Studies in health technology and informatics
29295063
The rise of health consumers and the accumulation of patient-generated health data (PGHD) have brought the patient to the centerstage of precision health and behavioral science. In this positional paper we outline an interpretability-aware framework ...
OBJECTIVE: To estimate costs attributable to robot-assisted laparoscopic prostatectomy (RALP) as compared with open prostatectomy (OP) and laparoscopic prostatectomies (LP) in a National Health Service perspective.
Journal of evaluation in clinical practice
29230910
RATIONALE, AIMS AND OBJECTIVES: A common approach to assessing treatment effects in nonrandomized studies with time-to-event outcomes is to estimate propensity scores and compute weights using logistic regression, test for covariate balance, and then...
OBJECTIVES: Current models for patient risk prediction rely on practitioner expertise and domain knowledge. This study presents a deep learning model-a type of machine learning that does not require human inputs-to analyze complex clinical and financ...
OBJECTIVE: We aim to characterise persistent high utilisers (PHUs) of healthcare services, and correspondingly, transient high utilisers (THUs) and non-high utilisers (non-HUs) for comparison, to facilitate stratifying HUs for targeted intervention. ...
International journal of medical informatics
32416430
OBJECTIVES: Various healthcare stakeholders define quality of care in different ways. Public policy could advocate all these concerns. This study was conducted to identify the main themes on patient safety of stakeholders expressed before and after t...
Psychotherapy research : journal of the Society for Psychotherapy Research
32602811
Decision-tree methods are machine-learning methods which provide results that are relatively easy to interpret and apply by human decision makers. The resulting decision trees show how baseline patient characteristics can be combined to predict trea...