Anemia

Increasing tendency of urine protein is a risk factor for rapid eGFR decline in patients with CKD: A machine learning-based prediction model by using a big database.

Artificial intelligence is increasingly being adopted in medical fields to predict various outcomes. In particular, chronic kidney disease (CKD) is problematic because it often progresses to end-stage kidney disease. However, the trajectories of kidney function depend on individual patients. In this study, we propose a machine learning-based model to predict the rapid decline in kidney function am...

Quantum machine learning using atom-in-molecule-based fragments selected on the fly.

First-principles-based exploration of chemical space deepens our understanding of chemistry and might help with the design of new molecules, materials or experiments. Due to the computational cost of quantum chemistry methods and the immense number of theoretically possible stable compounds, comprehensive in silico screening remains prohibitive. To overcome this challenge, we combine atom-in-molec...

Efficient and Effective Training of COVID-19 Classification Networks With Self-Supervised Dual-Track Learning to Rank.

Coronavirus Disease 2019 (COVID-19) has rapidly spread worldwide since first reported. Timely diagnosis of COVID-19 is crucial both for disease contro...

Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics.

Following prolonged swimming, cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for and here we suggest that in...

A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data.

The human foot is easily deformed owing to the innate form of the foot or an incorrect walking posture. Foot deformations not only pose a threat to fo...

Esophagus segmentation from planning CT images using an atlas-based deep learning approach.

BACKGROUND AND OBJECTIVE: One of the main steps in the planning of radiotherapy (RT) is the segmentation of organs at risk (OARs) in Computed Tomograp...

Long-Term Course of Haemoglobin and Ferritin Values in High-Frequency Donors of Whole Blood and Double Erythrocyte Apheresis.

BACKGROUND: High-intensity donation is a risk factor for iron deficiency in blood donors. Interdonation intervals for whole blood (WB) donation and do...

ADR-Net: Context extraction network based on M-Net for medical image segmentation.

PURPOSE: Medical image segmentation is an essential component of medical image analysis. Accurate segmentation can assist doctors in diagnosis and rel...

Is there any association between low level of serum nesfatin-1 and fibromyalgia syndrome?

OBJECTIVES: This study aims to investigate the relationship between serum level of nesfatin-1 and fibromyalgia syndrome (FMS) clinical parameters such...

Accelerating massively parallel hemodynamic models of coarctation of the aorta using neural networks.

Comorbidities such as anemia or hypertension and physiological factors related to exertion can influence a patient's hemodynamics and increase the sev...

Adaptive robot mediated upper limb training using electromyogram-based muscle fatigue indicators.

Studies on improving the adaptability of upper limb rehabilitation training do not often consider the implications of muscle fatigue sufficiently. In ...

Parametric investigation of the effects of load level on fatigue crack growth in trabecular bone based on artificial neural network computation.

This study reports the development of an artificial neural network computation model to predict the accumulation of crack density and crack length in ...

EEG Signal and Feature Interaction Modeling-Based Eye Behavior Prediction Research.

In recent years, with the development of brain science and biomedical engineering, as well as the rapid development of electroencephalogram (EEG) sign...

A generalized predictive control for remote cardiovascular surgical systems.

Robot-assisted cardiovascular surgery is used to avoid surgeon suffering from X-ray radiation and relieve fatigue caused by long-time standing wearing...

Flexoskeleton Printing Enables Versatile Fabrication of Hybrid Soft and Rigid Robots.

One of the many secrets to the success and prevalence of insects is their versatile, robust, and complex exoskeleton morphology. A fundamental challen...

Deep learning approaches for sleep disorder prediction in an asthma cohort.

OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower p...

Early prediction of circulatory failure in the intensive care unit using machine learning.

Intensive-care clinicians are presented with large quantities of measurements from multiple monitoring systems. The limited ability of humans to proce...

A review of methods for achieving upper limb movement following spinal cord injury through hybrid muscle stimulation and robotic assistance.

Individuals with tetraplegia, typically attributed to spinal cord injuries (SCI) at the cervical level, experience significant health care costs and l...

Latent Phase Identification of High-Frequency Micro-Scale Gamma Spike Transients in the Hypoxic Ischemic EEG of Preterm Fetal Sheep Using Spectral Analysis and Fuzzy Classifiers.

Premature babies are at high risk of serious neurodevelopmental disabilities, which in many cases are related to perinatal hypoxic-ischemic encephalop...

Control of Functional Electrical Stimulation Systems Using Simultaneous Pulse Width, Amplitude, and Frequency Modulations.

BACKGROUND: One significant challenge of developing a controller for functional electrical stimulation systems is the time-variant nonlinear dynamics ...