AIMC Topic: Bias
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Mitigating biases in feature selection and importance assessments in predictive models using LASSO regression.
Oral oncology
Nov 1, 2024
Yuan et al. developed a predictive model for early response using sub-regional radiomic features from multi-sequence MRI alongside clinical factors. However, biases in feature selection and assessment may lead to misleading conclusions regarding feat...
Laboratory Data as a Potential Source of Bias in Healthcare Artificial Intelligence and Machine Learning Models.
Annals of laboratory medicine
Oct 24, 2024
Artificial intelligence (AI) and machine learning (ML) are anticipated to transform the practice of medicine. As one of the largest sources of digital data in healthcare, laboratory results can strongly influence AI and ML algorithms that require lar...
Ethicara for Responsible AI in Healthcare: A System for Bias Detection and AI Risk Management.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Oct 21, 2024
The increasing torrents of health AI innovations hold promise for facilitating the delivery of patient-centered care. Yet the enablement and adoption of AI innovations in the healthcare and life science industries can be challenging with the rising c...
Data-centric challenges with the application and adoption of artificial intelligence for drug discovery.
Expert opinion on drug discovery
Sep 24, 2024
INTRODUCTION: Artificial intelligence (AI) is exhibiting tremendous potential to reduce the massive costs and long timescales of drug discovery. There are however important challenges currently limiting the impact and scope of AI models.
Disability Ethics and Education in the Age of Artificial Intelligence: Identifying Ability Bias in ChatGPT and Gemini.
Archives of physical medicine and rehabilitation
Aug 30, 2024
OBJECTIVE: To identify and quantify ability bias in generative artificial intelligence large language model chatbots, specifically OpenAI's ChatGPT and Google's Gemini.
Mitigating the risk of artificial intelligence bias in cardiovascular care.
The Lancet. Digital health
Aug 29, 2024
Digital health technologies can generate data that can be used to train artificial intelligence (AI) algorithms, which have been particularly transformative in cardiovascular health-care delivery. However, digital and health-care data repositories th...
Acquisition parameters influence AI recognition of race in chest x-rays and mitigating these factors reduces underdiagnosis bias.
Nature communications
Aug 29, 2024
A core motivation for the use of artificial intelligence (AI) in medicine is to reduce existing healthcare disparities. Yet, recent studies have demonstrated two distinct findings: (1) AI models can show performance biases in underserved populations,...
The risks and benefits of using AI for diagnosis: beware of unconscious bias.
Multiple sclerosis and related disorders
Aug 28, 2024
Zero- and few-shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials.
Research synthesis methods
Aug 23, 2024
Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of availabl...
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