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Q The authors of the assigned article, "A Patient-Driven Adaptive Prediction Technique to Improve Personalized Risk Estimation for Clinical Decision Support (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392846/) have found that using patient-driven, adaptive technologies to guide clinical decision making are influencing the quality of patient care. How might these technologies minimize risk, promote health, and encourage patient engagement in their own care?

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In the healthcare industry, quality, accuracy, and timeliness, are the most vital requirements that ensure that both the providers and the receivers of healthcare are benefitted. Recently, there has been an increase in implementing patient-driven technologies towards the decision making process regarding what is necessary and beneficial for the patient and better health. In patient care technology plays an immense role when considering what ways can computerized resources aid humans and make the caring process more compatible and efficient. Predictive models have been used in medical practices for uses like (Jiang, Boxwala, El-Kareh, Kim, and Ohno-Machado, 2012):