Researchers used machine learning models to predict preterm birth risk, identifying linear SVMs as the most accurate, with ...

Compared to other ML regression techniques, advantages are that it can handle both large and small datasets, and the results ...

Khatun, N. (2025) Evaluations of Machine Learning Algorithms Using Simulation Study. Open Journal of Statistics, 15, 41-52.

For the Preeclampsia Integrated Estimate of RiSk Machine Learning model, consecutive performance deteriorates over time.

There are numerous factors that affect the cost of a cervical disc replacement, and researchers used a machine learning model to analyze key variables for a stu ...

Glaucoma is characterised by progressive vision loss due to retinal ganglion cell deterioration, leading to gradual visual field (VF) impairment. The standard VF test may be impractical in some cases, ...

Many conventional computer architectures are ill-equipped to meet the computational demands of machine learning-based models. In recent years, some engineers have thus been trying to design ...

To develop a machine learning (ML) algorithm to predict survival probabilities for patients with epithelial ovarian cancer (EOC).Data were obtained from the SEER database for women diagnosed with EOC ...

Bob Dylan famously asked, “How many roads must a man walk down, before you can call him a man?”. The power of the question is ...

The mathematics behind artificial intelligence (AI) and machine learning (ML) rely on linear algebra, calculus, probability, ...