AIMC Topic: Machine Learning

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ATNAS: Automatic Termination for Neural Architecture Search.

Neural networks : the official journal of the International Neural Network Society
Neural architecture search (NAS) is a framework for automating the design process of a neural network structure. While the recent one-shot approaches have reduced the search cost, there still exists an inherent trade-off between cost and performance....

Transfer Learning on Electromyography (EMG) Tasks: Approaches and Beyond.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Machine learning on electromyography (EMG) has recently achieved remarkable success on various tasks, while such success relies heavily on the assumption that the training and future data must be of the same data distribution. However, this assumptio...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

Progress in biophysics and molecular biology
The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these mass effects, unruptured aneurysms frequently generate symptoms, how...

A machine learning approach to predict cellular mechanical stresses in response to chemical perturbation.

Biophysical journal
Mechanical stresses generated at the cell-cell level and cell-substrate level have been suggested to be important in a host of physiological and pathological processes. However, the influence various chemical compounds have on the mechanical stresses...

Discovery of novel TRPV1 modulators through machine learning-based molecular docking and molecular similarity searching.

Chemical biology & drug design
The transient receptor potential vanilloid 1 (TRPV1) channel belongs to the transient receptor potential channel superfamily and participates in many physiological processes. TRPV1 modulators (both agonists and antagonists) can effectively inhibit pa...

Virtual screening strategy for anti-DPP-IV natural flavonoid derivatives based on machine learning.

Journal of biomolecular structure & dynamics
Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for their antidiabetic effects. However, the variety of natural flavonoid derivatives is very rich, and even subtle structural differences can lead to seve...

Machine learning-guided REIMS pattern recognition of non-dairy cream, milk fat cream and whipping cream for fraudulence identification.

Food chemistry
The illegal adulteration of non-dairy cream in milk fat cream during the manufacturing process of baked goods has significantly hindered the robust growth of the dairy industry. In this study, a method based on rapid evaporative ionization mass spect...

Machine Learning Classification of Psychiatric Data Associated with Compensation Claims for Patient Injuries.

Methods of information in medicine
BACKGROUND: Adverse events are common in health care. In psychiatric treatment, compensation claims for patient injuries appear to be less common than in other medical specialties. The most common types of patient injury claims in psychiatry include ...

Generative Adversarial Networks in Medicine: Important Considerations for this Emerging Innovation in Artificial Intelligence.

Annals of biomedical engineering
The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations....