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Artificial intelligence. Artificial intelligence in healthcare is the application of artificial intelligence (AI) to copy human cognition in the analysis, presentation, and understanding of complex medical and health care data. It can also augment and exceed human capabilities by providing faster or new ways to diagnose, treat, or prevent ...
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] Recently, artificial neural networks have been able to surpass many previous approaches in ...
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 ...
Biomedical data science. 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.
In healthcare, cost-sensitive machine learning plays a role in medical diagnostics. The approach allows for customization of models based on the potential harm associated with misdiagnoses, ensuring a more patient-centric application of machine learning algorithms.
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 ...
Health technology. Health technology is defined by the World Health Organization as the "application of organized knowledge and skills in the form of devices, medicines, vaccines, procedures, and systems developed to solve a health problem and improve quality of lives". [1] This includes pharmaceuticals, devices, procedures, and organizational ...
Some models built via machine learning algorithms have over 90% accuracy in distinguishing between spam and legitimate emails. [22] These models can be refined from new data and evolving spam tactics. Machine learning also analyzes traits such as sender behavior, email header information, and attachment types. [23]