Endocrinology

Menopause

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

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Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach.

Bushfires are becoming more frequent and intensive due to changing climate. Those that occur close t...

Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is...

A deep convolutional neural network for the estimation of gas chromatographic retention indices.

A deep convolutional neural network was used for the estimation of gas chromatographic retention ind...

Non-contact heart and respiratory rate monitoring of preterm infants based on a computer vision system: a method comparison study.

BACKGROUND: Non-contact heart rate (HR) and respiratory rate (RR) monitoring is necessary for preter...

Data-driven self-calibration and reconstruction for non-cartesian wave-encoded single-shot fast spin echo using deep learning.

BACKGROUND: Current self-calibration and reconstruction methods for wave-encoded single-shot fast sp...

Identifying non-O157 Shiga toxin-producing Escherichia coli (STEC) using deep learning methods with hyperspectral microscope images.

Non-O157 Shiga toxin-producing Escherichia coli (STEC) serogroups such as O26, O45, O103, O111, O121...

Using Deep Neural Networks to Reconstruct Non-uniformly Sampled NMR Spectra.

Non-uniform and sparse sampling of multi-dimensional NMR spectra has over the last decade become an ...

Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization.

PURPOSE: To develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason...

Deep learning driven QSAR model for environmental toxicology: Effects of endocrine disrupting chemicals on human health.

Over 80,000 endocrine-disrupting chemicals (EDCs) are considered emerging contaminants (ECs), which ...

Characterization of the non-stationary nature of steady-state visual evoked potentials using echo state networks.

State Visual Evoked Potentials (SSVEPs) arise from a resonance phenomenon in the visual cortex that ...

Cancer classification and pathway discovery using non-negative matrix factorization.

OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for und...

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain.

Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate m...

Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.

PURPOSE: To explore the feasibility and performance of machine learning-based radiomics classifier t...

Screening and Assessment of Bone Health in Indian Women Using an Indigenous ELISA of Human Osteocalcin a Bone Turnover Marker.

Osteoporosis a major public health problem of the elderly, is associated with substantial morbidity ...

MR-based artificial intelligence model to assess response to therapy in locally advanced rectal cancer.

PURPOSE: To develop and validate an Artificial Intelligence (AI) model based on texture analysis of ...

Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning.

Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk ...

Analysis of the Deleterious Single Nucleotide Polymorphisms Impact on Estrogen Receptor Alpha-p53 Interaction: A Machine Learning Approach.

Breast cancer is a leading cancer type and one of the major health issues faced by women around the ...

Detecting mitotic cells in HEp-2 images as anomalies via one class classifier.

We propose a novel framework for classification of mitotic v/s non-mitotic cells in a Computer Aided...

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