AIMC Topic: Neural Networks, Computer

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Uncertainty quantification-guided patient-specific quality assurance using Bayesian neural networks based on field complexity features and fluence maps.

Physics in medicine and biology
Recent advancements in artificial intelligence (AI)-driven prediction models for measurement-based patient-specific quality assurance (PSQA) necessitate uncertainty quantification (UQ) to ensure clinical safety.An uncertainty-guided framework was pro...

From Function to Implementation: Exploring Degeneracy in Evolved Artificial Agents.

Neural computation
Degeneracy-the ability of different structures to perform the same function-is a fundamental feature of biological systems, contributing to their robustness and evolvability. However, the ubiquity of degeneracy in systems generated through adaptive p...

Synergistic Pathways of Modulation Enable Robust Task Packing Within Neural Dynamics.

Neural computation
Understanding how brain networks learn and manage multiple tasks simultaneously is of interest in both neuroscience and artificial intelligence. In this regard, a recent research thread in theoretical neuroscience has focused on how recurrent neural ...

Exploring the Architectural Biases of the Cortical Microcircuit.

Neural computation
The cortex plays a crucial role in various perceptual and cognitive functions, driven by its basic unit, the canonical cortical microcircuit. Yet, we remain short of a framework that definitively explains the structure-function relationships of this ...

ICU Length of Stay Prediction for Patients with Diabetes Using Machine Learning and Clinical Notes.

Studies in health technology and informatics
Diabetes, a chronic disease, often leads to poor health outcomes and increased healthcare costs, particularly for patients admitted to ICU. Accurate early prediction of ICU length of stay (LOS) is vital for hospital resource management and patient ou...

Lower Extremity Bypass Surveillance and Peak Systolic Velocities Value Prediction Using Recurrent Neural Networks.

Studies in health technology and informatics
Routine duplex ultrasound surveillance is recommended after femoral-popliteal and femoral-tibial-pedal vein bypass grafts at various post-operative intervals. Currently, there is no systematic method for bypass graft surveillance using a set of peak ...

Predicting Diabetes Using Convolutional Neural Networks and EKG Entropy Analysis.

Studies in health technology and informatics
Heart Rate Variability (HRV) is associated with diabetic complications. This analysis can quantify changes in heart rate variability, and it may help detect early alterations in diabetes. This study aimed to design and validate a Convolutional Neural...

Detecting and Classifying Mycetoma in Histopathological Images Using DenseNet and U-Net.

Studies in health technology and informatics
Mycetoma, recognised by the WHO as a Neglected Tropical Disease, has significant diagnostic hurdles which lead to severe health consequences. Mycetoma can be caused by certain types of bacteria (actinomycetoma) or fungi (eumycetoma). Identifying whet...

A Neural Embedding Approach to Mapping Health Concepts to Concept Unique Identifiers.

Studies in health technology and informatics
Understanding health concepts in free text is an important task in biomedical NLP. Being able to map the extracted concepts to unique concept identifiers can facilitate integration of and interoperability across biomedical informatics applications. A...

Multimodal Fusion of EHR in Structures and Semantics: Integrating Clinical Records and Notes with Hypergraph and LLM.

Studies in health technology and informatics
In recent decades, Electronic Health Records (EHRs) have become increasingly useful to support clinical decision-making and healthcare. EHRs usually contain heterogeneous information, such as structural data in tabular form and un-structured data in ...