Primary Care

Unique Views on Obesity-Related Behaviors and Environments: Research Using Still and Video Images.

OBJECTIVES: To document challenges to and benefits from research involving the use of images by capturing examples of such research to assess physical activity- or nutrition-related behaviors and/or environments.

[Robot-assisted vs laparoscopic gastric bypass : First experiences with the DaVinci system in bariatric surgery].

Conventional laparoscopy is the gold standard in bariatric surgery. Internationally, robot-assisted surgery is gaining in importance. Up to now there are only few reports from Germany on the use of the system in bariatric surgery. Since January 2017 we have been performing robot-assisted gastric bypass surgery. It remains unclear whether the use of the robotic system has advantages over the well-e...

Predictive markers of depression in hypertension.

Hypertension and depression, as 2 major public health issues, are closely related. For patients having hypertension, in particular, depression is a ri...

WDL-RF: predicting bioactivities of ligand molecules acting with G protein-coupled receptors by combining weighted deep learning and random forest.

MOTIVATION: Precise assessment of ligand bioactivities (including IC50, EC50, Ki, Kd, etc.) is essential for virtual screening and lead compound ident...

Discriminating early- and late-stage cancers using multiple kernel learning on gene sets.

MOTIVATION: Identifying molecular mechanisms that drive cancers from early to late stages is highly important to develop new preventive and therapeuti...

Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation.

Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio (CDR) plays an important role in the screening and dia...

Knowledge-driven dictionaries for sparse representation of continuous glucose monitoring signals.

Continuous glucose monitoring (CGM) of patients with diabetes allows the effective management of the disease and reduces the risk of hypoglycemic or h...

A New and Improved Method for Automated Screening of Age-Related Macular Degeneration Using Ensemble Deep Neural Networks.

In this paper, we provide a new framework on deep learning based automated screening method for finding individuals at risk of developing Age-related ...

Multi-Cell Multi-Task Convolutional Neural Networks for Diabetic Retinopathy Grading.

Diabetic Retinopathy (DR) is a non-negligible eye disease among patients with Diabetes Mellitus, and automatic retinal image analysis algorithm for th...

Personalised meal eating behaviour analysis via semi-supervised learning.

Automated monitoring and analysis of eating behaviour patterns, i.e., "how one eats", has recently received much attention by the research community, ...

The New Possibilities from "Big Data" to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis.

PURPOSE OF REVIEW: To review current practices and technologies within the scope of "Big Data" that can further our understanding of diabetes mellitus...

A Preventive Model for Muscle Injuries: A Novel Approach based on Learning Algorithms.

INTRODUCTION: The application of contemporary statistical approaches coming from Machine Learning and Data Mining environments to build more robust pr...

Using Unsupervised Machine Learning to Identify Subgroups Among Home Health Patients With Heart Failure Using Telehealth.

This study explored the use of unsupervised machine learning to identify subgroups of patients with heart failure who used telehealth services in the ...

[Technical advancement in surgical treatment of portal hypertension].

Recently, there have been many developments and improvements in portal hypertension surgery, but there are still many controversies regarding the surg...

Automatic Adaptation of Basal Insulin Using Sensor-Augmented Pump Therapy.

BACKGROUND: People with insulin-dependent diabetes rely on an intensified insulin regimen. Despite several guidelines, they are usually impractical an...

Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

BACKGROUND: In type 1 diabetes mellitus (T1DM), patients play an active role in their own care and need to have the knowledge to adapt decisions to th...

Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions.

Heavy smokers undergoing screening with low-dose chest CT are affected by cardiovascular disease as much as by lung cancer. Low-dose chest CT scans ac...

Building Bayesian Networks from Causal Rules.

Bayesian Networks (BNs) are often used for designing diagnosis decision support systems. They are a well-established method for reasoning under uncert...

Evaluating the Impact of Incorrect Diabetes Coding on the Performance of Multivariable Prediction Models.

The use of electronic health records for risk prediction models requires a sufficient quality of input data to ensure patient safety. The aim of our s...

Big-Data Analysis, Cluster Analysis, and Machine-Learning Approaches.

Medicine will experience many changes in the coming years because the so-called "medicine of the future" will be increasingly proactive, featuring fou...