Endocrinology

Menopause

Latest AI and machine learning research in menopause for healthcare professionals.

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Whole-brain modelling of resting state fMRI differentiates ADHD subtypes and facilitates stratified neuro-stimulation therapy.

Recent advances in non-linear computational and dynamical modelling have opened up the possibility t...

Cerebral blood flow measurements with O-water PET using a non-invasive machine-learning-derived arterial input function.

Cerebral blood flow (CBF) can be measured with dynamic positron emission tomography (PET) of O-label...

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 bon...

Multitask Non-Autoregressive Model for Human Motion Prediction.

Human motion prediction, which aims at predicting future human skeletons given the past ones, is a t...

Robotic lower extremity exoskeleton use in a non-ambulatory child with cerebral palsy: a case study.

PURPOSE: With few treatment options available for non-ambulatory children with cerebral palsy (CP), ...

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' activiti...

Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition.

BACKGROUND: Articular cartilage degeneration is the hallmark change of osteoarthritis, a severely di...

Predicting and Interpreting Spatial Accidents through MDLSTM.

Predicting and interpreting the spatial location and causes of traffic accidents is one of the curre...

Denoising non-steady state dynamic PET data using a feed-forward neural network.

The quality of reconstructed dynamic PET images, as well as the statistical reliability of the estim...

A Preliminary Characterization of Canonicalized and Non-Canonicalized Section Headers Across Variable Clinical Note Types.

In the electronic health record, the majority of clinically relevant information is stored within cl...

Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces.

We show how complexity theory can be introduced in machine learning to help bring together apparentl...

Recent Advancements and Future Prospects on E-Nose Sensors Technology and Machine Learning Approaches for Non-Invasive Diabetes Diagnosis: A Review.

Diabetes mellitus, commonly measured through an invasive process which although is accurate, has man...

Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy.

BACKGROUND: Surface-guided radiation therapy can be used to continuously monitor a patient's surface...

A non-conventional lightweight Auto Regressive Neural Network for accurate and energy efficient target tracking in Wireless Sensor Network.

The design of an energy-efficient tracking framework is a well-investigated issue and a prominent se...

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 ce...

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