User profiles for Melissa D. McCradden
 | Melissa McCraddenAustralian Institute for Machine learning Verified email at adelaide.edu.au Cited by 3163 |
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
A growing number of artificial intelligence (AI)-based clinical decision support systems are
showing promising performance in preclinical, in silico, evaluation, but few have yet …
showing promising performance in preclinical, in silico, evaluation, but few have yet …
What clinicians want: contextualizing explainable machine learning for clinical end use
…, S Joshi, MD McCradden… - Machine learning …, 2019 - proceedings.mlr.press
Translating machine learning (ML) models effectively to clinical practice requires establishing
clinicians’ trust. Explainability, or the ability of an ML model to justify its outcomes and …
clinicians’ trust. Explainability, or the ability of an ML model to justify its outcomes and …
Ethical limitations of algorithmic fairness solutions in health care machine learning
Artificial intelligence has exposed pernicious bias within health data that constitutes substantial
ethical threat to the use of machine learning in medicine. 1, 2 Solutions of algorithmic …
ethical threat to the use of machine learning in medicine. 1, 2 Solutions of algorithmic …
Ambiguous identities of drugs and people: a scoping review of opioid-related stigma
Background Human beings have long consumed opiates and opioids for pleasure and as a
treatment for numerous ailments, most notably pain. North America is currently in the grips of …
treatment for numerous ailments, most notably pain. North America is currently in the grips of …
A research ethics framework for the clinical translation of healthcare machine learning
MD McCradden, JA Anderson… - The American Journal …, 2022 - Taylor & Francis
The application of artificial intelligence and machine learning (ML) technologies in healthcare
have immense potential to improve the care of patients. While there are some emerging …
have immense potential to improve the care of patients. While there are some emerging …
The value of standards for health datasets in artificial intelligence-based applications
…, J Palmer, S Ganapathi, E Laws, MD McCradden… - Nature Medicine, 2023 - nature.com
Artificial intelligence as a medical device is increasingly being applied to healthcare for
diagnosis, risk stratification and resource allocation. However, a growing body of evidence has …
diagnosis, risk stratification and resource allocation. However, a growing body of evidence has …
TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning
MD McCradden, S Joshi, JA Anderson… - Journal of the …, 2020 - academic.oup.com
Accumulating evidence demonstrates the impact of bias that reflects social inequality on the
performance of machine learning (ML) models in health care. Given their intended …
performance of machine learning (ML) models in health care. Given their intended …
Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research
MD McCradden, T Sarker, PA Paprica - BMJ open, 2020 - bmjopen.bmj.com
Objectives Given widespread interest in applying artificial intelligence (AI) to health data to
improve patient care and health system efficiency, there is a need to understand the …
improve patient care and health system efficiency, there is a need to understand the …
Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a …
Background: As artificial intelligence (AI) approaches in research increase and AI becomes
more integrated into medicine, there is a need to understand perspectives from members of …
more integrated into medicine, there is a need to understand perspectives from members of …
