AI Medical Compendium Topic

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Models, Theoretical

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Achieving Occam's razor: Deep learning for optimal model reduction.

PLoS computational biology
All fields of science depend on mathematical models. Occam's razor refers to the principle that good models should exclude parameters beyond those minimally required to describe the systems they represent. This is because redundancy can lead to incor...

MSW-Net: A hierarchical stacking model for automated municipal solid waste classification.

Journal of the Air & Waste Management Association (1995)
Efficient solid waste management is crucial for urban health and welfare in the midst of fast industrialization and urbanization. In this changing environment, government authorities have a significant role in addressing and reducing the effects of s...

Decoupling ion concentrations from effluent conductivity profiles in capacitive and battery electrode deionizations using an artificial intelligence model.

Water research
Owing to its simplicity of measurement, effluent conductivity is one of the most studied factors in evaluations of desalination performance based on the ion concentrations in various ion adsorption processes such as capacitive deionization (CDI) or b...

Investigating stronger tolerant network against cascading failures in focusing on changing degree distributions.

PloS one
Many real-world networks with Scale-Free structure are significantly vulnerable against both intentional attacks and catastrophic cascading failures. On the other hand, it has been shown that networks with narrower degree distributions have strong ro...

Clinical efficacy of pre-trained large language models through the lens of aphasia.

Scientific reports
The rapid development of large language models (LLMs) motivates us to explore how such state-of-the-art natural language processing systems can inform aphasia research. What kind of language indices can we derive from a pre-trained LLM? How do they d...

The weighted multi-scale connections networks for macrodispersivity estimation.

Journal of contaminant hydrology
Macrodispersivity is critical for predicting solute behaviors with dispersive transport models. Conventional methods of estimating macrodispersivity usually need to solve flow equations and are time-consuming. Convolutional neural networks (CNN) have...

Fine-tuning inflow prediction models: integrating optimization algorithms and TRMM data for enhanced accuracy.

Water science and technology : a journal of the International Association on Water Pollution Research
This research explores machine learning algorithms for reservoir inflow prediction, including long short-term memory (LSTM), random forest (RF), and metaheuristic-optimized models. The impact of feature engineering techniques such as discrete wavelet...

An integrated ergonomic risk assessment framework based on fuzzy logic and IVSF-AHP for optimising ergonomic risks in a mixed-model assembly line.

Ergonomics
This study proposes a systematic approach to address ergonomic factors, including physical, environmental and psychosocial aspects, in solving assembly line balancing problems. A three-stage framework is developed, starting with determining weights f...

Complex artificial intelligence models for energy sustainability in educational buildings.

Scientific reports
Energy consumption of constructed educational facilities significantly impacts economic, social and environment sustainable development. It contributes to approximately 37% of the carbon dioxide emissions associated with energy use and procedures. Th...

Assessing the risk of takeover catastrophe from large language models.

Risk analysis : an official publication of the Society for Risk Analysis
This article presents a risk analysis of large language models (LLMs), a type of "generative" artificial intelligence (AI) system that produces text, commonly in response to textual inputs from human users. The article is specifically focused on the ...