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  2. Prognostics - Wikipedia

    en.wikipedia.org/wiki/Prognostics

    Data-driven prognostics usually use pattern recognition and machine learning techniques to detect changes in system states. [3] The classical data-driven methods for nonlinear system prediction include the use of stochastic models such as the autoregressive (AR) model, the threshold AR model, the bilinear model, the projection pursuit, the multivariate adaptive regression splines, and the ...

  3. Artificial intelligence in healthcare - Wikipedia

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

    Users report their symptoms into the app, which uses speech recognition to compare against a database of illnesses. Babylon then offers a recommended action, taking into account the user's medical history. Entrepreneurs in healthcare have been effectively using seven business model archetypes to take AI solution to the marketplace. These ...

  4. Prognosis - Wikipedia

    en.wikipedia.org/wiki/Prognosis

    Prognosis (Greek: πρόγνωσις "fore-knowing, foreseeing"; pl.: prognoses) is a medical term for predicting the likelihood or expected development of a disease, including whether the signs and symptoms will improve or worsen (and how quickly) or remain stable over time; expectations of quality of life, such as the ability to carry out daily activities; the potential for complications and ...

  5. Predictive medicine - Wikipedia

    en.wikipedia.org/wiki/Predictive_medicine

    The goal of predictive medicine is to predict the probability of future disease so that health care professionals and the patient themselves can be proactive in instituting lifestyle modifications and increased physician surveillance, such as bi-annual full body skin exams by a dermatologist or internist if their patient is found to have an increased risk of melanoma, an EKG and cardiology ...

  6. Predictive modelling - Wikipedia

    en.wikipedia.org/wiki/Predictive_modelling

    The first clinical prediction model reporting guidelines were published in 2015 (Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD)), and have since been updated. [10] Predictive modelling has been used to estimate surgery duration.

  7. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    The objective of these models is to assess the possibility that a unit in another sample will display the same pattern. Predictive model solutions can be considered a type of data mining technology. The models can analyze both historical and current data and generate a model in order to predict potential future outcomes. [14]

  8. Diagnosis (artificial intelligence) - Wikipedia

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

    Model-based diagnosis is an example of abductive reasoning using a model of the system. In general, it works as follows: Principle of the model-based diagnosis. We have a model that describes the behaviour of the system (or artefact). The model is an abstraction of the behaviour of the system and can be incomplete.

  9. Predictability - Wikipedia

    en.wikipedia.org/wiki/Predictability

    In the study of human–computer interaction, predictability is the property to forecast the consequences of a user action given the current state of the system. A contemporary example of human-computer interaction manifests in the development of computer vision algorithms for collision-avoidance software in self-driving cars.

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