More accurate and individualized health predictions will allow for preventative factors to be implemented well in advance.
Discover how artificial intelligence is transforming influenza vaccine development, accelerating timelines and improving ...
Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
While the potential benefits of AI in obesity prevention are substantial, the study devotes significant attention to ...
There was an error while loading. Please reload this page. This project focuses on developing and evaluating machine learning models to classify individuals into ...
Introduction Frailty is a common condition in older adults with diabetes, which significantly increases the risk of adverse health outcomes. Early identification of frailty in this population is ...
Background: Early identification of Type 1 Diabetes Mellitus (T1DM) in pediatric populations is crucial for implementing timely interventions and improving long-term outcomes. Peripheral blood ...
ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...
Background: Machine learning technology that uses available clinical data to predict diabetic retinopathy (DR) can be highly valuable in medical settings where fundus cameras are not accessible.
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