Advanced embedding details, examples, and help! Topics Genomic , Medicine. About this course: Precision medicine has the potential to change fundamentally how health care is practiced, but requires a health care workforce that understands the complexities of this field. Our course aims to provide participants with some baseline knowledge of genomics, an overview of the clinical applications of genomic medicine, the skills to evaluate the clinical validity and utility of new tests, and an appreciation of the associated ethical and social issues inherent in this field.
The course is geared toward practicing health care providers, although it should be accessible to anyone with a background in the biological sciences and a basic understanding of genetics. It is designed to be succinct and clinically-focused, offering both conceptual and practical information about real-world applications of genomics. Two lessons offer a basic primer on molecular genomics relevant to the individual patient as well as to patient populations.
The remaining five lessons focus on five applications of genomics and present the material as case studies, highlighting the strengths, limitations, and issues that arise in the use of each test. There are no reviews yet. Raviraja Shetty. G ecourses. Chandel ecourses. Shukla ecourses. Srinivasa ecourses. Meyyazhagan ecourses. Download Winrar Software B.
The courseware material is prepared as per ICAR approved syllabus for the benefit of under-graduate students already enrolled in Indian Agricultural Universities. Select to Download Desired e-Course. Course Title. Author s Name. Prasanth Rajan. Durga Devi. Kalyana Sundaram. Mukesh L Chavan. Anand B Masthihole. Meenakshi Ganesan. Ankita Sinha. A short summary of this paper. The given data is restricted to the city of Wisconsin and relates to patients in the age group years.
The agency wants to analyze the data to research on the healthcare costs and their utilization. Workflow Description I have used R-language to work on the project and analyze the data. It includes: Min. Based on the output we can see the list of Expenditure based on the Diagnosis and treatment.
Annova test is being used to analyze the Race wise cost occured The Residual Value deviation of the observed value is very high specifying that there is no relation between the race of patient and the hospital cost. From the summary we can also see that the data has patients of Race 1 out of the entries.
Hence we can conclude that there is no race wise cost biasness in the observed data. To properly utilize the costs, the agency has to analyze the severity of the hospital costs by age and gender for proper allocation of resources.
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