[HTML][HTML] Deploying digital health tools within large, complex health systems: key considerations for adoption and implementation
In recent years, the number of digital health tools with the potential to significantly improve
delivery of healthcare services has grown tremendously. However, the use of these tools in …
delivery of healthcare services has grown tremendously. However, the use of these tools in …
Leveraging physiology and artificial intelligence to deliver advancements in health care
Artificial intelligence in health care has experienced remarkable innovation and progress in
the last decade. Significant advancements can be attributed to the utilization of artificial …
the last decade. Significant advancements can be attributed to the utilization of artificial …
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 …
healthcare have immense potential to improve the care of patients. While there are some …
[HTML][HTML] APLUS: a Python library for usefulness simulations of machine learning models in healthcare
Despite the creation of thousands of machine learning (ML) models, the promise of
improving patient care with ML remains largely unrealized. Adoption into clinical practice is …
improving patient care with ML remains largely unrealized. Adoption into clinical practice is …
Artificial intelligence-enabled decision support in nephrology
Kidney pathophysiology is often complex, nonlinear and heterogeneous, which limits the
utility of hypothetical-deductive reasoning and linear, statistical approaches to diagnosis and …
utility of hypothetical-deductive reasoning and linear, statistical approaches to diagnosis and …
A framework for making predictive models useful in practice
Objective To analyze the impact of factors in healthcare delivery on the net benefit of
triggering an Advanced Care Planning (ACP) workflow based on predictions of 12-month …
triggering an Advanced Care Planning (ACP) workflow based on predictions of 12-month …
Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda
Purpose The proposed article is aimed at exploring the opportunities, challenges and
possible outcomes of incorporating big data analytics (BDA) into health-care sector. The …
possible outcomes of incorporating big data analytics (BDA) into health-care sector. The …
[HTML][HTML] Evaluation of domain generalization and adaptation on improving model robustness to temporal dataset shift in clinical medicine
Temporal dataset shift associated with changes in healthcare over time is a barrier to
deploying machine learning-based clinical decision support systems. Algorithms that learn …
deploying machine learning-based clinical decision support systems. Algorithms that learn …
Learning optimal predictive checklists
Checklists are simple decision aids that are often used to promote safety and reliability in
clinical applications. In this paper, we present a method to learn checklists for clinical …
clinical applications. In this paper, we present a method to learn checklists for clinical …
[HTML][HTML] Clinical deployment environments: Five pillars of translational machine learning for health
S Harris, T Bonnici, T Keen, W Lilaonitkul… - Frontiers in Digital …, 2022 - frontiersin.org
Machine Learning for Health (ML4H) has demonstrated efficacy in computer imaging and
other self-contained digital workflows, but has failed to substantially impact routine clinical …
other self-contained digital workflows, but has failed to substantially impact routine clinical …