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SGA-Driven feature selection and random forest classification for enhanced breast cancer diagnosis: A comparative study.
Scientific reports
Mar 30, 2025
In this study, we propose a novel approach for breast cancer classification that integrates the Seagull Optimization Algorithm (SGA) for feature selection with the Random Forest (RF) classifier for effective data classification. The novelty of our ap...
Multimodal contrastive learning for enhanced explainability in pediatric brain tumor molecular diagnosis.
Scientific reports
Mar 30, 2025
Despite the promising performance of convolutional neural networks (CNNs) in brain tumor diagnosis from magnetic resonance imaging (MRI), their integration into the clinical workflow has been limited. That is mainly due to the fact that the features ...
Investigation of the relationship between medical artificial intelligence readiness and individual innovativeness levels in nursing students.
Nurse education today
Mar 29, 2025
AIM: This study was conducted to identify nursing students' medical artificial intelligence readiness and individual innovativeness levels, to examine the relationship between these two concepts and to determine the variables that create a significan...
Accuracy of a deep neural network for automated pulmonary embolism detection on dedicated CT pulmonary angiograms.
European journal of radiology
Mar 29, 2025
PURPOSE: To assess the performance of a Deep Neural Network (DNN)-based prototype algorithm for automated PE detection on CTPA scans.
Female
Neural Networks, Computer
Humans
Middle Aged
Reproducibility of Results
Aged
Computed Tomography Angiography
Algorithms
Deep Learning
Aged, 80 and over
Pulmonary Artery
Retrospective Studies
Adult
Radiographic Image Interpretation, Computer-Assisted
Pulmonary Embolism
Sensitivity and Specificity
Male
Multiomics evaluation and machine learning optimize molecular classification, prediction of prognosis and immunotherapy response for ovarian cancer.
Pathology, research and practice
Mar 29, 2025
BACKGROUND: Ovarian cancer (OC), owing to its substantial heterogeneity and high invasiveness, has historically been devoid of precise, individualized treatment options. This study aimed to establish integrated consensus subtypes of OC using differen...
Handwriting strokes as biomarkers for Alzheimer's disease prediction: A novel machine learning approach.
Computers in biology and medicine
Mar 29, 2025
In recent years, machine learning-based handwriting analysis has emerged as a valuable tool for supporting the early diagnosis of Alzheimer's disease and predicting its progression. Traditional approaches represent handwriting tasks using a single fe...
Advanced convolutional neural network with attention mechanism for Alzheimer's disease classification using MRI.
Computers in biology and medicine
Mar 29, 2025
This paper introduces a novel convolutional neural network model with an attention mechanism to advance Alzheimer disease (AD) classification using Magnetic Resonance Imaging (MRI). The model architecture is meticulously crafted to enhance feature ex...
Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model.
BMC pregnancy and childbirth
Mar 29, 2025
OBJECTIVE: The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery.
A cross-sectional study comparing machine learning and logistic regression techniques for predicting osteoporosis in a group at high risk of cardiovascular disease among old adults.
BMC geriatrics
Mar 29, 2025
BACKGROUND: Osteoporosis has become a significant public health concern that necessitates the application of appropriate techniques to calculate disease risk. Traditional methods, such as logistic regression,have been widely used to identify risk fac...
Comparing discriminatory behavior against AI and humans.
Scientific reports
Mar 29, 2025
Although discrimination is typically believed to occur from well-defined categories like ethnicity, disability, and sex, studies have found that discrimination persists in minimal conditions lacking such categories. Participants have been found to pr...
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