Menopause

AI-enabled alkaline-resistant evolution of protein to apply in mass production.

Artificial intelligence (AI) models have been used to study the compositional regularities of protei...

Deep learning-based time-of-flight (ToF) enhancement of non-ToF PET scans for different radiotracers.

AIM: To evaluate a deep learning-based time-of-flight (DLToF) model trained to enhance the image qua...

Machine learning classification of active viewing of pain and non-pain images using EEG does not exceed chance in external validation samples.

Previous research has demonstrated that machine learning (ML) could not effectively decode passive o...

Cooperative Magnetic Interfacial Microrobot Couple for Versatile Non-Contact Biomedical Applications.

Magnetic interfacial microrobots are increasingly recognized as a promising approach for potential b...

Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic...

Non-destructive origin and ginsenoside analysis of American ginseng via NIR and deep learning.

American ginseng is widely in demand as a famous medicinal herb, but the production conditions affec...

Label-efficient sequential model-based weakly supervised intracranial hemorrhage segmentation in low-data non-contrast CT imaging.

BACKGROUND: In clinical settings, intracranial hemorrhages (ICH) are routinely diagnosed using non-c...

Development and validation of MRI-derived deep learning score for non-invasive prediction of PD-L1 expression and prognostic stratification in head and neck squamous cell carcinoma.

BACKGROUND: Immunotherapy has revolutionized the treatment landscape for head and neck squamous cell...

A practical deep learning model for core temperature prediction of specialized workers in high-temperature environments.

The health issues of hazardous operations in high-temperature environments are increasing concerns t...

Advancing tele-perception: a paradigm shift from traditional non-contact sensing to adaptive embodied artificial intelligence systems.

Machine-learning tool for classifying pulmonary hypertension via expert reader-provided CT features: An educational resource for non-dedicated radiologists.

PURPOSE: Pulmonary hypertension (PH) is a complex disease classified into five groups (I-V) by the E...

A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Interest in HDAC3 inhibitors (HDAC3i) for pharmacological applications outside of cancer is growing....

Developing a nomogram model for predicting non-obstructive azoospermia using machine learning techniques.

Azoospermia, defined by the absence of sperm in the ejaculate, manifests as obstructive azoospermia ...

Early detection of disease outbreaks and non-outbreaks using incidence data: A framework using feature-based time series classification and machine learning.

Forecasting the occurrence and absence of novel disease outbreaks is essential for disease managemen...

Artificial intelligence for opportunistic osteoporosis screening with a Hounsfield Unit in chronic obstructive pulmonary disease patients.

INTRODUCTION: To investigate the accuracy of an artificial intelligence (AI) prototype in determinin...

Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT.

PURPOSE: This study aims to explore the potential of non-contrast abdominal CT radiomics and deep le...

Screening of estrogen receptor activity of per- and polyfluoroalkyl substances based on deep learning and in vivo assessment.

Over the past decades, exposure to per- and polyfluoroalkyl substances (PFAS), a group of synthetic ...

Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.

This study aims to apply a multi-modal approach of the deep learning method for survival prediction ...

Machine Learning-Enabled Non-Invasive Screening of Tumor-Associated Circulating Transcripts for Early Detection of Colorectal Cancer.

Colorectal cancer (CRC) is a major cause of cancer-related mortality, highlighting the need for accu...

An assessment of breast cancer HER2, ER, and PR expressions based on mammography using deep learning with convolutional neural networks.

Mammography is the recommended imaging modality for breast cancer screening. Expressions of human ep...

Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.

BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by ost...