Advancing AI in healthcare: a comprehensive review of best practices

S Polevikov - Clinica Chimica Acta, 2023‏ - Elsevier
Abstract Artificial Intelligence (AI) and Machine Learning (ML) are powerful tools sha** the
healthcare sector. This review considers twelve key aspects of AI in clinical practice: 1) …

Ensuring that biomedical AI benefits diverse populations

J Zou, L Schiebinger - EBioMedicine, 2021‏ - thelancet.com
Artificial Intelligence (AI) can potentially impact many aspects of human health, from basic
research discovery to individual health assessment. It is critical that these advances in …

Performance of intensive care unit severity scoring systems across different ethnicities in the USA: a retrospective observational study

R Sarkar, C Martin, H Mattie, JW Gichoya… - The Lancet Digital …, 2021‏ - thelancet.com
Background Despite wide use of severity scoring systems for case-mix determination and
benchmarking in the intensive care unit (ICU), the possibility of scoring bias across …

Explainable machine learning on AmsterdamUMCdb for ICU discharge decision support: uniting intensivists and data scientists

PJ Thoral, M Fornasa, DP de Bruin… - Critical care …, 2021‏ - journals.lww.com
Objectives: Unexpected ICU readmission is associated with longer length of stay and
increased mortality. To prevent ICU readmission and death after ICU discharge, our team of …

Artificial intelligence and big data in sustainable entrepreneurship

SJ Bickley, A Macintyre, B Torgler - Journal of Economic …, 2025‏ - Wiley Online Library
There is an urgent need to transition our economy, society, and culture towards systems and
actions that facilitate ecological sustainability. Such radical change requires equally radical …

[HTML][HTML] Develo** ethics and equity principles, terms, and engagement tools to advance health equity and researcher diversity in AI and machine learning: modified …

R Hendricks-Sturrup, M Simmons, S Anders, K Aneni… - JMIR AI, 2023‏ - ai.jmir.org
Background: Artificial intelligence (AI) and machine learning (ML) technology design and
development continues to be rapid, despite major limitations in its current form as a practice …

Authentic integration of ethics and AI through sociotechnical, problem-based learning

A Krakowski, E Greenwald, T Hurt… - Proceedings of the …, 2022‏ - ojs.aaai.org
Growing awareness of both the demand for artificial intelligence (AI) expertise and of the
societal impacts of AI systems has led to calls to integrate learning of ethics alongside …

Rebooting consent in the digital age: a governance framework for health data exchange

N Saksena, R Matthan, A Bhan, S Balsari - BMJ Global Health, 2021‏ - gh.bmj.com
In August 2020, India announced its vision for the National Digital Health Mission (NDHM), a
federated national digital health exchange where digitised data generated by healthcare …

Risks and benefits of dermatological machine learning health care applications—an overview and ethical analysis

T Willem, S Krammer, AS Böhm… - Journal of the …, 2022‏ - Wiley Online Library
Background Visual data are particularly amenable for machine learning techniques. With
clinical photography established for skin surveillance and documentation purposes as well …

Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research

T Willem, MC Fritzsche, BM Zimmermann… - … and Engineering Ethics, 2025‏ - Springer
Integrating artificial intelligence (AI) into critical domains such as healthcare holds immense
promise. Nevertheless, significant challenges must be addressed to avoid harm, promote …