Statistical_Platform_Presentation
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The document discusses building a statistical platform to provide health researchers and administrators with real-time data analysis tools and a repository of disease registry and project information. The platform aims to support research by allowing data to be analyzed through different search parameters and models while preserving patient confidentiality. It is intended to help determine where and when to intervene, improve care quality, increase access, find cost-effective solutions, and satisfy research needs for accessible data.
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Health and Biomedical Informatics Centre @ The University of MelbourneHealth and Biomedical Informatics Centre @ The University of Melbourne
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The Health and Biomedical Informatics Centre (HaBIC) conducts activities in education, translational research informatics, e-health and participatory health research, informatics for precision medicine research, and engagement. Key activities include developing education strategies in health and biomedical informatics, providing expertise and tools to support health data collection and management for research, conducting e-health and participatory health research on topics like telehealth and self-quantification, and developing informatics approaches and systems to integrate and analyze genomic and clinical data to facilitate precision medicine research.
Information Products to Drive Decision Making
This document discusses information products to drive decision making in health systems. It summarizes research conducted in Kenya and Tanzania on the availability and use of information products from routine health information systems. Key findings include that staff value regular, standardized information products that provide feedback on performance against targets and recommendations for improvement. However, limited workforce and technical capacity are barriers to effective data use. The presentation provides examples of how information products can be designed and tested to promote greater use of routine health data for decision making.
HEALTH PREDICTION ANALYSIS USING DATA MINING
Data mining techniques are used for a variety of applications. In healthcare industry, datamining plays an important
role in predicting diseases. For detecting a disease number of tests should be required from the patient. But using data
mining technique the number of tests can be reduced. This reduced test plays an important role in time and performance.
This report analyses data mining techniques which can be used for predicting different types of diseases. This report reviewed
the research papers which mainly concentrate on predicting various disease
The Role of Data Lakes in Healthcare
The document discusses the role of data lakes in healthcare. It defines a data lake as a system that holds large amounts of raw data from various sources in its original format to enable analysis. Data lakes allow healthcare organizations to gain insights from patient outcomes, fraud detection, clinical trials, and more. Examples of potential use cases in healthcare include genomic analytics, improving clinical trials, predictive healthcare costs, creating a 360-degree view of patients, identifying billing opportunities from unstructured text, and psychographic prescriptive modeling. The document outlines best practices for assessing the need for a data lake, planning, implementing, and governing a data lake project in a healthcare organization.
Digital webinar master deck final
Federated Learning (FL) is a learning paradigm that enables collaborative learning without centralizing datasets. In this webinar, NVIDIA present the concept of FL and discuss how it can help overcome some of the barriers seen in the development of AI-based solutions for pharma, genomics and healthcare. Following the presentation, the panel debate on other elements that could drive the adoption of digital approaches more widely and help answer currently intractable science and business questions.
Advanced Analytics for Clinical Data Full Event Guide
This document provides information about the "Advanced Analytics for Clinical Data" conference to be held February 1-2, 2017 in San Francisco. The conference will focus on applying advanced analytics and data-driven methodologies in clinical research and drug development. It will feature presentations from experts in clinical data science from major pharmaceutical companies. Topics will include implementing analytics from areas like biostatistics, omics, and wearables. Attendees will learn how to extract value from large datasets and new sources of data. The agenda also includes panels on leveraging big data in clinical trials and evolving the role of clinical data management.
National Workshop to Advance Use of Electronic Data
The webinar slide presentations from the July 2-3, 2012 National Workshop to Advance Use of Electronic Data.
Lessons from the UK: Data access, patient trust & real-world impact with heal...
HDR UK is facilitating health data access in the UK for researchers through The Innovation Gateway. This allows researchers to discover and access de-identified health data from various custodians. HDR UK has emphasized transparency and patient/public involvement. During the COVID-19 pandemic, HDR UK coordinated data-driven research efforts and accelerated data access to support priority studies. This included enabling a clinical trial to more rapidly recruit participants using daily COVID test results. HDR UK is also laying the foundations for an international health data alliance to support open COVID-19 research globally.
Building a National Data Infrastructure to Advance Patient-Centered Comparati...
Building a National Data Infrastructure to Advance Patient-Centered Comparati...Patient-Centered Outcomes Research Institute
Executive Director Joe Selby's slide presentation at the National Press Club Roundtable event on April 22, 2013. Big Data Analytics using in Healthcare Management System
Big data is the new technology for healthcare management system. Present day's big data analytics are using in everywhere because of its good data management and its large storage capacity. In hospital managements the patients and doctors record keeping safe is the important role in healthcare system. In worldwide the big data method is extended use in the area of medicine and healthcare system. In this sector so many problems are there in implementing big data in healthcare system especially in relation to securities, privacy matters, standard records, good governance, managing of data, data storing and maintenance, etc. It is critical that these challenges to overcome before big data can be implemented successfully in healthcare. The amount of data being digitally collected and stored safely in big data Hadoop clusters. This paper introduces healthcare data, big data in healthcare systems, applications, advantages, issues of Big Data analytics in healthcare sector. Gagana H. S | Bhavani B. T | Gouthami H. S "Big Data Analytics using in Healthcare Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd31014.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/31014/big-data-analytics-using-in-healthcare-management-system/gagana-h-s
Demand connected medical devices to improve military EHRs
This document summarizes a presentation about improving military electronic health records (EHRs) by procuring connected medical devices. The presentation argues that medical devices are the best sources of clinical data but current devices are not designed for connectivity. It recommends changing procurement policies to require devices support inherent connectivity using open standards. This would help fill EHRs with more useful data for research and interoperability.
Clinical research innovation hub walking deck v12
This document outlines a vision for accelerating innovation in clinical research through digital transformation. It discusses current challenges such as slow recruitment, high costs, and lack of data sharing. The transformation framework proposes 3 waves of progress:
1) Incremental improvements to existing systems through better standardization and digitization.
2) Dramatic improvements using artificial intelligence and a common data platform to provide deeper insights.
3) Fully integrated research and care where data is continuously gathered in real-world settings to evaluate treatments over time.
The goal is to reduce patient burden, improve access to new therapies, and make research data more broadly available to accelerate discovery.
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Health and Biomedical Informatics Centre @ The University of Melbourne
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The Health and Biomedical Informatics Centre (HaBIC@UoM)
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Statistical_Platform_Presentation
- 1. DATA DYNAMICS USING THE POWER OF STATISTICS Shazia Naz Subhani Senior IT Specialist, Bioinformatician Project Manager Saudi Human Genome Program, Riyadh, Saudi Arabia
- 2. Our imagination is the only limit to what we can hope to have in the future. ~ Charles F. Kettering Ability is of little account without opportunity ~ Napoleon
- 4. Objectives To provide a unique real time statistical platform for researchers and health administrators that will assist them in making sound decisions. To provide state of the art repository of information on various disease registries and national projects. To make available the non-identifiable health research data for browsing and queries.
- 5. The platform supports research by providing a dynamic interface for health researchers and administrators where, data can be analyzed in different dimensions using a variety of search parameters and data models.
- 6. Conclusion Determining where and when to intervene. Improving the quality of care. Increasing accessibility of service. Finding more cost-effective delivery modes. Preserving patient confidentiality while satisfying the needs of the research community for data accessibility. Dynamic Statistics in Health Care Helps in
- 7. Thank you