Primary Care

Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal images have emerged as potential noninvasive screening tools for CKD, though their performance may be limited, especially in identifying individuals with p...

Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers.

BACKGROUND: Diabetic foot ulcers (DFUs) are a serious complication of diabetes mellitus that manifests as chronic, non-healing wounds that have a significant impact on patients quality of life. Identifying key molecular targets associated with DFUs could help develop targeted therapies to promote wound healing and prevent further complications. The CXCR4 gene is known to play a key role in cell mi...

CaBind_MCNN: Identifying Potential Calcium Channel Blocker Targets by Predicting Calcium-Binding Sites in Ion Channels and Ion Transporters Using Protein Language Models and Multiscale Feature Extraction.

Calcium ions (Ca) are crucial for various physiological processes, including neurotransmission and cardiac function. Dysregulation of Ca homeostasis c...

Cross-sectional design and protocol for Artificial Intelligence Ready and Equitable Atlas for Diabetes Insights (AI-READI).

INTRODUCTION: Artificial Intelligence Ready and Equitable for Diabetes Insights (AI-READI) is a data collection project on type 2 diabetes mellitus (T...

Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets.

Diabetes Mellitus (DM) is a global health challenge, and accurate early detection is critical for effective management. The study explores the potenti...

Transfer Learning Prediction of Early Exposures and Genetic Risk Score on Adult Obesity in Two Minority Cohorts.

Due to ethnic heterogeneity in genetic architecture, genetic risk score (GRS) constructed within the European population generally possesses poor port...

GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series.

Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with type 1 or 2 diabetes, thereby red...

REMED-T2D: A robust ensemble learning model for early detection of type 2 diabetes using healthcare dataset.

Early diagnosis and timely treatment of diabetes are critical for effective disease management and the prevention of complications. Undiagnosed diabet...

Estimation of Hematocrit Volume Using Blood Glucose Concentration through Extreme Gradient Boosting Regressor Machine Learning Model.

Lifestyle diseases such as cardiovascular disorders, diabetes, etc. affect the physiological metabolism and become chronic upon negligence. Diabetes i...

Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study.

BACKGROUND: Modern lifestyle risk factors, like physical inactivity and poor nutrition, contribute to rising rates of obesity and chronic diseases lik...

Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements.

Chronic kidney disease (CKD) is a global health concern with early detection playing a pivotal role in effective management. Machine learning models d...

Advances in the application of human-machine collaboration in healthcare: insights from China.

In the context of the technological revolution and the digital intelligence era, the contradiction between the rising incidence of diseases and the un...

Machine learning prediction of obesity-associated gut microbiota: identifying as a potential therapeutic target.

BACKGROUND: The rising prevalence of obesity and related metabolic disorders highlights the urgent need for innovative research approaches. Utilizing ...

Demystifying Infusion Pumps: Design of a Cost-Effective Platform for Education and Innovation.

INTRODUCTION: This article presents a cost-effective, modular infusion platform to help diabetes specialists customize and understand infusion pump me...

Modeling the latent impacts of extreme floods on indoor mold spores in residential buildings: Application of machine learning algorithms.

Floods can severely impact the economy, environment and society. These impacts can be direct and indirect. Past research has focused more on the forme...

Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study.

BACKGROUND: Emerging evidence suggests that artificial intelligence (AI) can increase cancer detection in mammography screening while reducing screen-...

Development and Evaluation of a Deep Learning-Based Pulmonary Hypertension Screening Algorithm Using a Digital Stethoscope.

BACKGROUND: Despite the poor outcomes related to the presence of pulmonary hypertension, it often goes undiagnosed in part because of low suspicion an...

Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases.

Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intel...

Identification of hub biomarkers in liver post-metabolic and bariatric surgery using comprehensive machine learning (experimental studies).

BACKGROUND: The global prevalence of non-alcoholic fatty liver disease (NAFLD) is approximately 30%, and the condition can progress to non-alcoholic s...

Artificial Intelligence in Ischemic Heart Disease Prevention.

PURPOSE OF REVIEW: This review discusses the transformative potential of artificial intelligence (AI) in ischemic heart disease (IHD) prevention. It e...