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  2. Artificial intelligence in healthcare - Wikipedia

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

    Through the use of machine learning, artificial intelligence can be able to substantially aid doctors in patient diagnosis through the analysis of mass electronic health records (EHRs). [22] AI can help early prediction, for example, of Alzheimer's disease and dementias, by looking through large numbers of similar cases and possible treatments ...

  3. Hallucination (artificial intelligence) - Wikipedia

    en.wikipedia.org/wiki/Hallucination_(artificial...

    The images above demonstrate an example of how an artificial neural network might make a false positive result in object detection. The input image is a simplified example of the training phase, using multiple images that are known to depict starfish and sea urchins, respectively. The starfish match with a ringed texture and a star outline ...

  4. Artificial empathy - Wikipedia

    en.wikipedia.org/wiki/Artificial_empathy

    Examples of artificial empathy research and practice [ edit ] People often communicate and make decisions based on inferences about each other's internal states (e.g., emotional, cognitive, and physical states) that are in turn based on signals emitted by the person such as facial expression, body gesture, voice, and words.

  5. Ethics of artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Ethics_of_artificial...

    The problem of bias in machine learning is likely to become more significant as the technology spreads to critical areas like medicine and law, and as more people without a deep technical understanding are tasked with deploying it. [36] Some open-sourced tools are looking to bring more awareness to AI biases. [37]

  6. Fairness (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Fairness_(machine_learning)

    Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).

  7. Quackery - Wikipedia

    en.wikipedia.org/wiki/Quackery

    Quackery, often synonymous with health fraud, is the promotion [1] of fraudulent or ignorant medical practices. A quack is a "fraudulent or ignorant pretender to medical skill" or "a person who pretends, professionally or publicly, to have skill, knowledge, qualification or credentials they do not possess; a charlatan or snake oil salesman". [ 2 ]

  8. List of topics characterized as pseudoscience - Wikipedia

    en.wikipedia.org/wiki/List_of_topics...

    Detailed discussion of these topics may be found on their main pages. These characterizations were made in the context of educating the public about questionable or potentially fraudulent or dangerous claims and practices, efforts to define the nature of science, or humorous parodies of poor scientific reasoning.

  9. Cognitive bias mitigation - Wikipedia

    en.wikipedia.org/wiki/Cognitive_bias_mitigation

    Machine learning, a branch of artificial intelligence, has been used to investigate human learning and decision making. [ 67 ] One technique particularly applicable to cognitive bias mitigation is neural network learning and choice selection , an approach inspired by the imagined structure and function of actual biological neural networks in ...