AIMC Topic:
Supervised Machine Learning
Clear Filters Showing 1491 to 1500 of 1637 articles
Ensemble of diverse deep neural networks with pseudo-labels for repayment prediction in social lending.
Science progress
Jan 1, 2022
In peer-to-peer (P2P) social lending, it is important to predict the repayment of borrowers. P2P lending data are generated in real-time, but most of them are pending to decide the repayment because the deadline is not yet expired. Adding the unexpir...
GRNUlar: A Deep Learning Framework for Recovering Single-Cell Gene Regulatory Networks.
Journal of computational biology : a journal of computational molecular cell biology
Jan 1, 2022
We propose GRNUlar, a novel deep learning framework for supervised learning of gene regulatory networks (GRNs) from single-cell RNA-Sequencing (scRNA-Seq) data. Our framework incorporates two intertwined models. First, we leverage the expressive abil...
Partnering a Compensatory Application with Activity-Aware Prompting to Improve Use in Individuals with Amnestic Mild Cognitive Impairment: A Randomized Controlled Pilot Clinical Trial.
Journal of Alzheimer's disease : JAD
Jan 1, 2022
BACKGROUND: Compensatory aids can help mitigate the impact of progressive cognitive impairment on daily living.
Early Identification of Trauma-induced Coagulopathy: Development and Validation of a Multivariable Risk Prediction Model.
Annals of surgery
Dec 1, 2021
OBJECTIVE: The aim of this study was to develop and validate a risk prediction tool for trauma-induced coagulopathy (TIC), to support early therapeutic decision-making.
Increasing the accuracy of single sequence prediction methods using a deep semi-supervised learning framework.
Bioinformatics (Oxford, England)
Nov 5, 2021
MOTIVATION: Over the past 50 years, our ability to model protein sequences with evolutionary information has progressed in leaps and bounds. However, even with the latest deep learning methods, the modelling of a critically important class of protein...
Learning Cellular Phenotypes through Supervision.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Image-based cell phenotyping is an important and open problem in computational pathology. The two principal challenges are: 1) making the cell cluster properties insensitive to experimental settings (like seed point and feature selection) and 2) ensu...
Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Deep learning has achieved promising segmentation performance on 3D left atrium MR images. However, annotations for segmentation tasks are expensive, costly and difficult to obtain. In this paper, we introduce a novel hierarchical consistency regular...
A new machine learning based user-friendly software platform for automatic radiomics modeling and analysis.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Supervised machine learning methods are usually used to build a custom model for disease diagnosis and auxiliary prognosis in radiomics studies. A classical machine learning pipeline involves a series of steps and multiple algorithms, which leads to ...
Segment Origin Prediction: A Self-supervised Learning Method for Electrocardiogram Arrhythmia Classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
The automatic arrhythmia classification system has made a significant contribution to reducing the mortality rate of cardiovascular diseases. Although the current deep-learning-based models have achieved ideal effects in arrhythmia classification, th...
A Semi-Supervised Few-Shot Learning Model for Epileptic Seizure Detection.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
In the past decade, the rapid development of machine learning has dramatically improved the performance of epileptic detection with Electroencephalography (EEG). However, only a small amount of labeled epileptic data is available for training because...
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 30140
- Neural Networks, Computer 29282
- Algorithms 26270
- Deep Learning 25792
- Artificial Intelligence 23822
- Robotics 13268
- Image Processing, Computer-Assisted 9276
- Retrospective Studies 8835
- Magnetic Resonance Imaging 5976
- Reproducibility of Results 5499
- Tomography, X-Ray Computed 4622
- Support Vector Machine 4609
- Computational Biology 4126
- Brain 3919
- Computer Simulation 3823
Recent Journals
- Scientific reports 5092
- Sensors (Basel, Switzerland) 4729
- PloS one 3884
- Neural networks : the official journal of the International Neural Network Society 2842
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1779
- 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 1224
- IEEE journal of biomedical and health informatics 1081
- Journal of chemical information and modeling 934
- Nature communications 854
- Briefings in bioinformatics 849
- Bioinformatics (Oxford, England) 847
- Computer methods and programs in biomedicine 844
- IEEE transactions on neural networks and learning systems 780