AIMC Topic: Machine Learning

Clear Filters Showing 13391 to 13400 of 34417 articles

Artificial intelligence to empower diagnosis of myelodysplastic syndromes by multiparametric flow cytometry.

Haematologica
The diagnosis of myelodysplastic syndromes (MDS) might be challenging and relies on the convergence of cytological, cytogenetic, and molecular factors. Multiparametric flow cytometry (MFC) helps diagnose MDS, especially when other features do not con...

HybridSNN: Combining Bio-Machine Strengths by Boosting Adaptive Spiking Neural Networks.

IEEE transactions on neural networks and learning systems
Spiking neural networks (SNNs), inspired by the neuronal network in the brain, provide biologically relevant and low-power consuming models for information processing. Existing studies either mimic the learning mechanism of brain neural networks as c...

ECG and EEG based detection and multilevel classification of stress using machine learning for specified genders: A preliminary study.

PloS one
Mental health, especially stress, plays a crucial role in the quality of life. During different phases (luteal and follicular phases) of the menstrual cycle, women may exhibit different responses to stress from men. This, therefore, may have an impac...

Are there accurate and legitimate ways to machine-quantify predatoriness, or an urgent need for an automated online tool?

Accountability in research
Yamada and Teixeira da Silva voiced valid concerns with the inadequacies of an online machine learning-based tool to detect predatory journals, and stressed on the urgent need for an automated, open, online-based semi-quantitative system that measure...

Self-orienting in human and machine learning.

Nature human behaviour
A current proposal for a computational notion of self is a representation of one's body in a specific time and place, which includes the recognition of that representation as the agent. This turns self-representation into a process of self-orientatio...

Crash injury severity prediction considering data imbalance: A Wasserstein generative adversarial network with gradient penalty approach.

Accident; analysis and prevention
For each road crash event, it is necessary to predict its injury severity. However, predicting crash injury severity with the imbalanced data frequently results in ineffective classifier. Due to the rarity of severe injuries in road traffic crashes, ...

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation.

Journal of medical Internet research
BACKGROUND: The reporting of machine learning (ML) prognostic and diagnostic modeling studies is often inadequate, making it difficult to understand and replicate such studies. To address this issue, multiple consensus and expert reporting guidelines...

Electroencephalogram (EEG) based prediction of attention deficit hyperactivity disorder (ADHD) using machine learning.

Applied neuropsychology. Adult
"Attention-Deficit Hyperactivity Disorder (ADHD)" is a neuro-developmental disorder in children under 12 years old. Learning deficits, anxiety, depression, sensory processing disorder, and oppositional defiant disorder are the most frequent comorbidi...

Artificial intelligence in rare disease diagnosis and treatment.

Clinical and translational science
Artificial intelligence (AI) utilization in health care has grown over the past few years. It also has demonstrated potential in improving the efficiency of diagnosis and treatment. Some types of AI, such as machine learning, allow for the efficient ...

Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation.

IEEE transactions on bio-medical engineering
OBJECTIVE: The scarcity of high-quality annotated data is omnipresent in machine learning. Especially in biomedical segmentation applications, experts need to spend a lot of their time into annotating due to the complexity. Hence, methods to reduce s...