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Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics , Biomedical informatics , and machine learning , with the goal of understanding biological and medical data.
This field deals with utilization of machine-learning algorithms and artificial intelligence, to emulate human cognition in the analysis, interpretation, and comprehension of complicated medical and healthcare data. Specifically, AI is the ability of computer algorithms to approximate conclusions based solely on input data.
Artificial intelligence in healthcare is the application of artificial intelligence (AI) to analyze and understand complex medical and healthcare data. In some cases, it can exceed or augment human capabilities by providing better or faster ways to diagnose, treat, or prevent disease.
Studierfenster (StudierFenster) is a free, non-commercial Open Science client/server-based Medical Imaging Processing (MIP) online framework. [52] Medical open network for AI is a framework for Deep learning in healthcare imaging that is open-source available under the Apache Licence and supported by the community. [53]
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The first group of these services is known as primary care services in the domain of digital health. These services include wireless medical devices that utilize technology such as Wi-Fi or Bluetooth, as well as applications on mobile devices that encourage the betterment of an individual's health as well as applications that promote overall general wellness. [13]
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Other projects like AgeGuess [8] focus on the senior demographics and enable the elderly to upload photos of themselves so the public can guess different ages. Lists of citizen science projects may change. For example, the Old Weather project website indicates that as of January 10, 2015, 51% of the logs were completed. [9]