AI Medical Compendium

Physics-embedded graph neural operator for interaction-controlled colloidal aggregation.

Water research Mar 20, 2026

Colloidal aggregation in natural and engineered waters is a complex function of both particle and groundwater electrochemical conditions, yet predicting aggregation behavior across diffusion-limited and reaction-limited regimes remains challenging du... read more

A systematic review of generative artificial intelligence techniques for synthetic medical image datasets: Quality, models, public availability and applications.

Computer methods and programs in biomedicine Mar 20, 2026

BACKGROUND AND OBJECTIVE: Generative Artificial Intelligence (GAI) offers promising solutions to long-standing challenges in developing medical imaging methods and applications, including data scarcity, privacy concerns, and class imbalance. However,... read more

Paper-based single-enzyme dual-substrate assay for rapid detection and differentiation of E. coli and E. coli O157:H7.

Biosensors & bioelectronics Mar 20, 2026

E. coli is usually harmless, but Shiga toxin-producing strains such as O157:H7 can cause severe disease, highlighting the need for rapid, low-cost, field-deployable detection methods. Here, we present a rapid paper-based dual-substrate colorimetric a... read more

Optimizing pediatric chest CT: superior image quality and lower radiation dose with deep learning reconstruction.

European journal of radiology Mar 20, 2026

OBJECTIVES: To compare image quality and radiation dose between deep learning reconstruction (DLIR) and hybrid iterative reconstruction (HIR) algorithms in unenhanced pediatric chest CT. MATERIALS AND METHODS: This hybrid prospective-retrospective st... read more

AnomalyTCN: Efficient contrastive-based time series anomaly detection with pure convolution structure.

Neural networks : the official journal of the International Neural Network Society Mar 20, 2026

In recent years, contrastive-based time series anomaly detection has emerged rapidly and become compelling thanks to its performance superiority. But at the same time, we observe that existing contrastive-based methods can only work with the complica... read more

Prediction of femoral shaft fracture healing and clinical decision support through integration of mechano-biological modeling and machine learning.

Computer methods and programs in biomedicine Mar 20, 2026

BACKGROUND AND OBJECTIVES: Current clinical practice in preoperative planning for femoral shaft fractures lacks tools capable of quantitatively predicting outcomes across different treatment options, which significantly hinders the implementation of ... read more

Prediction of gene expression levels in Saccharomyces cerevisiae based on chromatin accessibility using multiple machine learning models.

Computational biology and chemistry Mar 20, 2026

Chromatin accessibility is generally associated with the binding of transcription factors and other regulatory proteins, which is fundamental to governing gene transcription. While the association between chromatin accessibility and gene expression l... read more

Deep learning-assisted Ce/Zr-MOF nanozyme hydrogel sensor for colorimetric/photothermal dual-mode detection of glyphosate.

Talanta Mar 20, 2026

The extensive application of glyphosate (GLY) in modern agriculture has raised increasing concerns regarding environmental contamination and food safety. In this work, a dual-mode hydrogel sensing platform was constructed based on Ce/Zr-MOF with intr... read more

AI chatbots for patient education in localized prostate cancer radiotherapy: A comparative quality and readability analysis.

Patient education and counseling Mar 20, 2026

OBJECTIVES: This study aimed to conduct a comparative quality assessment of information provided by widely used artificial intelligence chatbots (AICs) regarding radiotherapy for localized prostate cancer, with a focus on reliability, readability, an... read more

A progressive screening strategy by combining UHPLCQTOF-MS and machine learning for distinguishing different varieties of Citri Reticulatae Pericarpium.

Journal of pharmaceutical and biomedical analysis Mar 20, 2026

This study employed UHPLC-QTOF-MS-based untargeted metabolomics, integrated with chemometrics and machine learning, to discriminate between varieties of Citri Reticulatae Pericarpium (CRP). To identify specific markers between each pair of varieties ... read more

Artificial Intelligence Medical Compendium