AIMC Topic: Humans

Clear Filters Showing 16621 to 16630 of 95995 articles

Self-supervised pre-trained neural network for quantum natural language processing.

Neural networks : the official journal of the International Neural Network Society
Quantum computing models have propelled advances in many application domains. However, in the field of natural language processing (NLP), quantum computing models are limited in representation capacity due to the high linearity of the underlying quan...

Simple and effective embedding model for single-cell biology built from ChatGPT.

Nature biomedical engineering
Large-scale gene-expression data are being leveraged to pretrain models that implicitly learn gene and cellular functions. However, such models require extensive data curation and training. Here we explore a much simpler alternative: leveraging ChatG...

Transformative laboratory medicine enabled by microfluidic automation and artificial intelligence.

Biosensors & bioelectronics
Laboratory medicine provides pivotal medical information through analyses of body fluids and tissues, and thus, it is essential for diagnosis of diseases as well as monitoring of disease progression. Despite its universal importance, the field is cur...

DropNaE: Alleviating irregularity for large-scale graph representation learning.

Neural networks : the official journal of the International Neural Network Society
Large-scale graphs are prevalent in various real-world scenarios and can be effectively processed using Graph Neural Networks (GNNs) on GPUs to derive meaningful representations. However, the inherent irregularity found in real-world graphs poses cha...

Multi-horizon event detection for in-hospital clinical deterioration using dual-channel graph attention network.

International journal of medical informatics
OBJECTIVE: In hospitals globally, the occurrence of clinical deterioration within the hospital setting poses a significant healthcare burden. Rapid clinical intervention becomes a crucial task in such cases. In this research, we propose an end-to-end...

Automated Classification of Body MRI Sequences Using Convolutional Neural Networks.

Academic radiology
RATIONALE AND OBJECTIVES: Multi-parametric MRI (mpMRI) studies of the body are routinely acquired in clinical practice. However, a standardized naming convention for MRI protocols and series does not exist currently. Conflicts in the series descripti...

Application of task-autonomous dental robot for lateral window preparation in the maxillary sinus.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
The study aimed to investigate the feasibility and accuracy of task-autonomous dental robots for lateral window preparation in the maxillary sinus, as well as to propose 3 indexes for assessing the accuracy of lateral window preparation. Twenty 1:1 r...

Revisiting the Endoscopic Third Ventriculostomy Success Score using machine learning: can we do better?

Journal of neurosurgery. Pediatrics
OBJECTIVE: The Endoscopic Third Ventriculostomy Success Score (ETVSS) is a useful decision-making heuristic when considering the probability of surgical success, defined traditionally as no repeat cerebrospinal fluid diversion surgery needed within 6...

Learning soft tissue deformation from incremental simulations.

Medical physics
BACKGROUND: Surgical planning for orthognathic procedures demands swift and accurate biomechanical modeling of facial soft tissues. Efficient simulations are vital in the clinical pipeline, as surgeons may iterate through multiple plans. Biomechanica...

Magnetic resonance image denoising for Rician noise using a novel hybrid transformer-CNN network (HTC-net) and self-supervised pretraining.

Medical physics
BACKGROUND: Magnetic resonance imaging (MRI) is a crucial technique for both scientific research and clinical diagnosis. However, noise generated during MR data acquisition degrades image quality, particularly in hyperpolarized (HP) gas MRI. While de...