Messages and Manifestations Moving Forward Mindfully: A Compilation of Linked in Messages in Keeping the Community Connected

The book is a self-help book for those trying to find a purpose in life and practice mindfulness. Through exploration we learn much more about ourselves. Through sharing we build stronger communities. When you get a good opportunity to change and making a decision is hard, go with your intuition what you feel is right is usually what you should be doing. You don\u27t need a lot of money or time. If you manage your time, a simple gesture can make the world of difference in someone\u27s life. Always learn to break the routine and go back and practice something you enjoy doing rather than something you have to do. We tend to overcomplicate our lives with things we don\u27t need but want. When you learn to separate from the needs vs the wants you can become a happier person. Get out of your comfort zone and explore what life has in store for you

Posterior reversible encephalopathy syndrome (PRES) after bevacizumab therapy for metastatic colorectal cancer.

Posterior reversible encephalopathy syndrome (PRES) is an increasingly recognizable neuro-clinical syndrome. Clinical and neurological manifestations of PRES include hypertension, headache, encephalopathy, seizures, and symmetrical white matter changes on brain MRI. Most common precipitants of PRES are acute medical illness, hypertensive crisis, eclampsia, immunosuppressive therapy, and chemotherapy. Bevacizumab is a monoclonal antibody that halts angiogenesis by inhibiting vascular endothelial growth factor. It has gained widespread popularity in oncology world especially for metastatic and recurrent cancers due to its inherent ability to stop angiogenesis; a vital step for tumor growth. Bevacizumab has also been implicated as the cause of PRES due to dysregulation of the blood-brain barrier. We are reporting a case of PRES induced by Bevacizumab in a patient of colorectal cancer

An Empirical Analysis of New Product by Using Models of Market Research (2013)

A biggest task for strategy maker, to perform market insights and its research by designing, collection of data with analyzing and reporting data (relevant) for specific purpose and market situation (problem) facing the company. However it requires spending a lot of time over it so several companies hire many professional experts having a knowledge regarding with technical operation of research like (syndicated-service research firms, custom-marketing research firms and specialty-line marketing research firms)

An Empirical Analysis of New Product by Using Models of Market Research (2013)

A biggest task for strategy maker, to perform market insights and its research by designing, collection of data with analyzing and reporting data (relevant) for specific purpose and market situation (problem) facing the company. However it requires spending a lot of time over it so several companies hire many professional experts having a knowledge regarding with technical operation of research like (syndicated-service research firms, custom-marketing research firms and specialty-line marketing research firms)

Better Physical Activity Classification using Smartphone Acceleration Sensor

Obesity is becoming one of the serious problems for the health of worldwide population. Social interactions on mobile phones and computers via internet through social e-networks are one of the major causes of lack of physical activities. For the health specialist, it is important to track the record of physical activities of the obese or overweight patients to supervise weight loss control. In this study, acceleration sensor present in the smartphone is used to monitor the physical activity of the user. Physical activities including Walking, Jogging, Sitting, Standing, Walking upstairs and Walking downstairs are classified. Time domain features are extracted from the acceleration data recorded by smartphone during different physical activities. Time and space complexity of the whole framework is done by optimal feature subset selection and pruning of instances. Classification results of six physical activities are reported in this paper. Using simple time domain features, 99 % classification accuracy is achieved. Furthermore, attributes subset selection is used to remove the redundant features and to minimize the time complexity of the algorithm. A subset of 30 features produced more than 98 % classification accuracy for the six physical activities

Role of AI and digital pathology for colorectal immuno-oncology

Immunotherapy deals with therapeutic interventions to arrest the progression of tumours using the immune system. These include checkpoint inhibitors, T-cell manipulation, cytokines, oncolytic viruses and tumour vaccines. In this paper, we present a survey of the latest developments on immunotherapy in colorectal cancer (CRC) and the role of artificial intelligence (AI) in this context. Among these, microsatellite instability (MSI) is perhaps the most popular IO biomarker globally. We first discuss the MSI status of tumours, its implications for patient management, and its relationship to immune response. In recent years, several aspiring studies have used AI to predict the MSI status of patients from digital whole-slide images (WSIs) of routine diagnostic slides. We present a survey of AI literature on the prediction of MSI and tumour mutation burden from digitised WSIs of haematoxylin and eosin-stained diagnostic slides. We discuss AI approaches in detail and elaborate their contributions, limitations and key takeaways to drive future research. We further expand this survey to other IO-related biomarkers like immune cell infiltrates and alternate data modalities like immunohistochemistry and gene expression. Finally, we underline possible future directions in immunotherapy for CRC and promise of AI to accelerate this exploration for patient benefits

An Aggregation of Aggregation Methods in Computational Pathology

Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide images (WSIs) often process a large number of tiles (sub-images) and require aggregating predictions from the tiles in order to predict WSI-level labels. In this paper, we present a review of existing literature on various types of aggregation methods with a view to help guide future research in the area of computational pathology (CPath). We propose a general CPath workflow with three pathways that consider multiple levels and types of data and the nature of computation to analyse WSIs for predictive modelling. We categorize aggregation methods according to the context and representation of the data, features of computational modules and CPath use cases. We compare and contrast different methods based on the principle of multiple instance learning, perhaps the most commonly used aggregation method, covering a wide range of CPath literature. To provide a fair comparison, we consider a specific WSI-level prediction task and compare various aggregation methods for that task. Finally, we conclude with a list of objectives and desirable attributes of aggregation methods in general, pros and cons of the various approaches, some recommendations and possible future directions.Comment: 32 pages, 4 figure

Modernism in the eyes of T.S Eliot: break from traditional writings with literary forms and movements

This paper owes to uncover the modern aspects in the writings of T. S. Eliot. Modernism, a movement which erupts from philosophy and has a “self-conscious” break from traditional writings and worked with literary forms and movements. As a modernist he portrays about the standard of love, money minded people and self centered people. The research is entirely based on T. S. Eliot’s poetry and generalizing its work entirely which required depth study of his work and citation of the critic who entitled T. S. Eliot as a “modernist-poet”. This study is retro-spective which requires depth study in order to relate by the previous work done on generalizing T. S. Eliot as a modernist poet