Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …

Diabetes Mellitus is a severe, chronic disease that occurs when blood glucose levels rise
above certain limits. Over the last years, machine and deep learning techniques have been …

Robustness to distribution shift has become a growing concern for text and image models as
they transition from research subjects to deployment in the real world. However, high-quality …

Background Diabetics has become a serious public health burden in China. Multiple
complications appear with the progression of diabetics pose a serious threat to the quality of …

Type 2 diabetes has recently acquired the status of an epidemic silent killer, though it is non-
communicable. There are two main reasons behind this perception of the disease. First, a …

learning algorithms. In this paper, we review the classification algorithms used in the health
care system (chronic diseases) and present the neural network-based Ensemble learning …

Data mining (DM) is an instrument of pattern detection and retrieval of knowledge from a
large quantity of data. Many robust early detection services and other health-related …

Objectives We aimed to review the literature regarding the use of machine learning to
predict chronic diseases. Study design This was a systematic review. Methods The searches …

Early identification of individuals at high risk of diabetes is crucial for implementing early
intervention strategies. However, algorithms specific to elderly Chinese adults are lacking …

Abstract Purpose of Review Machine learning approaches—which seek to predict outcomes
or classify patient features by recognizing patterns in large datasets—are increasingly …