Menopause

Rapid and sensitive mycoplasma detection system using image-based deep learning.

A major concern in the clinical application of cell therapy is the manufacturing cost of cell products, which mainly depends on quality control. The mycoplasma test, an important biological test in cell therapy, takes several weeks to detect a microorganism and is extremely expensive. Furthermore, the manual detection of mycoplasma from images requires high-level expertise. We hypothesized that a ...

Prediction model for the risk of osteoporosis incorporating factors of disease history and living habits in physical examination of population in Chongqing, Southwest China: based on artificial neural network.

BACKGROUND: Osteoporosis is a gradually recognized health problem with risks related to disease history and living habits. This study aims to establish the optimal prediction model by comparing the performance of four prediction models that incorporated disease history and living habits in predicting the risk of Osteoporosis in Chongqing adults.

A deep learning system for automated, multi-modality 2D segmentation of vertebral bodies and intervertebral discs.

PURPOSE: Fractures in vertebral bodies are among the most common complications of osteoporosis and other bone diseases. However, studies that aim to p...

Are social robots ready yet to be used in care and therapy of autism spectrum disorder: A systematic review of randomized controlled trials.

Autism is a neurodevelopmental disorder that affects the everyday life of people who have this lifelong condition. Robots hold great promise for uplif...

A Cascade Graph Convolutional Network for Predicting Protein-Ligand Binding Affinity.

Accurate prediction of binding affinity between protein and ligand is a very important step in the field of drug discovery. Although there are many me...

Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning.

Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its imag...

Machine learning analysis of gene expression profile reveals a novel diagnostic signature for osteoporosis.

BACKGROUND: Osteoporosis (OP) is increasingly prevalent with the aging of the world population. It is urgent to identify efficient diagnostic signatur...

Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study.

BACKGROUND: Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is sile...

Application of artificial intelligence in diagnosis of osteoporosis using medical images: a systematic review and meta-analysis.

Artificial intelligence (AI) is a potentially reliable assistant in the diagnosis of osteoporosis. This meta-analysis aims to assess the diagnostic ac...

Explainable AI reveals changes in skin microbiome composition linked to phenotypic differences.

Alterations in the human microbiome have been observed in a variety of conditions such as asthma, gingivitis, dermatitis and cancer, and much remains ...

Isogeometric finite element-based simulation of the aortic heart valve: Integration of neural network structural material model and structural tensor fiber architecture representations.

The functional complexity of native and replacement aortic heart valves (AVs) is well known, incorporating such physical phenomenons as time-varying n...

Bone strain index as a predictor of further vertebral fracture in osteoporotic women: An artificial intelligence-based analysis.

BACKGROUND: Osteoporosis is an asymptomatic disease of high prevalence and incidence, leading to bone fractures burdened by high mortality and disabil...

Objective characterization of hip pain levels during walking by combining quantitative electroencephalography with machine learning.

Pain is an undesirable sensory experience that can induce depression and limit individuals' activities of daily living, in turn negatively impacting t...

Predicting and Interpreting Spatial Accidents through MDLSTM.

Predicting and interpreting the spatial location and causes of traffic accidents is one of the current hot topics in traffic safety. This research pur...

Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy.

PURPOSE: Novel actuarial deep learning neural network (ADNN) architectures are proposed for joint prediction of radiation therapy outcomes-radiation p...

TargetDBP+: Enhancing the Performance of Identifying DNA-Binding Proteins via Weighted Convolutional Features.

Protein-DNA interactions exist ubiquitously and play important roles in the life cycles of living cells. The accurate identification of DNA-binding pr...

An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning.

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in ...

Non-Rigid Respiratory Motion Estimation of Whole-Heart Coronary MR Images Using Unsupervised Deep Learning.

Non-rigid motion-corrected reconstruction has been proposed to account for the complex motion of the heart in free-breathing 3D coronary magnetic reso...

Combined effects of volume ratio and nitrate recycling ratio on nutrient removal, sludge characteristic and microbial evolution for DPR optimization.

The optimization of volume ratio (V/V/V) and nitrate recycling ratio (R) in a two-sludge denitrifying phosphorus removal (DPR) process of Anaerobic An...

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture.

A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck in the development of machine learning (ML) applica...