Endocrinology

Menopause

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

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Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre study.

BACKGROUND: This study, based on multicentre cohorts, aims to utilize computed tomography (CT) image...

Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.

Comparing a family structure to a company, one can often think of parents as leaders and adolescents...

A machine learning method for predicting the probability of MODS using only non-invasive parameters.

OBJECTIVES: Timely and accurate prediction of multiple organ dysfunction syndrome (MODS) is essentia...

Non-Local Graph Neural Networks.

Modern graph neural networks (GNNs) learn node embeddings through multilayer local aggregation and a...

Deep learning to estimate durable clinical benefit and prognosis from patients with non-small cell lung cancer treated with PD-1/PD-L1 blockade.

Different biomarkers based on genomics variants have been used to predict the response of patients t...

Non-Local Temporal Difference Network for Temporal Action Detection.

As an important part of video understanding, temporal action detection (TAD) has wide application sc...

Identification and Improvement of Hazard Scenarios in Non-Motorized Transportation Using Multiple Deep Learning and Street View Images.

In the prioritized vehicle traffic environment, motorized transportation has been obtaining more spa...

Automatic identification of early ischemic lesions on non-contrast CT with deep learning approach.

Early ischemic lesion on non-contrast computed tomogram (NCCT) in acute stroke can be subtle and nee...

Trends in segmentectomy for the treatment of stage 1A non-small cell lung cancers: Does the robot have an impact?

OBJECTIVES: Lobectomy may unnecessarily resect healthy lung parenchyma in Stage 1A non-small cell lu...

Application of Deep Convolutional Neural Networks in the Diagnosis of Osteoporosis.

The aim of this study was to assess the possibility of using deep convolutional neural networks (DCN...

Segmentation of trabecular bone microdamage in Xray microCT images using a two-step deep learning method.

INTRODUCTION: One of the current approaches to improve our understanding of osteoporosis is to study...

Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors.

Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based reha...

CTRR-ncRNA: A Knowledgebase for Cancer Therapy Resistance and Recurrence Associated Non-coding RNAs.

Cancer therapy resistance and recurrence (CTRR) are the dominant causes of death in cancer patients....

Differentiation of eosinophilic and non-eosinophilic chronic rhinosinusitis on preoperative computed tomography using deep learning.

OBJECTIVES: This study aimed to develop deep learning (DL) models for differentiating between eosino...

Robotic Non-Destructive Testing.

Non-destructive testing (NDT) and evaluation (NDE) are commonly referred to as the vast group of ana...

PINC: A Tool for Non-Coding RNA Identification in Plants Based on an Automated Machine Learning Framework.

There is evidence that non-coding RNAs play significant roles in the regulation of nutrient homeosta...

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