Artificial intelligence in healthcare

KH Yu, AL Beam, IS Kohane - Nature biomedical engineering, 2018 - nature.com
Artificial intelligence (AI) is gradually changing medical practice. With recent progress in
digitized data acquisition, machine learning and computing infrastructure, AI applications …

[HTML][HTML] A systematic review of the prediction of hospital length of stay: Towards a unified framework

K Stone, R Zwiggelaar, P Jones… - PLOS Digital …, 2022 - journals.plos.org
Hospital length of stay of patients is a crucial factor for the effective planning and
management of hospital resources. There is considerable interest in predicting the LoS of …

Clinicalbert: Modeling clinical notes and predicting hospital readmission

K Huang, J Altosaar, R Ranganath - ar** clinically relevant applications for online CBT treatment
A Thieme, M Hanratty, M Lyons, J Palacios… - ACM Transactions on …, 2023 - dl.acm.org
Recent advances in AI and machine learning (ML) promise significant transformations in the
future delivery of healthcare. Despite a surge in research and development, few works have …

Predictive models for hospital readmission risk: A systematic review of methods

A Artetxe, A Beristain, M Grana - Computer methods and programs in …, 2018 - Elsevier
Objectives Hospital readmission risk prediction facilitates the identification of patients
potentially at high risk so that resources can be used more efficiently in terms of cost-benefit …

Artificial intelligence: the milestone in modern biomedical research

K Athanasopoulou, GN Daneva, PG Adamopoulos… - …, 2022 - mdpi.com
In recent years, the advent of new experimental methodologies for studying the high
complexity of the human genome and proteome has led to the generation of an increasing …

[HTML][HTML] Clinical data reuse or secondary use: current status and potential future progress

SM Meystre, C Lovis, T Bürkle… - Yearbook of medical …, 2017 - thieme-connect.com
Objective: To perform a review of recent research in clinical data reuse or secondary use,
and envision future advances in this field. Methods: The review is based on a large literature …

Application of Bayesian networks to generate synthetic health data

D Kaur, M Sobiesk, S Patil, J Liu… - Journal of the …, 2021 - academic.oup.com
Objective This study seeks to develop a fully automated method of generating synthetic data
from a real dataset that could be employed by medical organizations to distribute health data …

Clinician involvement in research on machine learning–based predictive clinical decision support for the hospital setting: A sco** review

JM Schwartz, AJ Moy, SC Rossetti… - Journal of the …, 2021 - academic.oup.com
Objective The study sought to describe the prevalence and nature of clinical expert
involvement in the development, evaluation, and implementation of clinical decision support …