Despite major advances in genetic testing for breast cancer risk prediction, death rates remain disproportionately high among ...
At a moment when the AI industry is obsessed with bigger models and higher scores, Professor Ganna Pogrebna opened the ...
Although large language models (LLMs) have the potential to transform biomedical research, their ability to reason accurately across complex, data-rich domains remains unproven. To address this ...
A new peer-reviewed study published in the journal Algorithms signals a major shift in how humanitarian logistics can be ...
Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
The ChatGPT o1 Pro can accurately identify glaucoma from visual field and optical coherence tomography data, a study shows.
In a recent study published in the journal Scientific Reports, researchers developed a pattern neural network (PNN) model that combined a novel measure of total antioxidant status with traditional ...
Abstract: The abstract is an imperfect defect detection model meant to classify various defects of castings. It presents an excellent precision, recall, and $\mathbf{F 1}$-score of six classes of ...
ABSTRACT: This paper aims to investigate the effectiveness of logistic regression and discriminant analysis in predicting diabetes in patients using a diabetes dataset. Additionally, the paper ...
Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...
Classification of gas wells is an important part of optimizing development strategies and increasing the recovery. The original classification standard of gas wells in the Sulige gas field has weak ...
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