AIMC Topic: Humans

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[Artificial intelligence in medicine-Opportunities and risks from an ethical perspective].

Die Ophthalmologie
Imaging disciplines, such as ophthalmology, offer a wide range of opportunities for the beneficial use of artificial intelligence (AI). The analysis of images and data by trained algorithms has the potential to facilitate making the diagnosis and pat...

Hardware Optimization and Implementation of a 16-Channel Neural Tree Classifier for On-Chip Closed-Loop Neuromodulation.

IEEE transactions on biomedical circuits and systems
This work presents the development of on-chip machine learning (ML) classifiers for implantable neuromodulation system-on-chips (SoCs), aimed at detecting epileptic seizures for closed-loop neuromodulation applications. Tree-based classifiers have ga...

Scalable Multi-FPGA HPC Architecture for Associative Memory System.

IEEE transactions on biomedical circuits and systems
Associative memory is a cornerstone of cognitive intelligence within the human brain. The Bayesian confidence propagation neural network (BCPNN), a cortex-inspired model with high biological plausibility, has proven effective in emulating high-level ...

RRAM-Based Spiking Neural Network With Target-Modulated Spike-Timing-Dependent Plasticity.

IEEE transactions on biomedical circuits and systems
The spiking neural network (SNN) training with spike timing-dependent plasticity (STDP) for image classification usually requires a lot of neurons to extract representative features and(or) needs an external classifier. Conventional bio-inspired lear...

High-Performance Method and Architecture for Attention Computation in DNN Inference.

IEEE transactions on biomedical circuits and systems
In recent years, The combination of Attention mechanism and deep learning has a wide range of applications in the field of medical imaging. However, due to its complex computational processes, existing hardware architectures have high resource consum...

Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma.

Frontiers in immunology
BACKGROUND: Unlike lung adenocarcinoma, patients with advanced squamous carcinoma exhibit a low proportion of driver gene positivity, with fewer effective treatment strategies available. Chemoimmunotherapy has now become the standard first-line treat...

Exploring the impact of AI on unemployment for people with disabilities: do educational attainment and governance matter?

Frontiers in public health
The current study investigates the impact of artificial intelligence (AI) on unemployment among people with disabilities, focusing on the mediating role of education and the moderating effect of governance quality. Using panel data from 27 high-tech ...

Artificial intelligence in hospital infection prevention: an integrative review.

Frontiers in public health
BACKGROUND: Hospital-acquired infections (HAIs) represent a persistent challenge in healthcare, contributing to substantial morbidity, mortality, and economic burden. Artificial intelligence (AI) offers promising potential for improving HAIs preventi...

Identifying the Most Critical Predictors of Workplace Violence Experienced by Junior Nurses: An Interpretable Machine Learning Perspective.

Journal of nursing management
Workplace violence, defined as any disruptive behavior or threat to employees, seriously threatens junior nurses. Compared with senior nurses, junior nurses are more vulnerable to workplace violence due to inexperience, low professional recognition,...

Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal of digestive diseases
OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.