Artificial intelligence in practice: Opportunities, challenges, and ethical considerations.

RL Farmer, AB Lockwood, A Goforth… - … : Research and Practice, 2024 - psycnet.apa.org
Artificial intelligence (AI) tools are being rapidly introduced into the workflow of health
service psychologists. This article critically examines the potential, limitations, and ethical …

Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects

B Koçak, A Ponsiglione, A Stanzione… - Diagnostic and …, 2024 - zora.uzh.ch
Although artificial intelligence (AI) methods hold promise for medical imaging-based
prediction tasks, their integration into medical practice may present a double-edged sword …

From Code to Clots: Applying Machine Learning to Clinical Aspects of Venous Thromboembolism Prevention, Diagnosis, and Management

P Chrysafi, B Lam, S Carton, R Patell - Hämostaseologie, 2024 - thieme-connect.com
The high incidence of venous thromboembolism (VTE) globally and the morbidity and
mortality burden associated with the disease make it a pressing issue. Machine learning …

Putting ai in fair: a framework for equity in ai-driven learner models and inclusive assessments

E Sato, V Shyyan, S Chauhan… - Journal of Measurement …, 2024 - dergipark.org.tr
This paper delves into the critical role of learner models in educational assessment and
includes a systematic review of recent literature on AI and K-12 education. This review …

[HTML][HTML] Evaluating predictive artificial intelligence approaches used in mobile health platforms to forecast mental health symptoms among youth: a systematic review

J Patel, C Hung, TR Katapally - Psychiatry Research, 2024 - Elsevier
The youth mental health crisis is exacerbated by limited access to care and resources.
Mobile health (mHealth) platforms using predictive artificial intelligence (AI) can improve …
LI Kumbo, VS Nkwera, RF Mero - ABUAD Journal of …, 2024 - journals.abuad.edu.ng
Abstract Artificial Intelligence (AI) and Machine Learning (ML) present transformative
opportunities for sectors in develo** countries like Tanzania that were previously hindered …

From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?

G Voria, S Lambiase, MC Schiavone… - arxiv preprint arxiv …, 2024 - arxiv.org
As the adoption of machine learning (ML) systems continues to grow across industries,
concerns about fairness and bias in these systems have taken center stage. Fairness …