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  2. Artificial intelligence in healthcare - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence_in...

    Through machine learning algorithms and deep learning, AI can analyse large sets of clinical data and electronic health records and can help to diagnose the disease more quickly and precisely. [3] In addition, AI is becoming more relevant in bringing culturally competent healthcare practices to the industry. [4]

  3. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is an interdisciplinary field [ 10 ] focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, developing data ...

  4. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  5. Health informatics - Wikipedia

    en.wikipedia.org/wiki/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 applied science.

  6. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    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]

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. [1]

  8. Applications of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Applications_of_artificial...

    AI is a mainstay of law-related professions. Algorithms and machine learning do some tasks previously done by entry-level lawyers. [235] While its use is common, it is not expected to replace most work done by lawyers in the near future. [236] The electronic discovery industry uses machine learning to reduce manual searching. [237]

  9. Bioinformatics - Wikipedia

    en.wikipedia.org/wiki/Bioinformatics

    Early bioinformatics—computational alignment of experimentally determined sequences of a class of related proteins; see § Sequence analysis for further information. Bioinformatics (/ ˌbaɪ.oʊˌɪnfərˈmætɪks / ⓘ) is an interdisciplinary field of science that develops methods and software tools for understanding biological data ...