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  2. Artificial intelligence in healthcare - Wikipedia

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

    Medical imaging (such as X-ray and photography) is a commonly used tool in dermatology [54] and the development of deep learning has been strongly tied to image processing. Therefore, there is a natural fit between the dermatology and deep learning. Machine learning learning holds great potential to process these images for better diagnoses. [55]

  3. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

  4. Machine learning in bioinformatics - Wikipedia

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

    Deep learning applications have been used for regulatory genomics and cellular imaging. [33] Other applications include medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. [34] Deep learning has been applied to regulatory genomics, variant calling and pathogenicity scores. [35]

  5. Explainable artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Explainable_artificial...

    The use of explainable artificial intelligence (XAI) in pain research, specifically in understanding the role of electrodermal activity for automated pain recognition: hand-crafted features and deep learning models in pain recognition, highlighting the insights that simple hand-crafted features can yield comparative performances to deep ...

  6. Applications of artificial intelligence - Wikipedia

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

    GNoME employs deep learning techniques to efficiently explore potential material structures, achieving a significant increase in the identification of stable inorganic crystal structures. The system's predictions were validated through autonomous robotic experiments, demonstrating a noteworthy success rate of 71%.

  7. Learning health systems - Wikipedia

    en.wikipedia.org/wiki/Learning_health_systems

    Some refer to a learning healthcare system, others refer to learning health systems or collaborative learning health systems. [11] The architecture and objectives are similar, irrespective of the label—addressing evidence gaps, harnessing data, and effectively utilizing the best evidence at the point of need.

  8. Friendly artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Friendly_artificial...

    Writing in The Guardian, Alan Winfield compares human-level artificial intelligence with faster-than-light travel in terms of difficulty and states that while we need to be "cautious and prepared" given the stakes involved, we "don't need to be obsessing" about the risks of superintelligence. [21]

  9. Health informatics - Wikipedia

    en.wikipedia.org/wiki/Health_informatics

    In the healthcare industry, health informatics has provided such technological solutions as telemedicine, surgical robots, electronic health records (EHR), Picture Archiving and Communication Systems (PACS), and decision support, artificial intelligence, and machine learning innovations including IBM's Watson and Google's DeepMind platform.