Artificial Intelligence Medical Compendium

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

Showing 12,631 to 12,640 of 210,436 articles

Precision improvement for indoor positioning based on fuzzy inference system with ultra-wideband wireless communications.

PloS one May 21, 2026
This paper investigates the enhancement of positioning accuracy in indoor non-line-of-sight (NLOS) environments using ultra-wideband (UWB) and angle of arrival (AoA) technologies. It examines the application of moving average filters and the adaptive... read more 

Learning semantic similarity from sentence pairs using hybrid features centric approach and explainable siamese neural networks.

PloS one May 21, 2026
Semantic embeddings play an important role in modern natural language processing because they help models understand meaning beyond individual words. Accurate text similarity is essential for many applications such as search, automated scoring, summa... read more 

Optimization of artificial intelligence models for prediction of new-onset cardiovascular disease in patients with arterial hypertension.

PLOS digital health May 21, 2026
Advanced preventive strategies are needed to decrease the burden of cardiovascular disease (CVD). We aimed to develop a predictive tool to identify individuals at higher CVD risk and facilitate proactive interventions to improve clinical outcomes. Th... read more 

Eigen-guided transformer: A data-driven approach for chronic kidney disease forecasting.

PloS one May 21, 2026
Accurate prediction of Chronic Kidney Disease (CKD) development is essential for prompt therapeutic intervention; nevertheless, it is difficult due to the highly individualized disease trajectories and intricate multivariate risk profiles. Contempora... read more 

Prediction of cognitive impairment through speech data analysis: A comparative evaluation of deep learning models.

PloS one May 21, 2026
BACKGROUND: The early detection of cognitive impairments, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD), is essential for timely intervention and management. This study evaluates the performance of various deep-learning models ... read more 

Against the grain: Leveraging machine learning to analyze mudbrick structures.

PloS one May 21, 2026
Mudbricks have been a fundamental building material since the Neolithic, yet their compositional variability and technological flexibility can be challenging for systematic and reproducible fabric characterization. Morphometric parameters such as gra... read more 

Fast reconstruction of degenerate populations of conductance-based neuron models from spike times.

PLoS computational biology May 21, 2026
Inferring the biophysical parameters of conductance-based models (CBMs) from experimentally accessible recordings remains a central challenge in computational neuroscience. Spike times are the most widely available data, yet they reveal little about ... read more 

Machine learning reveals microbiome differences by periodontitis severity.

PloS one May 21, 2026
Periodontitis is a chronic inflammatory disease driven by microbial dysbiosis, yet the microbial signatures associated with severity remain incompletely understood. This study investigated changes in subgingival microbial composition across clinicall... read more 

Enhancing aviation safety: An 80-year data-driven model for classification of aviation incident and accident.

PloS one May 21, 2026
The aviation system is safety-critical by nature, and any occurrence of an incident or accident can lead to the loss of human life and significant operational disruptions. The International Civil Aviation Organization (ICAO) emphasizes that every fli... read more 

Current Artificial Intelligence Large Language Models Exhibit Sycophantic Behavior in Orthopaedic Contexts.

The Journal of bone and joint surgery. American volume May 21, 2026
BACKGROUND: The use of large language models (LLMs) is increasingly common. However, LLMs may exhibit sycophancy, echoing users' beliefs while avoiding contradiction. In the present study, we describe sycophancy in general-purpose LLMs when applied t... read more 
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