ShareMind - Health Analytics
Health Analytics, branded as ShareMind, is a platform that combines predefined machine learning models with data analysis for researchers to develop their models. Researchers can contribute to the system's progress by using the platform worldwide.
- Effective & secure healthcare solutions
- Better outcomes with predictive analytics
- Reaching analysis directly from a platform without data sharing
- Difficulties in handling large numbers of live health data
- Obtaining clean and validated data
After implementing Exchange-Hub, it will be possible to collect and record large amounts of data accurately and reliably within the framework of health activities. As the volume of data increases, meaningful information can be generated by analyzing these data and scientific studies that will make possible breakthroughs in the health field possible.
Data scientists need help with conducting their research. The most crucial problem is the difficulty in accessing data. Mainly, there are great difficulties in obtaining clean and validated data. The other problem is the complexity of the tools and infrastructures that should be used in data analysis. On the one hand, while learning the programming languages to be used in research, on the other hand, it is a severe problem to install and configure the necessary software and hardware tools for the processing of data on a large scale.
Nowadays, billions of records have begun to be formed in operational systems with the problem of data collection. Processing this data requires using scalable data storage and processing systems rather than standard systems. These systems are created within the expertise of those involved in data science, creating severe barriers to working with big data. ShareMind is an exceptional data analysis and machine learning platform developed to minimize all these problems.
With ShareMind, data scientists can use the time they spend accessing and cleaning data for modeling and more inferences can be obtained from the data. In addition, it is now sufficient to learn only the programming language and the necessary libraries without knowing all the tools. Data scientists can sustain the models they create and their gains will not be lost.
ShareMind's infrastructure systems will be able to scale automatically as the workforce increases, thus serving more and more users. In addition, data security is one of the most critical components of health. This infrastructure provides solutions to data security concerns by authorizing access to data according to the research topic and needs.
Innovations
- Scalable platform
- Ease of use of tools and infrastructures that are used in data analysis
- Worldwide researchers can contribute to the progress of the system
- ML on health data
Benefits
Benefits for Researchers
- Data scientists can sustain the models they create on the platform; their gains will be recovered after publishing the articles.
- Data scientists can use the time they spend accessing and cleaning data for modeling.
- Providing solutions to data security concerns by providing authorization to access data according to the research topic and needs
- Allowing working / analysis directly from the platform without data sharing
- Reliable and collaborative platform
Benefits for Healthcare Professionals & Managers, Health System and Regulatory Organizations
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Helping family physicians diagnose and treat rural and small cities
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Ensuring continuous monitoring of quality, efficiency and control with recommendations for health service providers and managers
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Possibility to use the results by many stakeholders, such as healthcare providers, pharmaceuticals and insurance companies
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Possibility to collect and record large amounts of data