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  2. List of neuroscience databases - Wikipedia

    en.wikipedia.org/wiki/List_of_neuroscience_databases

    A number of online neuroscience databases are available which provide information regarding gene expression, neurons, macroscopic brain structure, and neurological or psychiatric disorders. Some databases contain descriptive and numerical data, some to brain function, others offer access to 'raw' imaging data, such as postmortem brain sections ...

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

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

    Lung Cancer Dataset Lung cancer dataset without attribute definitions 56 features are given for each case 32 Text Classification 1992 [270] [271] Z. Hong et al. Arrhythmia Dataset Data for a group of patients, of which some have cardiac arrhythmia. 276 features for each instance. 452 Text Classification 1998 [272] [273] H. Altay et al.

  4. Kaggle - Wikipedia

    en.wikipedia.org/wiki/Kaggle

    Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.

  5. The Cancer Imaging Archive - Wikipedia

    en.wikipedia.org/wiki/The_Cancer_Imaging_Archive

    The Cancer Imaging Archive (TCIA) is an open-access database of medical images for cancer research. The site is funded by the National Cancer Institute's (NCI) Cancer Imaging Program, and the contract is operated by the University of Arkansas for Medical Sciences. Data within the archive is organized into collections which typically share a ...

  6. 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]

  7. Brain connectivity estimators - Wikipedia

    en.wikipedia.org/wiki/Brain_connectivity_estimators

    The estimation of brain connectivity has found numerous and notable applications, namely when investigating brain changes associated with the treatment of psychopathology like schizophrenia [31] and depression, [32] or following structural damage like in hemorrhage [33] or tumor.

  8. Bayesian approaches to brain function - Wikipedia

    en.wikipedia.org/wiki/Bayesian_approaches_to...

    A synthesis has been attempted recently [29] by Karl Friston, in which the Bayesian brain emerges from a general principle of free energy minimisation. [30] In this framework, both action and perception are seen as a consequence of suppressing free-energy, leading to perceptual [ 31 ] and active inference [ 32 ] and a more embodied (enactive ...

  9. List of artificial intelligence projects - Wikipedia

    en.wikipedia.org/wiki/List_of_artificial...

    Blue Brain Project, an attempt to create a synthetic brain by reverse-engineering the mammalian brain down to the molecular level. [1] Google Brain, a deep learning project part of Google X attempting to have intelligence similar or equal to human-level. [2] Human Brain Project, ten-year scientific research project, based on exascale ...