AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning.

PloS one
Autonomous transportation systems have the potential to greatly impact the way we travel. A vital aspect of these systems is their connectivity, facilitated by intelligent transport applications. However, the safety ensured by the vehicular network c...

LazyAct: Lazy actor with dynamic state skip based on constrained MDP.

PloS one
Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. Specifically, each decision made by a...

Machine learning-based analyzing earthquake-induced slope displacement.

PloS one
Accurately evaluating earthquake-induced slope displacement is a key factor for designing slopes that can effectively respond to seismic activity. This study evaluates the capabilities of various machine learning models, including artificial neural n...

Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients.

PloS one
BACKGROUND: A second primary malignant tumor is one of the most important factors affecting the long-term survival of young women with breast cancer (YWBC). As one of the main treatments for breast cancer YWBC patients, postoperative radiotherapy (PO...

Why do people resist AI-based autonomous cars?: Analyzing the impact of the risk perception paradigm and conditional value on public acceptance of autonomous vehicles.

PloS one
This study examines the factors that lead to the acceptance of AI-based autonomous vehicles. Despite the considerable importance of AI-based autonomous vehicles there has been a lack of analysis based on theoretical models and analysis that considers...

FIRM image analysis: A machine learning workflow for quantifying extracellular matrix components from electron microscopy images.

PloS one
The extracellular matrix (ECM) is a complex network of biomolecules that plays an integral role in the structure, processes, and signaling mechanisms of cells and tissues. Identifying and quantifying changes in these matrix components provides insigh...

Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets.

PloS one
Shoulder X-ray images typically have low contrast and high noise levels, making it challenging to distinguish and identify subtle anatomical structures. While existing image enhancement techniques are effective in improving contrast, they often overl...

Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation.

PloS one
This work focuses on the efficiency of the knowledge distillation approach in generating a lightweight yet powerful BERT-based model for natural language processing (NLP) applications. After the model creation, we applied the resulting model, LastBER...

Decoupled level and flow rate control of a two-tank system in beverage production: A comparative analysis of Fuzzy-PID and GA-PID for minimum time operation.

PloS one
Due to the nonlinear characteristics of the valves and the interactions between the controlled variables, designing a control system for coupled tanks is a difficult task. This paper deals with the comparative study between Fuzzy-PID and GA-PID contr...

Federated learning based reference evapotranspiration estimation for distributed crop fields.

PloS one
Water resource management and sustainable agriculture rely heavily on accurate Reference Evapotranspiration (ETo). Efforts have been made to simplify the (ETo) estimation using machine learning models. The existing approaches are limited to a single ...