AIMC Topic: Female

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Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey.

Environmental health and preventive medicine
BACKGROUND: Hypertension is a serious chronic disease that can significantly lead to various cardiovascular diseases, affecting vital organs such as the heart, brain, and kidneys. Our goal is to predict the risk of new onset hypertension using machin...

A Multi-Label Deep Learning Model for Detailed Classification of Alzheimer's Disease.

Actas espanolas de psiquiatria
BACKGROUND: Accurate diagnosis and classification of Alzheimer's disease (AD) are crucial for effective treatment and management. Traditional diagnostic models, largely based on binary classification systems, fail to adequately capture the complexiti...

Using machine learning to predict patients with polycystic ovary disease in Chinese women.

Taiwanese journal of obstetrics & gynecology
OBJECTIVE: With an estimated global frequency ranging from5 % to 21 %, polycystic ovary syndrome (PCOS) is one of the most prevalent hormonal disorders. There are many factors found to be related to PCOS. However, most of these researches used tradit...

Artificial intelligence and assisted reproductive technology: A comprehensive systematic review.

Taiwanese journal of obstetrics & gynecology
The objective of this review is to evaluate the contributions of Artificial Intelligence (AI) to Assisted Reproductive Technologies (ART), focusing on its role in enhancing the processes and outcomes of fertility treatments. This study analyzed 48 re...

Predicting Live Weight for Female Rabbits of Meat Crosses From Body Measurements Using LightGBM, XGBoost and Support Vector Machine Algorithms.

Veterinary medicine and science
Prediction of body weight (BW) using biometric measurements is an important tool especially for animal welfare and automatic phenotyping tools that needs mathematical models. In this study, it was aimed to predict the BW using body length (BL), chest...

Prospective Evaluation of Accelerated Brain MRI Using Deep Learning-Based Reconstruction: Simultaneous Application to 2D Spin-Echo and 3D Gradient-Echo Sequences.

Korean journal of radiology
OBJECTIVE: To prospectively evaluate the effect of accelerated deep learning-based reconstruction (Accel-DL) on improving brain magnetic resonance imaging (MRI) quality and reducing scan time compared to that in conventional MRI.

Faster Acquisition and Improved Image Quality of T2-Weighted Dixon Breast MRI at 3T Using Deep Learning: A Prospective Study.

Korean journal of radiology
OBJECTIVE: The aim of this study was to compare image quality features and lesion characteristics between a faster deep learning (DL) reconstructed T2-weighted (T2-w) fast spin-echo (FSE) Dixon sequence with super-resolution (T2) and a conventional T...

Using voice recognition and machine learning techniques for detecting patient-reported outcomes from conversational voice in palliative care patients.

Japan journal of nursing science : JJNS
AIM: Patient-reported outcome measures (PROMs) are increasingly used in palliative care to evaluate patients' symptoms and conditions. Healthcare providers often collect PROMs through conversations. However, the manual entry of these data into electr...

Estimation of Central Aortic Pressure Waveforms by Combination of a Meta-Learning Neural Network and a Physics-Driven Method.

International journal for numerical methods in biomedical engineering
The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved....