AIMC Topic: Female

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Using Google web search to analyze and evaluate the application of ChatGPT in femoroacetabular impingement syndrome.

Frontiers in public health
BACKGROUND: Chat Generative Pre-trained Transformer (ChatGPT) is a new machine learning tool that allows patients to access health information online, specifically compared to Google, the most commonly used search engine in the United States. Patient...

DAU-Net: Dual attention-aided U-Net for segmenting tumor in breast ultrasound images.

PloS one
Breast cancer remains a critical global concern, underscoring the urgent need for early detection and accurate diagnosis to improve survival rates among women. Recent developments in deep learning have shown promising potential for computer-aided det...

Application of a transparent artificial intelligence algorithm for US adults in the obese category of weight.

PloS one
OBJECTIVE AND AIMS: Identification of associations between the obese category of weight in the general US population will continue to advance our understanding of the condition and allow clinicians, providers, communities, families, and individuals m...

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.

PloS one
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...

Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...

Using drawings and deep neural networks to characterize the building blocks of human visual similarity.

Memory & cognition
Early in life and without special training, human beings discern resemblance between abstract visual stimuli, such as drawings, and the real-world objects they represent. We used this capacity for visual abstraction as a tool for evaluating deep neur...

Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.

Annals of medicine
BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity.

How perceived lack of benevolence harms trust of artificial intelligence management.

The Journal of applied psychology
As organizations continue to supplement and replace human management with artificial intelligence (AI), it is essential that we understand the factors that influence employees' trust in AI management. Across one preregistered field study, where we su...

CT-based radiomics analysis of different machine learning models for differentiating gnathic fibrous dysplasia and ossifying fibroma.

Oral diseases
OBJECTIVE: In this study, our aim was to develop and validate the effectiveness of diverse radiomic models for distinguishing between gnathic fibrous dysplasia (FD) and ossifying fibroma (OF) before surgery.