AI Medical Compendium

AI-based plastic waste classification for sorting purposes: A review on recent progresses and challenges.

Waste management (New York, N.Y.) Apr 19, 2026

The rapid growth of plastic waste has heightened environmental concerns and created a pressing need for efficient classification for sorting purposes and recycling accordingly. In recent years, Artificial Intelligence (AI) based identification and cl... read more

Creativity in the age of AI: Exploring moderated mediation relationships between AI use, AI dependence, and academic support in higher education.

Acta psychologica Apr 19, 2026

Artificial intelligence is increasingly being adopted in higher education. However, its usage has created new possibilities and challenges. It has transformed the way students acquire and apply knowledge. Although AI usage improves efficiency, concer... read more

Unveiling novel biomarkers for diabetes-related complications through large-scale proteomics analysis: A FIELD sub-study.

Journal of diabetes and its complications Apr 19, 2026

BACKGROUND: Vascular complications of Type 2 diabetes (T2D) significantly contribute to its morbidity and mortality. Identifying robust biomarkers is critical for improving risk prediction, understanding disease mechanisms, and guiding targeted thera... read more

Copper stress responses in Scenedesmus obliquus-Bacillus subtilis Consortia: Machine Learning-Based prediction of copper removal.

Bioresource technology Apr 19, 2026

Copper pollution in wastewater is an environmental issue that requires efficient and sustainable waste treatment methods. To improve the efficiency of traditional microalgal treatment of heavy metals and enable predictive assessment of treatment outc... read more

Cuproptosis-related circulating non-coding RNAs as diagnostic and prognostic biomarkers in oncology.

Clinica chimica acta; international journal of clinical chemistry Apr 19, 2026

Cuproptosis is a recently described copper-dependent form of regulated cell death linked to mitochondrial metabolic stress and is emerging as a biologically relevant pathway in cancer. Circulating noncoding RNAs (ncRNAs), such as microRNAs, long nonc... read more

Optimizing laboratory X-ray diffraction contrast tomography: Effects of detector binning.

Ultramicroscopy Apr 19, 2026

In laboratory-based diffraction contrast tomography (LabDCT), pixel binning on 2D detectors is an effective strategy to reduce exposure time and improve acquisition efficiency. However, its impact on reconstruction accuracy remains unclear. To addres... read more

A physically guided and interpretable SWAT-BiLSTM framework with Bayesian optimization for bias correction in daily streamflow forecasting.

Journal of contaminant hydrology Apr 19, 2026

Accurate extreme streamflow simulation is essential for flood forecasting, water resource management, and water quality protection. However, process-based and data-driven models often suffer from limitations such as systematic bias, limited robustnes... read more

Deep learning-based reconstruction for 5.0T magnetic resonance imaging (MRI) in nasopharyngeal carcinoma: comparison of image quality and diagnostic efficacy.

Clinical radiology Apr 19, 2026

AIM: To investigate the effect of deep learning-based reconstruction (DLR) technology on image quality and diagnostic efficacy of 5T magnetic resonance imaging (MRI) in nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: This prospective study inc... read more

The role of artificial intelligence-enhanced multispectral imaging in burn surgery decision-making: A patient-centered mixed-methods service evaluation.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS Apr 19, 2026

BACKGROUND: Artificial intelligence (AI) supported imaging is increasingly used across plastic surgery, including burn care, to assist with assessment and surgical planning. Most of the existing literature has focused on accuracy and technical perfor... read more

Interpretable machine learning-augmented quantitative targeted flavoromics for quality grade prediction of Jiangxiangxing baijiu.

Food research international (Ottawa, Ont.) Apr 19, 2026

The quality of Jiangxiangxing (JXX) baijiu depends on its sensory and flavor characteristics, which traditional methods struggle to evaluate accurately. This study employed quantitative targeted flavoromics and interpretable machine learning (ML) to ... read more

Artificial Intelligence Medical Compendium