Foundation models (FMs), large neural networks pretrained on extensive and diverse datasets, have revolutionized artificial intelligence and demonstrated significant promise in medical imaging by enabling robust performance with limited labeled data.... read more
The aim of this study is to develop an innovative method of machine learning combining metabolomic and radiomic analyses for identifying biomarkers to distinguish diabetic retinopathy (DR) patients, non-retinopathy diabetic (NDR) patients and healthy... read more
Journal of pain and symptom management
Apr 12, 2026
CONTEXT: Chatbots are increasingly used by the public, but their performance in answering questions about complex health topics, such as cannabis, is unknown. OBJECTIVES: To evaluate responses of three popular chatbots regarding cannabis and its use ... read more
Rapid industrialization, urbanization, and intensive agriculture have worsened river basin water pollution globally, including in China. Traditional water pollution monitoring, though widely used, is time-consuming, limited in coverage, and lacking i... read more
UNLABELLED: Anaerobic co-digestion of food waste and paper mill wastewater offers a sustainable waste-to-energy solution, but performance instability limits its efficiency. While biochar (BC) is a promising additive, the specific surface area (SSA) r... read more
Critical reviews in oncology/hematology
Apr 12, 2026
Personalized cancer vaccines have re-emerged as a promising strategy in precision immunotherapy, driven by advances in tumor sequencing, neoantigen identification, and vaccine delivery platforms. Early-phase clinical trials have consistently demonstr... read more
A DFT-explainable machine-learning (DFT-XML) strategy integrated with an active learning mechanism was proposed and validated to connect quantum-level molecular properties with macroscopic environmental behaviors of halogenated polycyclic aromatic hy... read more
The lack of rapid, user-friendly methods for alternariol (AOH), a prevalent emerging mycotoxin, presents a considerable analytical challenge. This work introduces an integrated sensing strategy advancing from classical homogeneous liquid-phase detect... read more
Digital twin technology has emerged as a transformative innovation in healthcare, offering virtual replicas of physical entities at patient-level, equipment-level, and departmental-level that enable real-time monitoring, prediction, and optimisation.... read more
Pathological diagnosis is highly reliant on image analysis, where Regions of Interest (ROIs) serve as the primary basis for diagnostic evidence, while whole-slide image (WSI)-level tasks primarily capture aggregated patterns. To extract these critica... read more
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