[HTML][HTML] Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension

SC Rivera, X Liu, AW Chan, AK Denniston… - The Lancet Digital …, 2020 - thelancet.com
The SPIRIT 2013 statement aims to improve the completeness of clinical trial protocol
reporting by providing evidence-based recommendations for the minimum set of items to be …

Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension

X Liu, SC Rivera, D Moher, MJ Calvert… - The Lancet Digital …, 2020 - thelancet.com
The CONSORT 2010 statement provides minimum guidelines for reporting randomised
trials. Its widespread use has been instrumental in ensuring transparency in the evaluation …

Artificial intelligence and machine learning for improving glycemic control in diabetes: Best practices, pitfalls, and opportunities

PG Jacobs, P Herrero, A Facchinetti… - IEEE reviews in …, 2023 - ieeexplore.ieee.org
Objective: Artificial intelligence and machine learning are transforming many fields including
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …

The personal health applications of machine learning techniques in the internet of behaviors

Z Amiri, A Heidari, M Darbandi, Y Yazdani… - Sustainability, 2023 - mdpi.com
With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the
medical and healthcare fields are utilizing machine learning (ML) methodologies in …

Wearable chemical sensors for biomarker discovery in the omics era

JR Sempionatto, JA Lasalde-Ramírez… - Nature Reviews …, 2022 - nature.com
Biomarkers are crucial biological indicators in medical diagnostics and therapy. However,
the process of biomarker discovery and validation is hindered by a lack of standardized …

Diagnosis and treatment of type 1 diabetes at the dawn of the personalized medicine era

AAS Akil, E Yassin, A Al-Maraghi, E Aliyev… - Journal of translational …, 2021 - Springer
Type 1 diabetes affects millions of people globally and requires careful management to
avoid serious long-term complications, including heart and kidney disease, stroke, and loss …

Concordance of randomised controlled trials for artificial intelligence interventions with the CONSORT-AI reporting guidelines

APL Martindale, CD Llewellyn, RO De Visser… - Nature …, 2024 - nature.com
Abstract The Consolidated Standards of Reporting Trials extension for Artificial Intelligence
interventions (CONSORT-AI) was published in September 2020. Since its publication …

Artificial intelligence for diabetes care: current and future prospects

B Sheng, K Pushpanathan, Z Guan, QH Lim… - The Lancet Diabetes & …, 2024 - thelancet.com
Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise
care for people with diabetes and adapt treatments for complex presentations. However, the …

Recent applications of machine learning and deep learning models in the prediction, diagnosis, and management of diabetes: a comprehensive review

E Afsaneh, A Sharifdini, H Ghazzaghi… - Diabetology & Metabolic …, 2022 - Springer
Diabetes as a metabolic illness can be characterized by increased amounts of blood
glucose. This abnormal increase can lead to critical detriment to the other organs such as …

[HTML][HTML] A systematic approach to enhance the explainability of artificial intelligence in healthcare with application to diagnosis of diabetes

YC Wang, TCT Chen, MC Chiu - Healthcare Analytics, 2023 - Elsevier
Explainable artificial intelligence (XAI) tools are used to enhance the applications of existing
artificial intelligence (AI) technologies by explaining their execution processes and results. In …