Menopause

Deep learning-based low-dose CT simulator for non-linear reconstruction methods.

BACKGROUND: Computer algorithms that simulate lower-doses computed tomography (CT) images from clini...

Automated Lugano Metabolic Response Assessment in F-Fluorodeoxyglucose-Avid Non-Hodgkin Lymphoma With Deep Learning on F-Fluorodeoxyglucose-Positron Emission Tomography.

PURPOSE: Artificial intelligence can reduce the time used by physicians on radiological assessments....

Synergistic Machine Learning Accelerated Discovery of Nanoporous Inorganic Crystals as Non-Absorbable Oral Drugs.

Machine learning (ML) has taken drug discovery to new heights, where effective ML training requires ...

An interpretable ensemble structure with a non-iterative training algorithm to improve the predictive accuracy of healthcare data analysis.

The modern development of healthcare is characterized by a set of large volumes of tabular data for ...

Scan-Specific Self-Supervised Bayesian Deep Non-Linear Inversion for Undersampled MRI Reconstruction.

Magnetic resonance imaging is subject to slow acquisition times due to the inherent limitations in d...

Non-invasive detection of systemic lupus erythematosus using SERS serum detection technology and deep learning algorithms.

Systemic lupus erythematosus (SLE) is an autoimmune disease with multiple symptoms, and its rapid sc...

Perspectives on managing non-communicable diseases in pediatric health using artificial intelligence.

New vision of HookEfficientNet deep neural network: Intelligent histopathological recognition system of non-small cell lung cancer.

BACKGROUND: Efficient and precise diagnosis of non-small cell lung cancer (NSCLC) is quite critical ...

Systematic literature review on reinforcement learning in non-communicable disease interventions.

There is evidence that reducing modifiable risk factors and strengthening medical and health interve...

A comprehensive approach for osteoporosis detection through chest CT analysis and bone turnover markers: harnessing radiomics and deep learning techniques.

PURPOSE: The main objective of this study is to assess the possibility of using radiomics, deep lear...

Prediction of pharmaceutical and non-pharmaceutical expenditures associated with Diabetes Mellitus type II based on clinical risk.

OBJECTIVE: To assess the effectiveness of different machine learning models in estimating the pharma...

Identification of shared gene signatures and pathways for diagnosing osteoporosis with sarcopenia through integrated bioinformatics analysis and machine learning.

BACKGROUND: Prior studies have suggested a potential relationship between osteoporosis and sarcopeni...

Hybrid CNN-Transformer Network With Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-Contrast CT Scans.

Lesion segmentation is a fundamental step for the diagnosis of acute ischemic stroke (AIS). Non-cont...

A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods.

The comprehensive integration of machine learning healthcare models within clinical practice remains...

Appropriate use of blood cultures in the emergency department through machine learning (ABC): study protocol for a randomised controlled non-inferiority trial.

INTRODUCTION: The liberal use of blood cultures in emergency departments (EDs) leads to low yields a...

A novel case-finding strategy based on artificial intelligence for the systematic identification and management of individuals with osteoporosis or at varying risk of fragility fracture.

UNLABELLED: An artificial intelligence-based case-finding strategy has been developed to systematica...

Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical study.

BACKGROUND: Dengue epidemics impose considerable strain on healthcare resources. Real-time continuou...

Predicting Non-Alcoholic Steatohepatitis: A Lipidomics-Driven Machine Learning Approach.

Nonalcoholic fatty liver disease (NAFLD), nowadays the most prevalent chronic liver disease in Weste...

Adaptive sampling artificial-actual control for non-zero-sum games of constrained systems.

Considering physical constraints encountered by actuators, this paper addresses the non-zero-sum gam...

Integrating deep learning with non-destructive thermal imaging for precision guava ripeness determination.

BACKGROUND: To mitigate post-harvest losses and inform harvesting decisions at the same time as ensu...

A 36-nW Electrocardiogram Anomaly Detector Based on a 1.5-bit Non-Feedback Delta Quantizer for Always-on Cardiac Monitoring.

An always-on electrocardiogram (ECG) anomaly detector (EAD) with ultra-low power (ULP) consumption i...