AIMC Topic: Artificial Intelligence

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Improved Stroke Care in a Primary Stroke Centre Using AI-Decision Support.

Cerebrovascular diseases extra
BACKGROUND: Patient selection for reperfusion therapies requires significant expertise in neuroimaging. Increasingly, machine learning-based analysis is used for faster and standardized patient selection. However, there is little information on how s...

Artificial intelligence in the diagnosis of multiple sclerosis: A systematic review.

Multiple sclerosis and related disorders
BACKGROUND: In recent years Artificial intelligence (AI) techniques are rapidly evolving into clinical practices such as diagnosis and prognosis processes, assess treatment effectiveness, and monitoring of diseases. The previous studies showed intere...

[Forecasts from the retort. A Greek gift of artificial intelligence : Interdisciplinary data analysis in preoperative imaging diagnostics].

Der Chirurg; Zeitschrift fur alle Gebiete der operativen Medizen
The growing influence of artificial intelligence on radiology not only leads to a fundamental change in the way diagnoses are made but also creates a wealth of additional information. Many programs correlate the parameters of image evaluation with th...

Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation.

Journal of chemical information and modeling
The application of deep learning to generative molecule design has shown early promise for accelerating lead series development. However, questions remain concerning how factors like training, data set, and seed bias impact the technology's utility t...

De Novo Peptide and Protein Design Using Generative Adversarial Networks: An Update.

Journal of chemical information and modeling
Nowadays, machine learning and deep learning approaches are widely utilized for generative chemistry and computer-aided drug design and discovery such as de novo peptide and protein design, where target-specific peptide-based/protein-based therapeuti...

CVDF DYNAMIC-A Dynamic Fuzzy Testing Sample Generation Framework Based on BI-LSTM and Genetic Algorithm.

Sensors (Basel, Switzerland)
As one of the most effective methods of vulnerability mining, fuzzy testing has scalability and complex path detection ability. Fuzzy testing sample generation is the key step of fuzzy testing, and the quality of sample directly determines the vulner...

AI-Based Publicity Strategies for Medical Colleges: A Case Study of Healthcare Analysis.

Frontiers in public health
The health status and cognition of undergraduates, especially the scientific concept of healthcare, are particularly important for the overall development of society and themselves. The survey shows that there is a significant lack of knowledge about...

Optimal Architecture of Floating-Point Arithmetic for Neural Network Training Processors.

Sensors (Basel, Switzerland)
The convergence of artificial intelligence (AI) is one of the critical technologies in the recent fourth industrial revolution. The AIoT (Artificial Intelligence Internet of Things) is expected to be a solution that aids rapid and secure data process...

Real-time monitoring the color changes of large yellow croaker (Larimichthys crocea) fillets based on hyperspectral imaging empowered with artificial intelligence.

Food chemistry
Vis-NIR hyperspectral imaging (HSI) system combined with artificial neural networks was investigated for the first time to monitor color changes of large yellow croaker (Larimichthys crocea) fillets during low-temperature storage. Feed-forward neural...