The rapid progress in artificial intelligence (AI) and machine learning (ML) has raised hopes for a more personalized, efficient, and effective approach to the management of diabetes mellitus and its cardiovasc
Machine learning techniques trained on historical patient records have demonstrated considerable potential to predict critical events in different medical domains (for example, circulatory failure, diabetes and cardiovascular disorders)11,12,13,14,15. In the mental health domain, prediction algorithms have ...
Here, we develop a machine learning-assisted genetic priority score, which we call ML-GPS, that incorporates genetic associations with predicted disease phenotypes to enhance target discovery. First, we construct gradient boosting models to predict 112 chronic disease phecodes in the UK Biobank and ...
3. Diabetes Dataset 4. Digits Dataset 5. Wine Recognition Dataset 6. Breast Cancer Dataset In this tutorial, we will employ the Iris Plants Dataset with the assistance of Scikit-learn. The dataset comprises parameters such as sepal length, sepal width, petal length, and petal width, which col...
Summary: Efficient management of chronic diseases is critical in modern health care. We consider diabetes mellitus, and our ongoing goal is to examine how machine learning can deliver information for clinical efficiency. The challenge is to aggregate highly heterogeneous sources including demographics, ...
Automated Machine Learning for Healthcare Chapter © 2025 Towards more Accessible Precision Medicine: Building a more Transferable Machine Learning Model to Support Prognostic Decisions for Micro- and Macrovascular Complications of Type 2 Diabetes Mellitus Article 17 May 2019 Machine learning in preci...
Clinical pathway Machine learning Data-driven approach Patient data 1. Introduction Clinical pathways (CPs) are structured multi-disciplinary plans delineating sequences of events guiding the management of patients with specific clinical conditions [1], [2]. These events can be observations of particular...
coaches that can provide personalized diet, exercise, and wellness advice, especially for chronic disease management, tailored to individual patient data. At some point group appointments allow consulting low-income patients with similar conditions (heart diseases, diabetes). AI coaches are the next ...
Adipogenesis is intricately linked to the onset and progression of muscle aging; however, the relevant biomarkers remain unclear. This study sought to identify key genes associated with adipogenesis in the context of muscle aging. Firstly, gene expressio
Through the design and validation of a high-performance model to predict diabetes complications adverse outcomes at the population level, we demonstrate the potential of machine learning and administrative health data to inform health planning and healthcare resource allocation for diabetes management....