AIMC Topic: Humans

Clear Filters Showing 23101 to 23110 of 95995 articles

A Human-AI interaction paradigm and its application to rhinocytology.

Artificial intelligence in medicine
This article explores Human-Centered Artificial Intelligence (HCAI) in medical cytology, with a focus on enhancing the interaction with AI. It presents a Human-AI interaction paradigm that emphasizes explainability and user control of AI systems. It ...

Digital Ink and Surgical Dreams: Perceptions of Artificial Intelligence-Generated Essays in Residency Applications.

The Journal of surgical research
INTRODUCTION: Large language models like Chat Generative Pre-Trained Transformer (ChatGPT) are increasingly used in academic writing. Faculty may consider use of artificial intelligence (AI)-generated responses a form of cheating. We sought to determ...

Classification of subtask types and skill levels in robot-assisted surgery using EEG, eye-tracking, and machine learning.

Surgical endoscopy
BACKGROUND: Objective and standardized evaluation of surgical skills in robot-assisted surgery (RAS) holds critical importance for both surgical education and patient safety. This study introduces machine learning (ML) techniques using features deriv...

A systematic literature review of predicting patient discharges using statistical methods and machine learning.

Health care management science
Discharge planning is integral to patient flow as delays can lead to hospital-wide congestion. Because a structured discharge plan can reduce hospital length of stay while enhancing patient satisfaction, this topic has caught the interest of many hea...

Reducing language barriers, promoting information absorption, and communication using fanyi.

Chinese medical journal
Interpreting genes of interest is essential for identifying molecular mechanisms, but acquiring such information typically involves tedious manual retrieval. To streamline this process, the fanyi package offers tools to retrieve gene information from...

Brain age prediction using interpretable multi-feature-based convolutional neural network in mild traumatic brain injury.

NeuroImage
BACKGROUND: Convolutional neural network (CNN) can capture the structural features changes of brain aging based on MRI, thus predict brain age in healthy individuals accurately. However, most studies use single feature to predict brain age in healthy...

Contextual AI models for single-cell protein biology.

Nature methods
Understanding protein function and developing molecular therapies require deciphering the cell types in which proteins act as well as the interactions between proteins. However, modeling protein interactions across biological contexts remains challen...

Efficient Deep Model Ensemble Framework for Drug-Target Interaction Prediction.

The journal of physical chemistry letters
Accurate prediction of Drug-Target Interactions (DTI) is crucial for drug development. Current state-of-the-art deep learning methods have significantly advanced the field; however, these methods exhibit limitations in predictive performance and the ...