Machine LearningDecision Tree (DT)Logistic Regression (LR)Support Vector Machine (SVM)k Nearest Neighbors (kNN)Type 2 diabetes is a metabolic disease that causes abnormal high levels of glucose in the blood. The pancreas is healthy, but the body doesn't respond properly to its own insulin. ...
Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to develop a machine learning model that can accurately ...
Use MATLAB to develop, test, and generate embedded code for image analysis and machine learning algorithms Results Accuracy requirements exceeded Project completion time halved Optimized system delivered The Grifols MDmulticard. Knowing the blood antigen typing of ...
With the development of data mining, machine learning offers opportunities to improve discrimination by analyzing complex interactions among massive variables. To test the ability of machine learning algorithms for predicting risk of type 2 diabetes mellitus (T2DM) in a rural Chinese population, we focu...
Here are some of my implementations of some commonly used machine learning algorithms in C++, python, and typescript. Table of contents Linear Regression Linear Regression This is an implementation of simple Linear Regression in C++. Formula
The aim of this paper is to discuss the class of leap-frog-type neural learning algorithms having the unitary group of matrices as parameter space. In the discussed framework, each step of a learning algorithm computes as an unconstrained learning step followed by a projection step. The present...
et al. Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms. Lancet Digit. Health 2, e526–e536 (2020). Article Google Scholar Sabanayagam, C. et al. A deep learning algorithm to detect chronic kidney disease from retinal photographs...
Poseidon is a python-based application that leverages software defined networks (SDN) to acquire and then feed network traffic to a number of machine learning techniques. The machine learning algorithms classify and predict the type of device. - jentino
There is hardly any work in the technical ground to justify the claims of the psychologists in terms of machine learning (ML) algorithms to decode the emotional changes of the gamers in real-time. The proposed work is a novel one proposed by the authors in terms of mainly applicability of ...
A number of unsupervised machine-learning algorithms have been developed, including classical machine-learning-based methods such as Seurat7 and Scanpy8, and newly published deep learning-based methods, such as scDHA9 and CLEAR10. However, these methods can be time-consuming and burdensome. For ...