Predicting Cardiovascular Events by Machine Learning

Cardiovascular Event Prediction by Machine Learning

Obesity, risk factors, and predicting cardiovascular events.

APubMed search in March 2005 with the key word “metabolic syndrome” yielded 10 000 references. Past labels for this disorder include “syndrome X,” “deadly quartet,” and “cardiovascular dysmetabolic syndrome.”1–3 What is driving the current increased interest in the metabolic syndrome? Possibly the impetus comes from the dramatic increases in obesity in the United States and other developed coun...

Predicting Phospholipidosis Using Machine Learning

Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably identified by electron microscopy of cells revealing the presence of lamellar inclusion bodies. The development of phospholipidosis can cause a delay in the drug development process, and the impor...

Diagnosing Breast Cancer by Machine Learning

Background and Aim: Cancer and in particular Breast cancer are among the diseases that have the highest mortality rate in Iran after heart disease. The accurate prognosis for Breast cancer is important, and the presence of various symptoms and features of this disease makes it difficult for doctors to diagnose. This study aimed to identify the factors affecting Breast cancer, modeling and ultim...

Predicting mutagenicity of aromatic amines by various machine learning approaches.

Aromatic amines are prevalently used in a wide variety of industries and are ubiquitous in foods and environment. Many of this class of compounds are potentially mutagenic or even carcinogenic, and the assessment and prediction of their mutagenicity are of practical importance because mutagenicity and carcinogenicity are toxicological end points that play major roles in the genesis of cancer an...