Using AI as an assistive tool has the potential to improve accuracy and
reduce diagnostic errors, within an increasingly stretched Health Service.
Not exact matches
In an effort to
reduce patient misdiagnoses and associated poor patient outcomes from lack of prompt treatment, a Johns Hopkins Armstrong Institute for Patient Safety and Quality researcher is helping to lead the way in providing hospitals a new approach to quantify and monitor
diagnostic errors in their quality improvement efforts.
Self -
diagnostics and visual and audible signals enable school caterers to respond quickly to any
errors,
reducing downtime.
The study provides California medical malpractice lawyers firm evidence of the need for greater focus on preventing
diagnostic errors to
reduce medical
errors.