AIMC Topic: Humans

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Artificial Intelligence-Enabled Electrocardiography Predicts Future Pacemaker Implantation and Adverse Cardiovascular Events.

Journal of medical systems
Medical advances prolonging life have led to more permanent pacemaker implants. When pacemaker implantation (PMI) is commonly caused by sick sinus syndrome or conduction disorders, predicting PMI is challenging, as patients often experience related s...

Uncertainty quantification via localized gradients for deep learning-based medical image assessments.

Physics in medicine and biology
Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep learning models have been shown to be highly accurate across a variety of tasks, measures that indi...

Deep learning-based voxel sampling for particle therapy treatment planning.

Physics in medicine and biology
Scanned particle therapy often requires complex treatment plans, robust optimization, as well as treatment adaptation. Plan optimization is especially complicated for heavy ions due to the variable relative biological effectiveness. We present a nove...

Deep learning-enabled high-speed, multi-parameter diffuse optical tomography.

Journal of biomedical optics
SIGNIFICANCE: Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical breast tumor characterization. However, conventional diffuse optical tomography (DOT) image reconstruction algorithms require case-by-case expert tuning and are...

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.

Critical care explorations
BACKGROUND AND OBJECTIVE: To develop the COVid Veteran (COVet) score for clinical deterioration in Veterans hospitalized with COVID-19 and further validate this model in both Veteran and non-Veteran samples. No such score has been derived and validat...

Comparative performance of artificial ıntelligence models in physical medicine and rehabilitation board-level questions.

Revista da Associacao Medica Brasileira (1992)
OBJECTİVES: The aim of this study was to compare the performance of artificial intelligence models ChatGPT-3.5, ChatGPT-4, and Google Bard in answering Physical Medicine and Rehabilitation board-style questions, assessing their capabilities in medic...

deepAMPNet: a novel antimicrobial peptide predictor employing AlphaFold2 predicted structures and a bi-directional long short-term memory protein language model.

PeerJ
BACKGROUND: Global public health is seriously threatened by the escalating issue of antimicrobial resistance (AMR). Antimicrobial peptides (AMPs), pivotal components of the innate immune system, have emerged as a potent solution to AMR due to their t...

Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review.

PeerJ
Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize...

Feature extraction method of EEG based on wavelet packet reconstruction and deep learning model of VR motion sickness feature classification and prediction.

PloS one
The surging popularity of virtual reality (VR) technology raises concerns about VR-induced motion sickness, linked to discomfort and nausea in simulated environments. Our method involves in-depth analysis of EEG data and user feedback to train a soph...

The SSHVEP Paradigm-Based Brain Controlled Method for Grasping Robot Using MVMD Combined CNN Model.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In recent years, the steady-state visual evoked potentials (SSVEP) based brain control method has been employed to help people with disabilities because of its advantages of high information transmission rate and low training time. However, the exist...