Primary Care

Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular age are limited, as they rely on a limited set of histological markers and lack predictive power. Here, we implement GERAS (GEnetic Reference for Age...

The Healthy Children, Strong Families 2 (HCSF2) Randomized Controlled Trial Improved Healthy Behaviors in American Indian Families with Young Children.

BACKGROUND: American Indian (AI) families experience a disproportionate risk of obesity due to a number of complex reasons, including poverty, historic trauma, rural isolation or urban loss of community connections, lack of access to healthy foods and physical activity opportunities, and high stress. Home-based obesity prevention interventions are lacking for these families.

Individual and Combined Relationship between Reduced eGFR and/or Increased Urinary Albumin Excretion Rate with Mortality Risk among Insulin-Treated Patients with Type 2 Diabetes in Routine Practice.

BACKGROUND: A low estimated glomerular filtration rate (eGFR) and an increased urinary albumin-to-creatinine ratio (ACR) are well-recognised prognosti...

Blood Sugar Level Indication Through Chewing and Swallowing from Acoustic MEMS Sensor and Deep Learning Algorithm for Diabetic Management.

Diabetes, a metabolic disorder due to high blood glycemic index in the human body. The glycemic index varies in the human of improper diet and eating ...

A Study of Machine-Learning Classifiers for Hypertension Based on Radial Pulse Wave.

OBJECTIVE: In this study, machine learning was utilized to classify and predict pulse wave of hypertensive group and healthy group and assess the risk...

The association between serum uric acid to creatinine ratio and renal disease progression in type 2 diabetic patients in Chinese communities.

AIMS: Serum uric acid (UA) increases in patients with kidney disease due to the impaired UA clearance. The present study sought to evaluate the associ...

Deep Learning-Based Algorithms in Screening of Diabetic Retinopathy: A Systematic Review of Diagnostic Performance.

TOPIC: Diagnostic performance of deep learning-based algorithms in screening patients with diabetes for diabetic retinopathy (DR). The algorithms were...

Circulating betatrophin in relation to metabolic, inflammatory parameters, and oxidative stress in patients with type 2 diabetes mellitus.

AIMS: Recently, it was suggested that betatrophin has a role in controlling pancreatic β cell proliferation and lipid metabolism, however, its role in...

Serum adipocytokines are associated with microalbuminuria in patients with type 1 diabetes and incipient chronic complications.

AIMS: Recent studies have implicated possible contribution of adipocytokines in development and progression of microvascular complications in patients...

Ensemble machine learning prediction of posttraumatic stress disorder screening status after emergency room hospitalization.

Posttraumatic stress disorder (PTSD) develops in a substantial minority of emergency room admits. Inexpensive and accurate person-level assessment of ...

Photoplethysmography and Deep Learning: Enhancing Hypertension Risk Stratification.

Blood pressure is a basic physiological parameter in the cardiovascular circulatory system. Long-term abnormal blood pressure will lead to various car...

Prevalence of Diabetic Retinopathy and Associated Mortality Among Diabetic Adults With and Without Chronic Kidney Disease.

PURPOSE: To estimate prevalence and severity of diabetic retinopathy (DR) among U.S. adults with diabetes and with or without chronic kidney disease (...

SCREEN-DR: Collaborative platform for diabetic retinopathy.

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is the most prevalent microvascular complication of diabetes mellitus and can lead to irreversible...

Identifying in Palliative Care Consultations: A Tandem Machine-Learning and Human Coding Method.

Systematic measurement of conversational features in the natural clinical setting is essential to better understand, disseminate, and incentivize hig...

Stacked classifiers for individualized prediction of glycemic control following initiation of metformin therapy in type 2 diabetes.

OBJECTIVE: Metformin is the preferred first-line medication for management of type 2 diabetes and prediabetes. However, over a third of patients exper...

Protein Family-Specific Models Using Deep Neural Networks and Transfer Learning Improve Virtual Screening and Highlight the Need for More Data.

Machine learning has shown enormous potential for computer-aided drug discovery. Here we show how modern convolutional neural networks (CNNs) can be a...

An improved support vector machine-based diabetic readmission prediction.

BACKGROUND AND OBJECTIVE: In healthcare systems, the cost of unplanned readmission accounts for a large proportion of total hospital payment. Hospital...

Obesity and chronic kidney disease progression-the role of a new adipocytokine: C1q/tumour necrosis factor-related protein-1.

BACKGROUND: Obesity is a risk factor for incident chronic kidney disease (CKD) in the general population. C1q/tumour necrosis factor-related protein 1...

Application of electronic trigger tools to identify targets for improving diagnostic safety.

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify errors, high-risk situations, and adverse events....

Can nurses remain relevant in a technologically advanced future?

Technological breakthroughs occur at an ever-increasing rate thereby revolutionizing human health and wellness care. Technological advancements have d...