Endocrinology

Menopause

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

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Identification of early invisible acute ischemic stroke in non-contrast computed tomography using two-stage deep-learning model.

Although non-contrast computed tomography (NCCT) is the recommended examination for the suspected a...

Deep Learning-Based Non-Intrusive Commercial Load Monitoring.

Commercial load is an essential demand-side resource. Monitoring commercial loads helps not only com...

Non-Deep Active Learning for Deep Neural Networks.

One way to improve annotation efficiency is active learning. The goal of active learning is to selec...

Non-iterative learning machine for identifying CoViD19 using chest X-ray images.

CoViD19 is a novel disease which has created panic worldwide by infecting millions of people around ...

Deep learning applications in telerehabilitation speech therapy scenarios.

Nowadays, many application scenarios benefit from automatic speech recognition (ASR) technology. Wit...

Application of image processing and soft computing strategies for non-destructive estimation of plum leaf area.

Plant leaf area (LA) is a key metric in plant monitoring programs. Machine learning methods were use...

Non-Intrusive Fish Weight Estimation in Turbid Water Using Deep Learning and Regression Models.

Underwater fish monitoring is the one of the most challenging problems for efficiently feeding and h...

Cardiotocography in Obstetrics: New Solutions for "Routine" Technology.

This work is devoted to the problems of one of the most common screening examinations used in medica...

Predicting poor glycemic control during Ramadan among non-fasting patients with diabetes using artificial intelligence based machine learning models.

AIMS: This study aims to predict poor glycemic control during Ramadan among non-fasting patients wit...

Causal Discovery in Linear Non-Gaussian Acyclic Model With Multiple Latent Confounders.

Causal discovery from observational data is a fundamental problem in science. Though the linear non-...

Two stream Non-Local CNN-LSTM network for the auxiliary assessment of mental retardation.

At present, the assessment of mental retardation is mainly based on clinical interview, which requir...

Accurate contactless sleep apnea detection framework with signal processing and machine learning methods.

The detection of sleep apnea is critical for assessing sleep quality. It is also a proven biometric ...

Automation of dry eye disease quantitative assessment: A review.

Dry eye disease (DED) is a common eye condition worldwide and a primary reason for visits to the oph...

A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.

Artificial intelligence techniques were explored to assess the ability to anticipate self-harming be...

Disturbance Observer-Based Minimum Entropy Control for a Class of Disturbed Non-Gaussian Stochastic Systems.

In this article, a novel control algorithm is developed for a class of nonlinear stochastic systems ...

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.

Non-preference-based patient-reported outcome measures (PROMs) are popular in health outcomes resear...

A non-destructive methodology for determination of cantaloupe sugar content using machine vision and deep learning.

BACKGROUND: To determine the maturity of cantaloupe, measuring the soluble solid content (SSC) as th...

eTEP-RS for incisional hernias in a non-robotic center. Is laparoscopy enough to perform a durable MIS repair of the abdominal wall defect?

INTRODUCTION: Incisional hernias can complicate up to 25% of laparotomies, and successful repair rem...

DNL-Net: deformed non-local neural network for blood vessel segmentation.

BACKGROUND: The non-local module has been primarily used in literature to capturing long-range depen...

NPBDREG: Uncertainty assessment in diffeomorphic brain MRI registration using a non-parametric Bayesian deep-learning based approach.

Quantification of uncertainty in deep-neural-networks (DNN) based image registration algorithms play...

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