AIMC Topic: Machine Learning

Clear Filters Showing 15351 to 15360 of 34417 articles

Public Discourse and Sentiment Toward Dementia on Chinese Social Media: Machine Learning Analysis of Weibo Posts.

Journal of medical Internet research
BACKGROUND: Dementia is a global public health priority due to rapid growth of the aging population. As China has the world's largest population with dementia, this debilitating disease has created tremendous challenges for older adults, family careg...

Radiomics and Deep Learning for Disease Detection in Musculoskeletal Radiology: An Overview of Novel MRI- and CT-Based Approaches.

Investigative radiology
Radiomics and machine learning-based methods offer exciting opportunities for improving diagnostic performance and efficiency in musculoskeletal radiology for various tasks, including acute injuries, chronic conditions, spinal abnormalities, and neop...

Improving energy consumption prediction for residential buildings using Modified Wild Horse Optimization with Deep Learning model.

Chemosphere
The consumption of a significant quantity of energy in buildings has been linked to the emergence of environmental problems that can have unfavourable effects on people. The prediction of energy consumption is widely regarded as an effective method f...

The effect of preprocessing filters on predictive performance in radiomics.

European radiology experimental
BACKGROUND: Radiomics is a noninvasive method using machine learning to support personalised medicine. Preprocessing filters such as wavelet and Laplacian-of-Gaussian filters are commonly used being thought to increase predictive performance. However...

MolPredictX: Online Biological Activity Predictions by Machine Learning Models.

Molecular informatics
Here we report the development of MolPredictX, an innovate and freely accessible web interface for biological activity predictions of query molecules. MolPredictX utilizes in-house QSAR models to provide 27 qualitative predictions (active or inactive...

Randomized Clinical Trials of Machine Learning Interventions in Health Care: A Systematic Review.

JAMA network open
IMPORTANCE: Despite the potential of machine learning to improve multiple aspects of patient care, barriers to clinical adoption remain. Randomized clinical trials (RCTs) are often a prerequisite to large-scale clinical adoption of an intervention, a...

Comprehensive Analysis of Network Slicing for the Developing Commercial Needs and Networking Challenges.

Sensors (Basel, Switzerland)
Network slicing (NS) is one of the most prominent next-generation wireless cellular technology use cases, promising to unlock the core benefits of 5G network architecture by allowing communication service providers (CSPs) and operators to construct s...

Evaluation of Three Feature Dimension Reduction Techniques for Machine Learning-Based Crop Yield Prediction Models.

Sensors (Basel, Switzerland)
Machine learning (ML) has been widely used worldwide to develop crop yield forecasting models. However, it is still challenging to identify the most critical features from a dataset. Although either feature selection (FS) or feature extraction (FX) t...

MMDCP: Multi-Modal Dental Caries Prediction for Decision Support System Using Deep Learning.

International journal of environmental research and public health
In recent years, healthcare has gained unprecedented attention from researchers in the field of Human health science and technology. Oral health, a subdomain of healthcare described as being very complex, is threatened by diseases like dental caries,...

Learning a confidence score and the latent space of a new supervised autoencoder for diagnosis and prognosis in clinical metabolomic studies.

BMC bioinformatics
BACKGROUND: Presently, there is a wide variety of classification methods and deep neural network approaches in bioinformatics. Deep neural networks have proven their effectiveness for classification tasks, and have outperformed classical methods, but...