AIMC Topic: Humans

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Lane-change intention recognition considering oncoming traffic: Novel insights revealed by advances in deep learning.

Accident; analysis and prevention
Lane-changing (LC) intention recognition models have seen limited real-world application due to a lack of research on two-lane two-way road environments. This study constructs a high-fidelity simulated two-lane two-way road to develop a Transformer m...

Multi-modal deep learning networks for RGB-D pavement waste detection and recognition.

Waste management (New York, N.Y.)
To create a clean living environment, governments around the world have hired a large number of workers to clean up waste on pavements, which is inefficient for waste management. To better alleviate this problem, relevant scholars have proposed sever...

Bolstering Advance Care Planning Measurement Using Natural Language Processing.

Journal of palliative medicine
Despite its growth as a clinical activity and research topic, the complex dynamic nature of advance care planning (ACP) has posed serious challenges for researchers hoping to quantitatively measure it. Methods for measurement have traditionally depen...

Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery.

Expert opinion on drug discovery
INTRODUCTION: Targeting RNAs with small molecules offers an alternative to the conventional protein-targeted drug discovery and can potentially address unmet and emerging medical needs. The recent rise of interest in the strategy has already resulted...

Predicting malnutrition in gastric cancer patients using computed tomography(CT) deep learning features and clinical data.

Clinical nutrition (Edinburgh, Scotland)
OBJECTIVE: The aim of this study is using clinical factors and non-enhanced computed tomography (CT) deep features of the psoas muscles at third lumbar vertebral (L3) level to construct a model to predict malnutrition in gastric cancer before surgery...

Identifying potential ligand-receptor interactions based on gradient boosted neural network and interpretable boosting machine for intercellular communication analysis.

Computers in biology and medicine
Cell-cell communication is essential to many key biological processes. Intercellular communication is generally mediated by ligand-receptor interactions (LRIs). Thus, building a comprehensive and high-quality LRI resource can significantly improve in...

Extracting adverse drug events from clinical Notes: A systematic review of approaches used.

Journal of biomedical informatics
BACKGROUND: An adverse drug event (ADE) is any unfavorable effect that occurs due to the use of a drug. Extracting ADEs from unstructured clinical notes is essential to biomedical text extraction research because it helps with pharmacovigilance and p...