Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
Explaining machine learning models with interactive natural language conversations using TalkToModel
Practitioners increasingly use machine learning (ML) models, yet models have become
more complex and harder to understand. To understand complex models, researchers have …
more complex and harder to understand. To understand complex models, researchers have …
Artificial Intelligence for multiple sclerosis management using retinal images: pearl, peaks, and pitfalls
Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory
processes, demyelination, neurodegeneration, and axonal damage within the central …
processes, demyelination, neurodegeneration, and axonal damage within the central …
Data-centric artificial intelligence: A survey
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …
of its great success is the availability of abundant and high-quality data for building machine …
Demographic bias in misdiagnosis by computational pathology models
Despite increasing numbers of regulatory approvals, deep learning-based computational
pathology systems often overlook the impact of demographic factors on performance …
pathology systems often overlook the impact of demographic factors on performance …
Machine learning in precision agriculture: a survey on trends, applications and evaluations over two decades
Precision agriculture represents the new age of conventional agriculture. This is made
possible by the advancement of various modern technologies such as the internet of things …
possible by the advancement of various modern technologies such as the internet of things …
Integrating low-cost sensor monitoring, satellite mapping, and geospatial artificial intelligence for intra-urban air pollution predictions
There is a growing need to apply geospatial artificial intelligence analysis to disparate
environmental datasets to find solutions that benefit frontline communities. One such …
environmental datasets to find solutions that benefit frontline communities. One such …
Benchmarking emergency department prediction models with machine learning and public electronic health records
The demand for emergency department (ED) services is increasing across the globe,
particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have …
particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have …
VisAlign: dataset for measuring the alignment between AI and humans in visual perception
AI alignment refers to models acting towards human-intended goals, preferences, or ethical
principles. Analyzing the similarity between models and humans can be a proxy measure for …
principles. Analyzing the similarity between models and humans can be a proxy measure for …
Exploring evaluation methods for interpretable machine learning: A survey
N Alangari, M El Bachir Menai, H Mathkour… - Information, 2023 - mdpi.com
In recent times, the progress of machine learning has facilitated the development of decision
support systems that exhibit predictive accuracy, surpassing human capabilities in certain …
support systems that exhibit predictive accuracy, surpassing human capabilities in certain …