The Journal of international medical research
May 22, 2015
OBJECTIVES: To develop a Web-based tool to draw attention to patients positive for human papillomavirus (HPV) who have a high risk of progression to cervical cancer, in order to increase compliance with follow-up examinations and facilitate good doct...
Journal of environmental sciences (China)
Apr 20, 2015
Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentratio...
Environmental science and pollution research international
Mar 18, 2015
This research aimed at developing comprehensive assessments of physicochemical quality of groundwater for drinking and irrigation purposes at Dalcheon in Ulsan City, Korea. The mean concentration of major ions represented as follows: Ca (94.3 mg/L) >...
Chlorophyll-a (Chl-a) is a direct indicator used to evaluate the ecological state of a waterbody, such as algal blooms that degrade the water quality in lakes, reservoirs and estuaries. In this study, artificial neural network (ANN) and support vecto...
The rise in cyanobacterial harmful algal blooms (CHABs), driven by eutrophication and climate change, necessitates understanding cyanotoxin conditions to mitigate risks. However, limited studies have explored the influencing factors of cyanobacterial...
OBJECTIVE: To develop a multimodal model to predict chronic kidney disease (CKD) in patients with type 2 diabetes mellitus (T2DM), given the limited research on this integrative approach.
Journal of the American Medical Informatics Association : JAMIA
Aug 1, 2025
OBJECTIVES: This study develops and validates the confidence-linked and uncertainty-based staged (CLUES) framework by integrating large language models (LLMs) with uncertainty quantification to assist manual chart review while ensuring reliability th...
PURPOSE: Large language models (LLMs) have shown potential in medicine, transforming patient education, clinical decision support, and medical research. However, the effectiveness of LLMs in providing accurate medical information, particularly in non...
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
Accurate forecasting of ground-level ozone (O) is essential for assessing its public health and socioeconomic impacts. This study evaluates the performance of three deep learning models-Deep Convolutional Neural Networks (Deep-CNN), Long Short-Term M...
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