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  2. Machine learning in bioinformatics - Wikipedia

    en.wikipedia.org/wiki/Machine_learning_in...

    [2] [59] Machine learning can be used for this knowledge extraction task using techniques such as natural language processing to extract the useful information from human-generated reports in a database. Text Nailing, an alternative approach to machine learning, capable of extracting features from clinical narrative notes was introduced in 2017.

  3. Biomedical data science - Wikipedia

    en.wikipedia.org/wiki/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.

  4. Computational biology - Wikipedia

    en.wikipedia.org/wiki/Computational_biology

    In biology supervised learning can be helpful when we have data that we know how to categorize and we would like to categorize more data into those categories. Diagram showing a simple random forest. A common supervised learning algorithm is the random forest, which uses numerous decision trees to train a model to classify a dataset. Forming ...

  5. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...

  6. Bioinformatics - Wikipedia

    en.wikipedia.org/wiki/Bioinformatics

    The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches is its focus on developing and applying computationally intensive techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning algorithms, and visualization.

  7. Journal of Machine Learning Research - Wikipedia

    en.wikipedia.org/wiki/Journal_of_Machine...

    The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the first editor-in-chief was Leslie Kaelbling. [1] The current editors-in-chief are Francis Bach and David Blei (Columbia University).

  8. List of Nature Research journals - Wikipedia

    en.wikipedia.org/wiki/List_of_Nature_Research...

    npj series. The Nature Partner Journals series, abbreviated npj, is a series of online-only, open access, journals.It was launched in April 2014 with three journals: npj Primary Care Respiratory Medicine, npj Biofilms and Microbiomes, and npj Schizophrenia.

  9. Active learning (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Active_learning_(machine...

    Active learning is a special case of machine learning in which a learning algorithm can interactively query a human user (or some other information source), to label new data points with the desired outputs. The human user must possess knowledge/expertise in the problem domain, including the ability to consult/research authoritative sources ...