The secondary use of electronic health records for data mining: Data characteristics and challenges
The primary objective of implementing Electronic Health Records (EHRs) is to improve the
management of patients' health-related information. However, these records have also been …
management of patients' health-related information. However, these records have also been …
Machine learning solutions for osteoporosis—a review
J Smets, E Shevroja, T Hügle… - Journal of bone and …, 2020 - academic.oup.com
Osteoporosis and its clinical consequence, bone fracture, is a multifactorial disease that has
been the object of extensive research. Recent advances in machine learning (ML) have …
been the object of extensive research. Recent advances in machine learning (ML) have …
The National COVID Cohort Collaborative (N3C): rationale, design, infrastructure, and deployment
Abstract Objective Coronavirus disease 2019 (COVID-19) poses societal challenges that
require expeditious data and knowledge sharing. Though organizational clinical data are …
require expeditious data and knowledge sharing. Though organizational clinical data are …
A review on utilizing machine learning technology in the fields of electronic emergency triage and patient priority systems in telemedicine: Coherent taxonomy …
Background With the remarkable increasing in the numbers of patients, the triaging and
prioritizing patients into multi-emergency level is required to accommodate all the patients …
prioritizing patients into multi-emergency level is required to accommodate all the patients …
Applications of machine learning in routine laboratory medicine: Current state and future directions
Abstract Machine learning is able to leverage large amounts of data to infer complex
patterns that are otherwise beyond the capabilities of rule-based systems and human …
patterns that are otherwise beyond the capabilities of rule-based systems and human …
Inferring multimodal latent topics from electronic health records
Electronic health records (EHR) are rich heterogeneous collections of patient health
information, whose broad adoption provides clinicians and researchers unprecedented …
information, whose broad adoption provides clinicians and researchers unprecedented …
[HTML][HTML] Understanding the role and adoption of artificial intelligence techniques in rheumatology research: an in-depth review of the literature
A Madrid-García, B Merino-Barbancho… - Seminars in Arthritis and …, 2023 - Elsevier
The major and upward trend in the number of published research related to rheumatic and
musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the …
musculoskeletal diseases, in which artificial intelligence plays a key role, has exhibited the …
Systematic review of functional MRI applications for psychiatric disease subtyping
L Miranda, R Paul, B Pütz, N Koutsouleris… - Frontiers in …, 2021 - frontiersin.org
Background: Psychiatric disorders have been historically classified using symptom
information alone. Recently, there has been a dramatic increase in research interest not only …
information alone. Recently, there has been a dramatic increase in research interest not only …
Machine learning approaches for electronic health records phenotyping: a methodical review
S Yang, P Varghese, E Stephenson… - Journal of the …, 2023 - academic.oup.com
Objective Accurate and rapid phenotyping is a prerequisite to leveraging electronic health
records for biomedical research. While early phenotyping relied on rule-based algorithms …
records for biomedical research. While early phenotyping relied on rule-based algorithms …
Artificial intelligence in clinical and translational science: Successes, challenges and opportunities
EV Bernstam, PK Shireman… - Clinical and …, 2022 - Wiley Online Library
Artificial intelligence (AI) is transforming many domains, including finance, agriculture,
defense, and biomedicine. In this paper, we focus on the role of AI in clinical and …
defense, and biomedicine. In this paper, we focus on the role of AI in clinical and …