One of the developments in machine learning is the technology that has been used for disease prediction in many fields around the world, including the healthcare industry. Analysis has been attempted to classify the most influential heart disease causes and to reliably predict the overall risk ...
By comparing the AI-generated blood flow results with the health outcomes of each patient, the team found that the patients with reduced blood flow were more likely to have adverse health outcomes including death, heart attack, stroke and heart failure. The AI technique was therefore shown for ...
"Current standard prediction models like the ACC are based on eight risk factors including age, cholesterol level and blood pressure but are too simplistic to account for other factors like medications, multiple disease conditions, and other non-traditional biomarkers. These AI algorithms have the pot...
Early detection of atrial fibrillation can reduce the risk of stroke and heart failure, but screening people for the condition has been historically challenging
27 have proposed a framework of a hybrid system for the identification of cardiac disease, using machine learning, and attained an accuracy of 86.0%. Similarly, Mohan et al.28 have proposed another intelligent system that integrates RF with a linear model for the prediction of heart disease and...
It may sound like a sappy sentiment from a Hallmark card. Essentially though, that's what researchers at Google did in applying artificial intelligence to predict something deadly serious: the likelihood that a patient will suffer a heart attack or stroke. The researchers made such determinations ...
The results showed the AI-driven system (when incorporated with age, sex, smoking status and medical history) could deliver 10-year risk scores for stroke and heart disease equal to one of the most commonly used diagnostic tools called the Framingham Risk Score (FRS). Because FRS diagnostics ...
Therefore, we describe the case of an 86-year-old woman with dyspnea and cTn-elevation within the first days following acute ischemic stroke and discuss potential differential diagnoses and diagnostic dilemmas.Henke, KatrinGalimanis, Aikaterini
ECG-based AI models, like the one in this repository, can assist in the prediction of these arrhythmias, enabling prompt diagnosis and management. Preparing MIMIC-Ext dataset The MIMIC-IV-ECG dataset, a subset of the MIMIC-IV Clinical Database, contains approximately 800,000 diagnostic ECGs ...
Every year, over 100,000 people die from a heart attack or related stroke in the UK alone, and heart disease and stroke remain the two biggest overall causes of death worldwide. Yet there is no method that allows for early detection of a potentially fatal build-up of plaque that could ...