AI Medical Compendium Journal:
Frontiers in artificial intelligence

Showing 21 to 30 of 147 articles

SineKAN: Kolmogorov-Arnold Networks using sinusoidal activation functions.

Frontiers in artificial intelligence
Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation functions on the edges of the computational graph fo...

Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.

Frontiers in artificial intelligence
BACKGROUND: The Department of Rehabilitation Medicine is key to improving patients' quality of life. Driven by chronic diseases and an aging population, there is a need to enhance the efficiency and resource allocation of outpatient facilities. This ...

The sociolinguistic foundations of language modeling.

Frontiers in artificial intelligence
In this article, we introduce a sociolinguistic perspective on language modeling. We claim that language models in general are inherently modeling , and we consider how this insight can inform the development and deployment of language models. We beg...

Artificial intelligence-based framework for early detection of heart disease using enhanced multilayer perceptron.

Frontiers in artificial intelligence
Cardiac disease refers to diseases that affect the heart such as coronary artery diseases, arrhythmia and heart defects and is amongst the most difficult health conditions known to humanity. According to the WHO, heart disease is the foremost cause o...

Evaluating accuracy and reproducibility of large language model performance on critical care assessments in pharmacy education.

Frontiers in artificial intelligence
BACKGROUND: Large language models (LLMs) have demonstrated impressive performance on medical licensing and diagnosis-related exams. However, comparative evaluations to optimize LLM performance and ability in the domain of comprehensive medication man...

Fostering effective hybrid human-LLM reasoning and decision making.

Frontiers in artificial intelligence
The impressive performance of modern Large Language Models (LLMs) across a wide range of tasks, along with their often non-trivial errors, has garnered unprecedented attention regarding the potential of AI and its impact on everyday life. While consi...

Application progress of artificial intelligence in tumor diagnosis and treatment.

Frontiers in artificial intelligence
The rapid advancement of artificial intelligence (AI) has introduced transformative opportunities in oncology, enhancing the precision and efficiency of tumor diagnosis and treatment. This review examines recent advancements in AI applications across...

A systematic review of Machine Learning and Deep Learning approaches in Mexico: challenges and opportunities.

Frontiers in artificial intelligence
This systematic review provides a state-of-art of Artificial Intelligence (AI) models such as Machine Learning (ML) and Deep Learning (DL) development and its applications in Mexico in diverse fields. These models are recognized as powerful tools in ...

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets.

Frontiers in artificial intelligence
Packed columns are commonly used in post-combustion processes to capture CO emissions by providing enhanced contact area between a CO-laden gas and CO-absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs...

A bird's-eye view of the biological mechanism and machine learning prediction approaches for cell-penetrating peptides.

Frontiers in artificial intelligence
Cell-penetrating peptides (CPPs) are highly effective at passing through eukaryotic membranes with various cargo molecules, like drugs, proteins, nucleic acids, and nanoparticles, without causing significant harm. Creating drug delivery systems with ...