AIMC Topic: Decision Making

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DeepSOFA: A Continuous Acuity Score for Critically Ill Patients using Clinically Interpretable Deep Learning.

Scientific reports
Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require time-consuming, error-prone calculations using static variable thresholds. These methods do not capitalize on the emerging a...

Using a Support Vector Machine Based Decision Stage to Improve the Fault Diagnosis on Gearboxes.

Computational intelligence and neuroscience
Gearboxes are mechanical devices that play an essential role in several applications, e.g., the transmission of automotive vehicles. Their malfunctioning may result in economic losses and accidents, among others. The rise of powerful graphical proces...

Good advice is beyond all price, but what if it comes from a machine?

Journal of experimental psychology. Applied
As nonhuman agents are integrated into the workforce, the question becomes to what extent advice seeking in technology-infused environments depends on the perceived fit between agent and task and whether humans are willing to consider advice from non...

Building Moral Robots: Ethical Pitfalls and Challenges.

Science and engineering ethics
This paper examines the ethical pitfalls and challenges that non-ethicists, such as researchers and programmers in the fields of computer science, artificial intelligence and robotics, face when building moral machines. Whether ethics is "computable"...

Network structure and input integration in competing firing rate models for decision-making.

Journal of computational neuroscience
Making a decision among numerous alternatives is a pervasive and central undertaking encountered by mammals in natural settings. While decision making for two-option tasks has been studied extensively both experimentally and theoretically, characteri...

Pedestrian's risk-based negotiation model for self-driving vehicles to get the right of way.

Accident; analysis and prevention
Negotiations among drivers and pedestrians are common on roads, but it is still challenging for a self-driving vehicle to negotiate for its right of way with other human road users, especially pedestrians. Currently, the self-driving vehicles are pro...

Task representations in neural networks trained to perform many cognitive tasks.

Nature neuroscience
The brain has the ability to flexibly perform many tasks, but the underlying mechanism cannot be elucidated in traditional experimental and modeling studies designed for one task at a time. Here, we trained single network models to perform 20 cogniti...

Facility Layout Planning with SHELL and Fuzzy AHP Method Based on Human Reliability for Operating Theatre.

Journal of healthcare engineering
A well-design facility layout planning refers to the reduction of the operation cost in the manufacturing and service industry. This work consists of reliability analysis of facility layout for an operating theatre; it aims at proposing a new evaluat...

A Group Decision Making Framework Based on Neutrosophic TOPSIS Approach for Smart Medical Device Selection.

Journal of medical systems
Advances in the medical industry has become a major trend because of the new developments in information technologies. This research offers a novel approach for estimating the smart medical devices (SMDs) selection process in a group decision making ...

The Relationship Between Trust and Use Choice in Human-Robot Interaction.

Human factors
OBJECTIVE: To understand the influence of trust on use choice in human-robot interaction via experimental investigation.