[HTML][HTML] Machine learning and data mining methods in diabetes research
The remarkable advances in biotechnology and health sciences have led to a significant
production of data, such as high throughput genetic data and clinical information, generated …
production of data, such as high throughput genetic data and clinical information, generated …
Precision prognostics for the development of complications in diabetes
C Schiborn, MB Schulze - Diabetologia, 2022 - Springer
Individuals with diabetes face higher risks for macro-and microvascular complications than
their non-diabetic counterparts. The concept of precision medicine in diabetes aims to …
their non-diabetic counterparts. The concept of precision medicine in diabetes aims to …
Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts
This study aimed to develop and validate a machine learning (ML) model tailored to the
Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for …
Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for …
Exercise and type 1 diabetes
X Lu, C Zhao - Physical Exercise for Human Health, 2020 - Springer
Diabetes mellitus (DM) is the most common endocrine and metabolic disease caused by
absolute or insufficient insulin secretion. Under the context of an aging population …
absolute or insufficient insulin secretion. Under the context of an aging population …
Precision prognostics for cardiovascular disease in type 2 diabetes: a systematic review and meta-analysis
Background Precision medicine has the potential to improve cardiovascular disease (CVD)
risk prediction in individuals with Type 2 diabetes (T2D). Methods We conducted a …
risk prediction in individuals with Type 2 diabetes (T2D). Methods We conducted a …
Artificial intelligence based prediction models for individuals at risk of multiple diabetic complications: A systematic review of the literature
L Gosak, K Martinović, M Lorber… - Journal of nursing …, 2022 - Wiley Online Library
Aim The aim of this review is to examine the effectiveness of artificial intelligence in
predicting multimorbid diabetes‐related complications. Background In diabetic patients …
predicting multimorbid diabetes‐related complications. Background In diabetic patients …
[HTML][HTML] Temporal patterns selection for All-Cause Mortality prediction in T2D with ANNs
P Novitski, CM Cohen, A Karasik, G Hodik… - Journal of Biomedical …, 2022 - Elsevier
Mortality prevention in T2D elderly population having Chronic Kidney Disease (CKD) may
be possible thorough risk assessment and predictive modeling. In this study we investigate …
be possible thorough risk assessment and predictive modeling. In this study we investigate …
Scalable healthcare assessment for diabetic patients using deep learning on multiple GPUs
The large-scale parallel computation that became available on the new generation of
graphics processing units (GPUs) and on cloud-based services can be exploited for use in …
graphics processing units (GPUs) and on cloud-based services can be exploited for use in …
Machine learning models for prediction of diabetic microvascular complications
S Kanbour, C Harris, B Lalani… - Journal of diabetes …, 2024 - journals.sagepub.com
Importance and Aims: Diabetic microvascular complications significantly impact morbidity
and mortality. This review focuses on machine learning/artificial intelligence (ML/AI) in …
and mortality. This review focuses on machine learning/artificial intelligence (ML/AI) in …
Development and validation of a risk prediction model for severe hypoglycemia in adult patients with type 2 diabetes: a nationwide population-based cohort study
Purpose There is a scarcity of long-term prediction models for severe hypoglycemia (SH) in
subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and …
subjects with type 2 diabetes mellitus (T2DM). In this study, a model was developed and …