[HTML][HTML] A systematic literature review on obesity: Understanding the causes & consequences of obesity and reviewing various machine learning approaches used to …

M Safaei, EA Sundararajan, M Driss, W Boulila… - Computers in biology …, 2021 - Elsevier
Obesity is considered a principal public health concern and ranked as the fifth foremost
reason for death globally. Overweight and obesity are one of the main lifestyle illnesses that …

[HTML][HTML] Clinical information extraction applications: a literature review

Y Wang, L Wang, M Rastegar-Mojarad, S Moon… - Journal of biomedical …, 2018 - Elsevier
Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …

[HTML][HTML] Clinical text data in machine learning: systematic review

I Spasic, G Nenadic - JMIR medical informatics, 2020 - medinform.jmir.org
Background: Clinical narratives represent the main form of communication within health
care, providing a personalized account of patient history and assessments, and offering rich …

Advances in electronic phenotyping: from rule-based definitions to machine learning models

JM Banda, M Seneviratne… - Annual review of …, 2018 - annualreviews.org
With the widespread adoption of electronic health records (EHRs), large repositories of
structured and unstructured patient data are becoming available to conduct observational …

Machine learning models to predict childhood and adolescent obesity: a review

G Colmenarejo - Nutrients, 2020 - mdpi.com
The prevalence of childhood and adolescence overweight an obesity is raising at an
alarming rate in many countries. This poses a serious threat to the current and near-future …

[HTML][HTML] Applications of artificial intelligence to obesity research: scoping review of methodologies

R An, J Shen, Y Xiao - Journal of Medical Internet Research, 2022 - jmir.org
Background Obesity is a leading cause of preventable death worldwide. Artificial
intelligence (AI), characterized by machine learning (ML) and deep learning (DL), has …

Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies

MG Kersloot, FJP van Putten, A Abu-Hanna… - Journal of biomedical …, 2020 - Springer
Background Free-text descriptions in electronic health records (EHRs) can be of interest for
clinical research and care optimization. However, free text cannot be readily interpreted by a …

A systematic literature review on outlier detection in wireless sensor networks

M Safaei, S Asadi, M Driss, W Boulila, A Alsaeedi… - Symmetry, 2020 - mdpi.com
A wireless sensor network (WSN) is defined as a set of spatially distributed and
interconnected sensor nodes. WSNs allow one to monitor and recognize environmental …

Obesity Prediction with EHR Data: A deep learning approach with interpretable elements

M Gupta, TLT Phan, HT Bunnell… - ACM Transactions on …, 2022 - dl.acm.org
Childhood obesity is a major public health challenge. Early prediction and identification of
the children at an elevated risk of developing childhood obesity may help in engaging …

[HTML][HTML] Trends and opportunities in computable clinical phenotyping: A scoping review

T He, A Belouali, J Patricoski, H Lehmann… - Journal of Biomedical …, 2023 - Elsevier
Identifying patient cohorts meeting the criteria of specific phenotypes is essential in
biomedicine and particularly timely in precision medicine. Many research groups deliver …