AIMC Topic: Diabetes Mellitus
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A deep neural network prediction method for diabetes based on Kendall's correlation coefficient and attention mechanism.
PloS one
Jul 2, 2024
Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels. It may affect various organs and tissues, and even lead to life-threatening complications. Accurate prediction of diabetes can significantly reduce its incid...
A machine learning tool for identifying patients with newly diagnosed diabetes in primary care.
Primary care diabetes
Jun 28, 2024
BACKGROUND AND AIM: It is crucial to identify a diabetes diagnosis early. Create a predictive model utilizing machine learning (ML) to identify new cases of diabetes in primary health care (PHC).
Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar.
International journal of environmental research and public health
Jun 27, 2024
Raised blood sugar (hyperglycemia) is considered a strong indicator of prediabetes or diabetes mellitus. Diabetes mellitus is one of the most common non-communicable diseases (NCDs) affecting the adult population. Recently, the prevalence of diabetes...
Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.
Scientific reports
Jun 24, 2024
The study aimed to achieve the following objectives: (1) to perform the fusion of thermal and visible tongue images with various fusion rules of discrete wavelet transform (DWT) to classify diabetes and normal subjects; (2) to obtain the statistical ...
Group-informed attentive framework for enhanced diabetes mellitus progression prediction.
Frontiers in endocrinology
Jun 24, 2024
The increasing prevalence of Diabetes Mellitus (DM) as a global health concern highlights the paramount importance of accurately predicting its progression. This necessity has propelled the use of deep learning's advanced analytical and predictive ca...
Intelligent deep model based on convolutional neural network's and multi-layer perceptron to classify cardiac abnormality in diabetic patients.
Physical and engineering sciences in medicine
Jun 20, 2024
The ECG is a crucial tool in the medical field for recording the heartbeat signal over time, aiding in the identification of various cardiac diseases. Commonly, the interpretation of ECGs necessitates specialized knowledge. However, this paper explor...
Utilizing machine learning algorithms for precise discrimination of glycosuria in fluorescence spectroscopic data.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 1, 2024
Fluorescence spectroscopy coupled with a random forest machine learning algorithm offers a promising non-invasive approach for diagnosing glycosuria, a condition characterized by excess sugar in the urine of diabetic patients. This study investigated...
Explainable hypoglycemia prediction models through dynamic structured grammatical evolution.
Scientific reports
Jun 1, 2024
Effective blood glucose management is crucial for people with diabetes to avoid acute complications. Predicting extreme values accurately and in a timely manner is of vital importance to them. People with diabetes are particularly concerned about suf...
Identification of key genes and biological pathways associated with vascular aging in diabetes based on bioinformatics and machine learning.
Aging
May 27, 2024
Vascular aging exacerbates diabetes-associated vascular damage, a major cause of microvascular and macrovascular complications. This study aimed to elucidate key genes and pathways underlying vascular aging in diabetes using integrated bioinformatics...
Smartphone based wearable sweat glucose sensing device correlated with machine learning for real-time diabetes screening.
Analytica chimica acta
May 21, 2024
BACKGROUND: Diabetes is a significant health threat, with its prevalence and burden increasing worldwide indicating its challenge for global healthcare management. To decrease the disease severity, the diabetic patients are recommended to regularly c...
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