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Reinventing Clinical Decision Support - Data Analytics, Artificial Intelligence, and Diagnostic Reasoning (Paperback)
Loot Price: R1,458
Discovery Miles 14 580
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Reinventing Clinical Decision Support - Data Analytics, Artificial Intelligence, and Diagnostic Reasoning (Paperback)
Series: HIMSS Book Series
Expected to ship within 12 - 19 working days
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This book takes an in-depth look at the emerging technologies that
are transforming the way clinicians manage patients, while at the
same time emphasizing that the best practitioners use both
artificial and human intelligence to make decisions. AI and machine
learning are explored at length, with plain clinical English
explanations of convolutional neural networks, back propagation,
and digital image analysis. Real-world examples of how these tools
are being employed are also discussed, including their value in
diagnosing diabetic retinopathy, melanoma, breast cancer, cancer
metastasis, and colorectal cancer, as well as in managing severe
sepsis. With all the enthusiasm about AI and machine learning, it
was also necessary to outline some of criticisms, obstacles, and
limitations of these new tools. Among the criticisms discussed: the
relative lack of hard scientific evidence supporting some of the
latest algorithms and the so-called black box problem. A chapter on
data analytics takes a deep dive into new ways to conduct subgroup
analysis and how it's forcing healthcare executives to rethink the
way they apply the results of large clinical trials to everyday
medical practice. This re-evaluation is slowly affecting the way
diabetes, heart disease, hypertension, and cancer are treated. The
research discussed also suggests that data analytics will impact
emergency medicine, medication management, and healthcare costs. An
examination of the diagnostic reasoning process itself looks at how
diagnostic errors are measured, what technological and cognitive
errors are to blame, and what solutions are most likely to improve
the process. It explores Type 1 and Type 2 reasoning methods;
cognitive mistakes like availability bias, affective bias, and
anchoring; and potential solutions such as the Human Diagnosis
Project. Finally, the book explores the role of systems biology and
precision medicine in clinical decision support and provides
several case studies of how next generation AI is transforming
patient care.
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