AIMC Topic: Decision Making

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Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence.

PloS one
With the development of digital health, enhancing decision-making effectiveness has become a critical task. This study proposes an improved Artificial Bee Colony (ABC) algorithm aimed at optimizing decision-making models in the field of digital healt...

Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review.

BMC medical research methodology
BACKGROUND: This scoping review systematically maps externally validated machine learning (ML)-based models in cancer patient care, quantifying their performance, and clinical utility, and examining relationships between models, cancer types, and cli...

Artificial intelligence in neurovascular decision-making: a comparative analysis of ChatGPT-4 and multidisciplinary expert recommendations for unruptured intracranial aneurysms.

Neurosurgical review
In the multidisciplinary treatment of cerebrovascular diseases, specialists from different disciplines strive to develop patient-specific treatment recommendations. ChatGPT is a natural language processing chatbot with increasing applicability in med...

Constraining an Unconstrained Multi-agent Policy with offline data.

Neural networks : the official journal of the International Neural Network Society
Real-world multi-agent decision-making systems often have to satisfy some constraints, such as harmfulness, economics, etc., spurring the emergence of Constrained Multi-Agent Reinforcement Learning (CMARL). Existing studies of CMARL mainly focus on t...

Latent circuit inference from heterogeneous neural responses during cognitive tasks.

Nature neuroscience
Higher cortical areas carry a wide range of sensory, cognitive and motor signals mixed in heterogeneous responses of single neurons tuned to multiple task variables. Dimensionality reduction methods that rely on correlations between neural activity a...

AI Ethics beyond Principles: Strengthening the Life-world Perspective.

Science and engineering ethics
The search for ethical guidance in the development of artificial intelligence (AI) systems, especially in healthcare and decision support, remains a crucial effort. So far, principles usually serve as the main reference points to achieve ethically co...

LazyAct: Lazy actor with dynamic state skip based on constrained MDP.

PloS one
Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. Specifically, each decision made by a...

AI language model rivals expert ethicist in perceived moral expertise.

Scientific reports
People view AI as possessing expertise across various fields, but the perceived quality of AI-generated moral expertise remains uncertain. Recent work suggests that large language models (LLMs) perform well on tasks designed to assess moral alignment...

Me vs. the machine? Subjective evaluations of human- and AI-generated advice.

Scientific reports
Artificial intelligence ("AI") has the potential to vastly improve human decision-making. In line with this, researchers have increasingly sought to understand how people view AI, often documenting skepticism and even outright aversion to these tools...

When and what patients need to know about AI in clinical care.

Swiss medical weekly
In this article, we describe and analyse when and what patients need to be told about the use of artificial intelligence in clinical care. In many circumstances, patients do not need to be told about the use of AI, but in cases in which AI is making ...