AIMC Topic: Sex Factors
Clear Filters Showing 191 to 200 of 225 articles
Determinants of ascending aortic morphology: cross-sectional deep learning-based analysis on 25 073 non-contrast-enhanced NAKO MRI studies.
European heart journal. Cardiovascular Imaging
Apr 30, 2025
AIMS: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resona...
Risk evaluation and incidence prediction of endolymphatic hydrops using multilayer perceptron in patients with audiovestibular symptoms.
Medicine
Mar 14, 2025
Endolymphatic hydrops (EH) has been visualized on magnetic resonance imaging (MRI) in patients with various inner ear diseases. The purpose of this study was to evaluate the prevalence and risk factors of significant EH on inner ear MRI in patients w...
Artificial intelligence-enhanced electrocardiography for the identification of a sex-related cardiovascular risk continuum: a retrospective cohort study.
The Lancet. Digital health
Mar 1, 2025
BACKGROUND: Females are typically underserved in cardiovascular medicine. The use of sex as a dichotomous variable for risk stratification fails to capture the heterogeneity of risk within each sex. We aimed to develop an artificial intelligence-enha...
Identifying high-dose opioid prescription risks using machine learning: A focus on sociodemographic characteristics.
Journal of opioid management
Jan 1, 2025
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.
Integrating Clinical Data and Patient-Reported Outcomes for Analyzing Gender Differences and Progression in Multiple Sclerosis Using Machine Learning.
Studies in health technology and informatics
Nov 22, 2024
Multiple sclerosis (MS) is a complex neurodegenerative disease with a variable prognosis that complicates effective management and treatment. This study leverages machine learning (ML) to enhance the understanding of disease progression and uncover g...
Machine learning trial to detect sex differences in simple sticker arts of 1606 preschool children.
Minerva pediatrics
Jun 1, 2024
BACKGROUND: Previous studies suggested that drawings made by preschool boys and girls show distinguishable differences. However, children's drawings on their own are too complexly determined and inherently ambiguous to be a reliable indicator. In the...
New approach of prediction of recurrence in thyroid cancer patients using machine learning.
Medicine
Oct 22, 2021
Although papillary thyroid cancers are known to have a relatively low risk of recurrence, several factors are associated with a higher risk of recurrence, such as extrathyroidal extension, nodal metastasis, and BRAF gene mutation. However, predicting...
Adult
Male
Middle Aged
Thyroidectomy
Thyroid Neoplasms
Body Mass Index
Lymphatic Metastasis
Age Factors
Neoplasm Recurrence, Local
Iodine Radioisotopes
Prognosis
Female
Proto-Oncogene Proteins B-raf
Reproducibility of Results
Humans
Aged
Machine Learning
Young Adult
Sex Factors
Algorithms
Tumor Burden
Thyroglobulin
Thyroid Cancer, Papillary
A novel deep learning method for predictive modeling of microbiome data.
Briefings in bioinformatics
May 20, 2021
With the development and decreasing cost of next-generation sequencing technologies, the study of the human microbiome has become a rapid expanding research field, which provides an unprecedented opportunity in various clinical applications such as d...
DS-GCNs: Connectome Classification using Dynamic Spectral Graph Convolution Networks with Assistant Task Training.
Cerebral cortex (New York, N.Y. : 1991)
Jan 5, 2021
Functional connectivity (FC) matrices measure the regional interactions in the brain and have been widely used in neurological brain disease classification. A brain network, also named as connectome, could form a graph structure naturally, the nodes ...
Machine-learning prediction of unplanned 30-day rehospitalization using the French hospital medico-administrative database.
Medicine
Dec 4, 2020
Predicting unplanned rehospitalizations has traditionally employed logistic regression models. Machine learning (ML) methods have been introduced in health service research and may improve the prediction of health outcomes. The objective of this work...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32021
- Neural Networks, Computer 30231
- Algorithms 27405
- Deep Learning 26912
- Artificial Intelligence 24844
- Robotics 13389
- Image Processing, Computer-Assisted 9738
- Retrospective Studies 9346
- Magnetic Resonance Imaging 6347
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4866
- Support Vector Machine 4771
- Computational Biology 4333
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6800
- Sensors (Basel, Switzerland) 4794
- PloS one 4210
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1066
- Nature communications 1047
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 874
- Journal of medical Internet research 864
- Briefings in bioinformatics 853