Artificial Intelligence Medical Compendium

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

Showing 3,461 to 3,470 of 168,679 articles

Query Attribute Modeling: Improving search relevance with Semantic Search and Meta Data Filtering

arXiv
This study introduces Query Attribute Modeling (QAM), a hybrid framework that enhances search precision and relevance by decomposing open text queries into structured metadata tags and semantic elements. QAM addresses traditional search limitations... read more 

A machine learning approach for image classification in synthetic aperture RADAR

arXiv
We consider the problem in Synthetic Aperture RADAR (SAR) of identifying and classifying objects located on the ground by means of Convolutional Neural Networks (CNNs). Specifically, we adopt a single scattering approximation to classify the shape ... read more 

Predicting soil organic carbon with ensemble learning techniques by using satellite images for precision farming.

Scientific reports
Soil plays a major role in the agricultural system. Soil composition detection can help farmers to take appropriate decision leading to proper crop growth. Soil organic carbon is crucial for many soil activities and ecological characteristics, is at ... read more 

Deep neural network models of emotion understanding.

Cognition & emotion
Deep neural networks (DNNs) provide a useful computational framework for constructing cognitive models of emotion understanding. This paper provides a focused discussion of the use of DNNs in this context. It begins by defining three key components o... read more 

Readability analysis of breast cancer resources shared on X-implications for patient education and the potential of AI.

Breast cancer research and treatment
PURPOSE: Breast cancer remains a global public health burden. This study aimed to evaluate the readability of breast cancer articles shared on X (formerly Twitter) during Breast Cancer Awareness Month (October 2024), and it explores the possibility o... read more 

Transductive zero-shot learning via knowledge graph and graph convolutional networks.

Scientific reports
Zero-shot learning methods are used to recognize objects of unseen categories. By transferring knowledge from the seen classes to describe the unseen classes, deep learning models can recognize unseen categories. However, relying solely on a small la... read more 

Are Today's LLMs Ready to Explain Well-Being Concepts?

arXiv
Well-being encompasses mental, physical, and social dimensions essential to personal growth and informed life decisions. As individuals increasingly consult Large Language Models (LLMs) to understand well-being, a key challenge emerges: Can LLMs ge... read more 

A Comprehensive Framework for Uncertainty Quantification of Voxel-wise Supervised Models in IVIM MRI

arXiv
Accurate estimation of intravoxel incoherent motion (IVIM) parameters from diffusion-weighted MRI remains challenging due to the ill-posed nature of the inverse problem and high sensitivity to noise, particularly in the perfusion compartment. In th... read more 

Adaptive context biasing in transformer-based ASR systems.

Scientific reports
With the advancement of neural networks, end-to-end neural automatic speech recognition (ASR) systems have demonstrated significant improvements in identifying contextually biased words. However, the incorporation of bias layers introduces additional... read more 

Neural Synchrony and Consumer Behavior: Predicting Friends' Behavior in Real-World Social Networks.

The Journal of neuroscience : the official journal of the Society for Neuroscience
The endogenous aspect of social influence, reflected in the spontaneous alignment of behaviors within close social relationships, plays a crucial role in understanding human social behavior. In two studies involving 222 human subjects (Study 1:  = 17... read more