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A large part of industry focus of implementation of AI in the healthcare sector is in the clinical decision support systems. As more data is collected, machine learning algorithms adapt and allow for more robust responses and solutions. [100] Numerous companies are exploring the possibilities of the incorporation of big data in the healthcare ...
The ITU-WHO Focus Group on Artificial Intelligence for Health (AI for Health) is an inter-agency collaboration between the World Health Organization and the ITU, which created a benchmarking framework to assess the accuracy of AI in health. [1][2] This organization convenes an international network of experts and stakeholders from fields like ...
Learning health systems. Learning health systems (LHS) are health and healthcare systems in which knowledge generation processes are embedded in daily practice to improve individual and population health. At its most fundamental level, a learning health system applies a conceptual approach wherein science, informatics, incentives, and culture ...
Health informatics. Medical informatics introduces information processing concepts and machinery to the domain of medicine. Health informatics is the study and implementation of computer structures and algorithms to improve communication, understanding, and management of medical information. [1] It can be viewed as a branch of engineering and ...
v. t. e. Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
List of datasets in computer vision and image processing. Outline of machine learning. v. t. e. These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning ...
LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. [4][5] It is based on decision tree algorithms and used for ranking, classification and other machine learning tasks. The development focus is on performance and scalability.
Flux (machine-learning framework) Flux is an open-source machine-learning software library and ecosystem written in Julia. [1][6] Its current stable release is v0.14.5 [4] . It has a layer-stacking-based interface for simpler models, and has a strong support on interoperability with other Julia packages instead of a monolithic design. [7]
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