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As more data is collected, machine learning algorithms adapt and allow for more robust responses and solutions. [111] Numerous companies are exploring the possibilities of the incorporation of big data in the healthcare industry. Many companies investigate the market opportunities through the realms of "data assessment, storage, management, and ...
Medical open network for AI (MONAI) is an open-source, community-supported framework for Deep learning (DL) in healthcare imaging. MONAI provides a collection of domain-optimized implementations of various DL algorithms and utilities specifically designed for medical imaging tasks.
In the healthcare industry, health informatics has provided such technological solutions as telemedicine, surgical robots, electronic health records (EHR), Picture Archiving and Communication Systems (PACS), and decision support, artificial intelligence, and machine learning innovations including IBM's Watson and Google's DeepMind platform.
This includes pharmaceuticals, devices, procedures, and organizational systems used in the healthcare industry, [2] as well as computer-supported information systems. In the United States, these technologies involve standardized physical objects, as well as traditional and designed social means and methods to treat or care for patients. [3]
For example, there is a prototype, photonic, quantum memristive device for neuromorphic (quantum-)computers (NC)/artificial neural networks and NC-using quantum materials with some variety of potential neuromorphic computing-related applications, [367] [368] and quantum machine learning is a field with some variety of applications under ...
In order for any potential AI health and safety application to be adopted, it requires acceptance by both managers and workers. For example, worker acceptance may be diminished by concerns about information privacy, [7] or from a lack of trust and acceptance of the new technology, which may arise from inadequate transparency or training.