Current challenges and future opportunities for XAI in machine learning-based clinical decision support systems: a systematic review
Machine Learning and Artificial Intelligence (AI) more broadly have great immediate and
future potential for transforming almost all aspects of medicine. However, in many …
future potential for transforming almost all aspects of medicine. However, in many …
How machine learning will transform biomedicine
This Perspective explores the application of machine learning toward improved diagnosis
and treatment. We outline a vision for how machine learning can transform three broad …
and treatment. We outline a vision for how machine learning can transform three broad …
Autogen: Enabling next-gen llm applications via multi-agent conversation framework
This technical report presents AutoGen, a new framework that enables development of LLM
applications using multiple agents that can converse with each other to solve tasks. AutoGen …
applications using multiple agents that can converse with each other to solve tasks. AutoGen …
Human–AI collaboration enables more empathic conversations in text-based peer-to-peer mental health support
Advances in artificial intelligence (AI) are enabling systems that augment and collaborate
with humans to perform simple, mechanistic tasks such as scheduling meetings and …
with humans to perform simple, mechanistic tasks such as scheduling meetings and …
Does the whole exceed its parts? the effect of ai explanations on complementary team performance
Many researchers motivate explainable AI with studies showing that human-AI team
performance on decision-making tasks improves when the AI explains its recommendations …
performance on decision-making tasks improves when the AI explains its recommendations …
[HTML][HTML] Explainable Artificial Intelligence (XAI) from a user perspective: A synthesis of prior literature and problematizing avenues for future research
The rapid growth and use of artificial intelligence (AI)-based systems have raised concerns
regarding explainability. Recent studies have discussed the emerging demand for …
regarding explainability. Recent studies have discussed the emerging demand for …
Do as AI say: susceptibility in deployment of clinical decision-aids
Artificial intelligence (AI) models for decision support have been developed for clinical
settings such as radiology, but little work evaluates the potential impact of such systems. In …
settings such as radiology, but little work evaluates the potential impact of such systems. In …
Human–computer collaboration for skin cancer recognition
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …
intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI …
Towards a science of human-ai decision making: a survey of empirical studies
As AI systems demonstrate increasingly strong predictive performance, their adoption has
grown in numerous domains. However, in high-stakes domains such as criminal justice and …
grown in numerous domains. However, in high-stakes domains such as criminal justice and …
Human-centered explainable ai (xai): From algorithms to user experiences
QV Liao, KR Varshney - arXiv preprint arXiv:2110.10790, 2021 - arxiv.org
In recent years, the field of explainable AI (XAI) has produced a vast collection of algorithms,
providing a useful toolbox for researchers and practitioners to build XAI applications. With …
providing a useful toolbox for researchers and practitioners to build XAI applications. With …