AIMC Topic: Female

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An enhanced denoising system for mammogram images using deep transformer model with fusion of local and global features.

Scientific reports
Image denoising is a critical problem in low-level computer vision, where the aim is to reconstruct a clean, noise-free image from a noisy input, such as a mammogram image. In recent years, deep learning, particularly convolutional neural networks (C...

The Feasibility of Large Language Models in Verbal Comprehension Assessment: Mixed Methods Feasibility Study.

JMIR formative research
BACKGROUND: Cognitive assessment is an important component of applied psychology, but limited access and high costs make these evaluations challenging.

Machine Learning-Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: To address gaps in global understanding of cultural and social variations, this study used a high-performance machine learning (ML) model to predict adolescent substance use across three national datasets.

Identifying Patient-Reported Care Experiences in Free-Text Survey Comments: Topic Modeling Study.

JMIR medical informatics
BACKGROUND: Patient-reported experience surveys allow administrators, clinicians, and researchers to quantify and improve health care by receiving feedback directly from patients. Existing research has focused primarily on quantitative analysis of su...

Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.

Acta neurochirurgica
PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitating the prediction of treatment outcomes and patient survival. However, the effectiveness of ML models heavily relies on both the choice of algorithms...

Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia.

Frontiers in immunology
BACKGROUND: Neutrophil extracellular traps (NETs) play pivotal roles in various pathological processes. The formation of NETs is impaired in acute myeloid leukemia (AML), which can result in immunodeficiency and increased susceptibility to infection.

Development and validation of predictive models for diabetic retinopathy using machine learning.

PloS one
OBJECTIVE: This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks.

Bridging gaps in artificial intelligence adoption for maternal-fetal and obstetric care: Unveiling transformative capabilities and challenges.

Computer methods and programs in biomedicine
PURPOSE: This review aims to comprehensively explore the application of Artificial Intelligence (AI) to an area that has not been traditionally explored in depth: the continuum of maternal-fetal health. In doing so, the intent was to examine this phy...

Novel Robotic Balloon-Based Device for Wrist-Extension Therapy of Hemiparesis Stroke Patients.

Sensors (Basel, Switzerland)
Upper-limb paresis is one of the main complications after stroke. It is commonly associated with impaired wrist-extension function. Upper-limb paresis can place a tremendous burden on stroke survivors and their families. A novel soft-actuator device,...

Machine learning using random forest to differentiate between blow and fall situations of head trauma.

International journal of legal medicine
Blunt head trauma is a common occurrence in forensic practice. Interpreting the origin of craniocerebral injuries can be a challenging process, particularly when it comes to distinguishing between falls or inflicted blows. The objective of this study...