AIMC Topic: Humans

Clear Filters Showing 20061 to 20070 of 95995 articles

Factors associated with 90-day mortality in Vietnamese stroke patients: Prospective findings compared with explainable machine learning, multicenter study.

PloS one
The prevalence and predictors of mortality following an ischemic stroke or intracerebral hemorrhage have not been well established among patients in Vietnam. 2885 consecutive diagnosed patients with ischemic stroke and intracerebral hemorrhage at ten...

Effects of Individual Research Practices on fNIRS Signal Quality and Latent Characteristics.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool for cross-cultural neuroimaging studies. However, the reproducibility and comparability of fNIRS studies is still an open issue in the scientific community. The paucity of ...

Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is the estimation of musculotendon kinematics, which comprise musculotendon unit lengths, moment arms, an...

Integrating Large Language Model, EEG, and Eye-Tracking for Word-Level Neural State Classification in Reading Comprehension.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
With the recent proliferation of large language models (LLMs), such as Generative Pre-trained Transformers (GPT), there has been a significant shift in exploring human and machine comprehension of semantic language meaning. This shift calls for inter...

Efficient visual representations for learning and decision making.

Psychological review
The efficient representation of visual information is essential for learning and decision making due to the complexity and uncertainty of the world, as well as inherent constraints on the capacity of cognitive systems. We hypothesize that biological ...

A Self-Supervised Equivariant Refinement Classification Network for Diabetic Retinopathy Classification.

Journal of imaging informatics in medicine
Diabetic retinopathy (DR) is a retinal disease caused by diabetes. If there is no intervention, it may even lead to blindness. Therefore, the detection of diabetic retinopathy is of great significance for preventing blindness in patients. Most of the...

Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.

Journal of imaging informatics in medicine
Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the performance of TotalSegmentator, a state-of-the-art adult-trained CT organ segmentation model, on a s...

Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.

Journal of imaging informatics in medicine
To compare the image quality and fat attenuation index (FAI) of coronary artery CT angiography (CCTA) under different tube voltages between deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASIR-V). Three ...

Robotic Assisted Transcranial Doppler Monitoring in Acute Neurovascular Care: A Feasibility and Safety Study.

Neurocritical care
BACKGROUND: Transcranial color Doppler (TCD) is currently the only noninvasive bedside tool capable of providing real-time information on cerebral hemodynamics. However, being operator dependent, TCD monitoring is not feasible in many institutions. R...

Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography.

European radiology
OBJECTIVE: To evaluate radiation dose and image quality of a double-low CCTA protocol reconstructed utilizing high-strength deep learning image reconstructions (DLIR-H) compared to standard adaptive statistical iterative reconstruction (ASiR-V) proto...