Trustworthy AI guidelines in biomedical decision-making applications: a sco** review

M Mora-Cantallops, E García-Barriocanal… - Big Data and Cognitive …, 2024‏ - mdpi.com
Recently proposed legal frameworks for Artificial Intelligence (AI) depart from some
frameworks of concepts regarding ethical and trustworthy AI that provide the technical …

[HTML][HTML] Evaluating impact of movement on diabetes via artificial intelligence and smart devices systematic literature review

S Rotbei, WH Tseng, B Merino-Barbancho… - Expert Systems with …, 2024‏ - Elsevier
As diabetes management becomes more complicated, there is an increasing interest in
understanding how to manage diabetes with physical activity. Our study aimed to investigate …

(Hybrid) Closed-Loop Systems: From Announced to Unannounced Exercise

RT Zimmer, A Auth, J Schierbauer, S Haupt… - Diabetes Technology …, 2023‏ - liebertpub.com
Physical activity and exercise have many beneficial effects on general and type 1 diabetes
(T1D) specific health and are recommended for individuals with T1D. Despite these health …

What is meant by 'integrated personalized diabetes management': A view into the future and what success should look like

N Guldemond - Diabetes, Obesity and Metabolism, 2024‏ - Wiley Online Library
Integrated personalized diabetes management (IPDM) has emerged as a promising
approach to improving outcomes in patients with diabetes mellitus (DM). This care approach …

Leveraging Machine Learning for Disease Diagnoses based on Wearable Devices: A Survey

Z Jiang, V Van Zoest, W Deng… - IEEE Internet of Things …, 2023‏ - ieeexplore.ieee.org
Many countries around the world are facing a shortage of healthcare resources, especially
during the post-epidemic era, leading to a dramatic increase in the need for self-detection …

A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes

R Tao, X Yu, J Lu, Y Wang, W Lu, Z Zhang, H Li… - … Engineering Sciences in …, 2023‏ - Springer
Continuous glucose monitoring (CGM) data analysis will provide a new perspective to
analyze factors related to diabetic retinopathy (DR). However, the problem of visualizing …

When fairness meets privacy: Fair classification with semi-private sensitive attributes

C Chen, Y Liang, X Xu, S **e, A Kundu… - arxiv preprint arxiv …, 2022‏ - arxiv.org
Machine learning models have demonstrated promising performance in many areas.
However, the concerns that they can be biased against specific demographic groups hinder …

[HTML][HTML] A proposal of a mixed diagnostic system based on decision trees and probabilistic experts rules

G Aguilera-Venegas, E Roanes-Lozano… - … of Computational and …, 2023‏ - Elsevier
Decision trees and rule-based expert systems (RBES) are standard diagnostic tools. We
propose a mixed technique that starts with a probabilistic decision tree where information is …

Impact of machine learning on dietary and exercise behaviors in type 2 diabetes self-management: a systematic literature review

RR Mir, NU Haq, K Ishaq, N Safie, AB Dogar - PeerJ Computer Science, 2025‏ - peerj.com
Self-awareness and self-management in diabetes are critical as they enhance patient well-
being, decrease financial burden, and alleviate strain on healthcare systems by mitigating …

Prebiotics Beyond the Gut: Omics Insights, Artificial Intelligence, and Clinical Trials in Organ-Specific Applications

ISI Al‐Adham, ASA Agha, F Al‑Akayleh… - Probiotics and …, 2025‏ - Springer
Prebiotics, traditionally linked to gut health, are increasingly recognized for their systemic
benefits, influencing multiple organ systems through interactions with the gut microbiota …