AIMC Topic: Female

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A machine-learning based model for automated recommendation of individualized treatment of rifampicin-resistant tuberculosis.

PloS one
BACKGROUND: Rifampicin resistant tuberculosis remains a global health problem with almost half a million new cases annually. In high-income countries patients empirically start a standardized treatment regimen, followed by an individualized regimen g...

Diagnostic accuracy of dental caries detection using ensemble techniques in deep learning with intraoral camera images.

PloS one
Camera image-based deep learning (DL) techniques have achieved promising results in dental caries screening. To apply the intraoral camera image-based DL technique for dental caries detection and assess its diagnostic performance, we employed the ens...

Exploring a method for extracting concerns of multiple breast cancer patients in the domain of patient narratives using BERT and its optimization by domain adaptation using masked language modeling.

PloS one
Narratives posted on the internet by patients contain a vast amount of information about various concerns. This study aimed to extract multiple concerns from interviews with breast cancer patients using the natural language processing (NLP) model bid...

Using machine learning to predict judgments on Western visual art along content-representational and formal-perceptual attributes.

PloS one
Art research has long aimed to unravel the complex associations between specific attributes, such as color, complexity, and emotional expressiveness, and art judgments, including beauty, creativity, and liking. However, the fundamental distinction be...

Precision meets generalization: Enhancing brain tumor classification via pretrained DenseNet with global average pooling and hyperparameter tuning.

PloS one
Brain tumors pose significant global health concerns due to their high mortality rates and limited treatment options. These tumors, arising from abnormal cell growth within the brain, exhibits various sizes and shapes, making their manual detection f...

Classification of Alzheimer disease using DenseNet-201 based on deep transfer learning technique.

PloS one
Alzheimer's disease (AD) is a brain illness that causes gradual memory loss. AD has no treatment and cannot be cured, so early detection is critical. Various AD diagnosis approaches are used in this regard, but Magnetic Resonance Imaging (MRI) provid...

Predictive modeling of lean body mass, appendicular lean mass, and appendicular skeletal muscle mass using machine learning techniques: A comprehensive analysis utilizing NHANES data and the Look AHEAD study.

PloS one
This study addresses the pressing need for improved methods to predict lean mass in adults, and in particular lean body mass (LBM), appendicular lean mass (ALM), and appendicular skeletal muscle mass (ASMM) for the early detection and management of s...

Use machine learning models to identify and assess risk factors for coronary artery disease.

PloS one
Accurate prediction of coronary artery disease (CAD) is crucial for enabling early clinical diagnosis and tailoring personalized treatment options. This study attempts to construct a machine learning (ML) model for predicting CAD risk and further elu...

Accelerated chemical shift encoded cardiovascular magnetic resonance imaging with use of a resolution enhancement network.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) chemical shift encoding (CSE) enables myocardial fat imaging. We sought to develop a deep learning network (fast chemical shift encoding [FastCSE]) to accelerate CSE.

Sentiment of Nurses Towards Artificial Intelligence and Resistance to Change in Healthcare Organisations: A Mixed-Method Study.

Journal of advanced nursing
BACKGROUND: Research identified preliminary evidence that artificial intelligence (AI) has emerged as a transformative force in healthcare, revolutionising various aspects of healthcare delivery, from diagnostics to treatment planning. However, integ...