações precisas é crucial para oferecer a melhor solução para a sociedade em geral. Ferramentas para envolver profissionais de saúde. Os profissionais para torná-los confiantes e melhorar suas práticas atuais são sempre prioritários através de várias ferramentas de engajamento multicanal que lhes permitem melhorar seu diagnóstico e capacidade de tratamento padrão para uma determinada área de doença, mantendo a atenção para a melhor solução para seus clientes. O objetivo do estudo é analisar o impacto das ferramentas de engajamento multicanal na qualidade dos cuidados prestados por um profissional de saúde que atua ativamente nas melhores práticas para a comunidade, informações de qualidade sobre a área de terapia relevante para profissionais de saúde por meio de e-mail, site e Realização de webinar científico. 200 profissionais de saúde de hospitais, clínicas privadas fizeram parte deste estudo e as respostas dadas foram analisadas e tratadas através de parâmetros estatísticos para chegar à conclusão. Os resultados mostram que as informações provenientes de e-mail, marketing de sites e sessões científicas podem contribuir para uma prática qualificada de profissionais de saúde.

Today’s in the global era of digital word, things are changing and evolving around the health care professional with a patient centricity and a integrated approach for a better and healthier society, the access for accurate information for the patients is crucial to deliver the best solution for the society at large. Tools to engage the health care professionals to make them confident and improve the current practices are always on the priority, through several multi channel engagement tools that allow them to enhance the capability of their diagnostic and treatment pattern for a particular disease area while keeping the patient centricity view in the back of mind and to provide best possible solution for their customers. the purpose of the study is to analyze the impact of multi channel engagement tools on the quality of care provided by a health care professional actively serving the best practice for the community, quality information about the relevant therapy area for health care professional through email, website and conducting scientific webinar. 200 health care professionals from the hospital, private clinics were the part of this study and the given responses were analyzed and treated through statistical parameter for drawing the conclusion. the results showed that the information through the email, website marketing and scientific sessions may contribute the quality practice of health care professionals. Key words: health care professional, multi channel engagement tool, statistical parameter, scientific session., Hoje em dia, na palavra digital global, as coisas que envolvem o cuidado profissional da saúde estão mudando em termos de foco no paciente e abordagem integrada para uma sociedade melhor e mais saudável, o acesso a informações precisas é crucial para oferecer a melhor solução para a sociedade em geral. Ferramentas para envolver profissionais de saúde. Os profissionais para torná-los confiantes e melhorar suas práticas atuais são sempre prioritários através de várias ferramentas de engajamento multicanal que lhes permitem melhorar seu diagnóstico e capacidade de tratamento padrão para uma determinada área de doença, mantendo a atenção para a melhor solução para seus clientes. O objetivo do estudo é analisar o impacto das ferramentas de engajamento multicanal na qualidade dos cuidados prestados por um profissional de saúde que atua ativamente nas melhores práticas para a comunidade, informações de qualidade sobre a área de terapia relevante para profissionais de saúde por meio de e-mail, site e Realização de webinar científico. 200 profissionais de saúde de hospitais, clínicas privadas fizeram parte deste estudo e as respostas dadas foram analisadas e tratadas através de parâmetros estatísticos para chegar à conclusão. Os resultados mostram que as informações provenientes de e-mail, marketing de sites e sessões científicas podem contribuir para uma prática qualificada de profissionais de saúde.