AIMC Topic: Humans

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On human-in-the-loop optimization of human-robot interaction.

Nature
From industrial exoskeletons to implantable medical devices, robots that interact closely with people are poised to improve every aspect of our lives. Yet designing these systems is very challenging; humans are incredibly complex and, in many cases, ...

Emergence of cooperation in the one-shot Prisoner's dilemma through Discriminatory and Samaritan AIs.

Journal of the Royal Society, Interface
As artificial intelligence (AI) systems are increasingly embedded in our lives, their presence leads to interactions that shape our behaviour, decision-making and social interactions. Existing theoretical research on the emergence and stability of co...

Deep learning for blood glucose level prediction: How well do models generalize across different data sets?

PloS one
Deep learning-based models for predicting blood glucose levels in diabetic patients can facilitate proactive measures to prevent critical events and are essential for closed-loop control therapy systems. However, selecting appropriate models from the...

Continuous Short-Term Pain Assessment in Temporomandibular Joint Therapy Using LSTM Models Supported by Heat-Induced Pain Data Patterns.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This study aims to design a time-continuous pain level assessment system for temporomandibular joint therapy. Our objectives cover verifying literature suggestions on pain stimulus, protocols for collecting reference data, and continuous pain recogni...

Performance of a Novel Muscle Synergy Approach for Continuous Motion Estimation on Untrained Motion.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
When applying continuous motion estimation (CME) model based on sEMG to human-robot system, it is inevitable to encounter scenarios in which the motions performed by the user are different from the motions in the training stage of the model. It has b...

Subject-Independent Wearable P300 Brain-Computer Interface Based on Convolutional Neural Network and Metric Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user experience of the system. Each user needs to spend additional time establishing a decoder adapted to their own brainwaves. Therefore, achieving subje...

Editorial Commentary: Machine Learning and Artificial Intelligence Are Valuable Tools yet Dependent on the Data Input.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
Machine learning is likely to become one of the most valuable tools for predicting outcomes in patients with patellofemoral instability. Traditional statistical analysis is challenging in this diagnosis as the result of the multitude of risk factors....

Evaluating ChatGPT as a patient resource for frequently asked questions about lung cancer surgery-a pilot study.

The Journal of thoracic and cardiovascular surgery
OBJECTIVE: Chat-based artificial intelligence programs like ChatGPT are reimagining how patients seek information. This study aims to evaluate the quality and accuracy of ChatGPT-generated answers to common patient questions about lung cancer surgery...

Upfront surgery for intrahepatic cholangiocarcinoma: Prediction of futility using artificial intelligence.

Surgery
OBJECTIVE: We sought to identify patients at risk of "futile" surgery for intrahepatic cholangiocarcinoma using an artificial intelligence (AI)-based model based on preoperative variables.

Randomized controlled trial of an artificial intelligence diagnostic system for the detection of esophageal squamous cell carcinoma in clinical practice.

Endoscopy
BACKGROUND: Artificial intelligence (AI) has made remarkable progress in image recognition using deep learning systems. It has been used to detect esophageal squamous cell carcinoma (ESCC); however, none of the previous reports were investigations in...