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Development and application of explainable artificial intelligence using machine learning classification for long-term facial nerve function after vestibular schwannoma surgery.

Journal of neuro-oncology
PURPOSE: Vestibular schwannomas (VSs) represent the most common cerebellopontine angle tumors, posing a challenge in preserving facial nerve (FN) function during surgery. We employed the Extreme Gradient Boosting machine learning classifier to predic...

AI driven interpretable deep learning based fetal health classification.

SLAS technology
In this study, a deep learning model is proposed for the classification of fetal health into 3 categories: Normal, suspect, and pathological. The primary objective is to utilize the power of deep learning to improve the efficiency and effectiveness o...

Segmentation of four-chamber view images in fetal ultrasound exams using a novel deep learning model ensemble method.

Computers in biology and medicine
Fetal echocardiography, a specialized ultrasound application commonly utilized for fetal heart assessment, can greatly benefit from automated segmentation of anatomical structures, aiding operators in their evaluations. We introduce a novel approach ...

Sex dimorphism and hormesis response to polystyrene microplastic exposure in kinematics and metabolism of Drosophila model based on deep learning.

Journal of environmental management
The emergence of microplastics (MPs) has become a significant focus of environmental pollution, prompting widespread concern regarding its potential toxicity and impact on the environment and organisms. Recent research indicates notable alterations i...

Classification of Internal and External Distractions in an Educational VR Environment Using Multimodal Features.

IEEE transactions on visualization and computer graphics
Virtual reality (VR) can potentially enhance student engagement and memory retention in the classroom. However, distraction among participants in a VR-based classroom is a significant concern. Several factors, including mind wandering, external noise...

Integrating anoikis and ErbB signaling insights with machine learning and single-cell analysis for predicting prognosis and immune-targeted therapy outcomes in hepatocellular carcinoma.

Frontiers in immunology
BACKGROUND: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its poor prognosis and limited therapeutic modalities. Anoikis and ErbB signaling pathways are pivotal in cancer cell proliferation and metastasis, but thei...

Machine learning-based risk prediction for major adverse cardiovascular events in a Brazilian hospital: Development, external validation, and interpretability.

PloS one
BACKGROUND: Studies of cardiovascular disease risk prediction by machine learning algorithms often do not assess their ability to generalize to other populations and few of them include an analysis of the interpretability of individual predictions. T...

Comparative study of machine learning approaches integrated with genetic algorithm for IVF success prediction.

PloS one
INTRODUCTION: IVF is a widely-used assisted reproductive technology with a consistent success rate of around 30%, and improving this rate is crucial due to emotional, financial, and health-related implications for infertile couples. This study aimed ...

A Systematic Review and Meta-Analysis of the Association between Childhood Exposure to Intimate Partner Violence and Intimate Partner Violence Victimization/Perpetration in Adulthood in Africa.

Trauma, violence & abuse
Intimate partner violence (IPV) is widespread in many African countries. Evidence, mainly from Western countries, shows that exposure to IPV in childhood is an important risk factor for experiences of IPV in adulthood. However, to date, no systematic...