|
Showing 1 - 1 of
1 matches in All Departments
The medical domain is home to many critical challenges that stand
to be overcome with the use of data-driven clinical decision
support systems (CDSS), and there is a growing set of examples of
automated diagnosis, prognosis, drug design, and testing. However,
the current state of AI in medicine has been summarized as "high on
promise and relatively low on data and proof." If such problems can
be addressed, a data-driven approach will be very important to the
future of CDSSs as it simplifies the knowledge acquisition and
maintenance process, a process that is time-consuming and requires
considerable human effort. Diverse Perspectives and
State-of-the-Art Approaches to the Utilization of Data-Driven
Clinical Decision Support Systems critically reflects on the
challenges that data-driven CDSSs must address to become mainstream
healthcare systems rather than a small set of exemplars of what
might be possible. It further identifies evidence-based, successful
data-driven CDSSs. Covering topics such as automated planning,
diagnostic systems, and explainable artificial intelligence, this
premier reference source is an excellent resource for medical
professionals, healthcare administrators, IT managers, pharmacists,
students and faculty of higher education, librarians, researchers,
and academicians.
|
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.