Machine learning model predicts serious transplant complications months before symptoms appear

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...
AHA/ASA Journals

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...
Scientific Research Publishing

Accuracy and Response Speed of Eye Center Annotation Using Eye Movement Models: Validating the Effectiveness of Eyesight Detection ()

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the ...

AI can predict success of hip operations

Artificial intelligence can help to predict how well patients with hip osteoarthritis will be able to walk again after an ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
IEEE

Study and Observation of the Variation of Accuracies of KNN, SVM, LMNN, ENN Algorithms on Eleven Different Datasets from UCI Machine Learning Repository

Abstract: Machine learning qualifies computers to assimilate with data, without being solely programmed [1, 2]. Machine learning can be classified as supervised and unsupervised learning. In ...
IEEE

Design of a Generic Fault Diagnosis Model for Electrical Distribution Networks Using a Support Vector Machine (SVM) Algorithm

Abstract: This article presents the design and implementation of a generic model for fault diagnosis in electrical distribution networks, based on the Support Vector Machine (SVM) algorithm. The ...
Frontiers

Intelligent optimization of slope step parameters in open pit mines containing weak interbedded layers based on machine learning and multi-objective optimization methods

1 Faculty of Land Resources Engineering, Kunming University of Science and Technology Kunming, Kunming, China 2 Pangang Group Mining Company Limited Panzhihua, Panzhihua, Sichuan, China The stability ...
GitHub

Prediction of stroke using Support Vector Machine (SVM) and Decision Tree (DTREE).

The stroke deprives person's brain of oxygen and nutrients, which can cause brain cells to die. Numerous works have been carried out for predicting various diseases by comparing the performance of ...
Assembly Mag

Traditional Machine Learning for Practical Machine Vision: It’s Been There All Along

Powerful and practical machine learning tools for machine vision applications are already available to everyone, even if you’re not a data scientist. It might come as a bit of a surprise, but machine ...