Titlebook: Online Machine Learning; A Practical Guide wi Eva Bartz,Thomas Bartz-Beielstein Book 2024 The Editor(s) (if applicable) and The Author(s),

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Thomas Bartz-Beielstein,Lukas Hansprofessionals. Conservative estimates indicate one in four patients will suffer from a medical error or inappropriate care. Unfortunately, healthcare organizations too often respond to these harm events with a delay, deny, and defend approach that involves erecting a “wall of silence.” This wall of

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Thomas Bartz-Beielsteinhealthcare workers must be taught that violence is never to be considered “part of the job,” and it is everyone’s responsibility to provide for the safety for healthcare workers and patients. Behavior is a form of communication, and it is critical that healthcare workers collaborate to find out what

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2730-9908 volved with it now. This book already presents some tools that will facilitate the practice of OML in the future. A promising breakthrough is expected because practice shows that due to the large amounts of dat978-981-99-7009-4978-981-99-7007-0Series ISSN 2730-9908 Series E-ISSN 2730-9916

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Thomas Bartz-Beielstein,Lukas Hanstions that reliably approach harm events in healthcare with a holistic, empathic, and honest approach experience improvements in patient safety learning, patient experience, healthcare professional wellness, reductions in serious safety events, and mitigation of risk. To succeed, leaders and their o

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Thomas Bartz-Beielsteinhallenges that healthcare workers face, and concerns raised by healthcare workers must be taken seriously. Providing care to communities who are increasingly traumatized by structural inequities, increasing incidence of substance dependence, and untreated mental illness requires patient specific edu

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,Practical Applications of Online Machine Learning,tions or show promising potential for OML usage (Sect. .). The second surveyed application field is the process of hot rolling in the steel industry (Sect. .). In general, the process quality of hot rolling (Sect. .) benefits from ML predictions (Sect. .). However, because of being susceptible to dr

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Book 2024 OML might outweigh the costs...OML will soon become practical; it is worthwhile to get involved with it now. This book already presents some tools that will facilitate the practice of OML in the future. A promising breakthrough is expected because practice shows that due to the large amounts of dat

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