AIMC Topic: Machine Learning

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Machine Learning for Predicting Chemical Potentials of Multifunctional Organic Compounds in Atmospherically Relevant Solutions.

The journal of physical chemistry letters
We have trained the Extreme Minimum Learning Machine (EMLM) machine learning model to predict chemical potentials of individual conformers of multifunctional organic compounds containing carbon, hydrogen, and oxygen. The model is able to predict chem...

Review of Fundamental Active Current Extraction Techniques for SAPF.

Sensors (Basel, Switzerland)
The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods. Shunt active power filters are highly desirable...

Computer Vision and Machine Learning-Based Gait Pattern Recognition for Flat Fall Prediction.

Sensors (Basel, Switzerland)
BACKGROUND: Gait recognition has been applied in the prediction of the probability of elderly flat ground fall, functional evaluation during rehabilitation, and the training of patients with lower extremity motor dysfunction. Gait distinguishing betw...

Deep learning for religious and continent-based toxic content detection and classification.

Scientific reports
With time, numerous online communication platforms have emerged that allow people to express themselves, increasing the dissemination of toxic languages, such as racism, sexual harassment, and other negative behaviors that are not accepted in polite ...

3D multi-physics uncertainty quantification using physics-based machine learning.

Scientific reports
Quantitative predictions of the physical state of the Earth's subsurface are routinely based on numerical solutions of complex coupled partial differential equations together with estimates of the uncertainties in the material parameters. The resulti...

Predicting mortality in the very old: a machine learning analysis on claims data.

Scientific reports
Machine learning (ML) may be used to predict mortality. We used claims data from one large German insurer to develop and test differently complex ML prediction models, comparing them for their (balanced) accuracy, but also the importance of different...

OpenFL: the open federated learning library.

Physics in medicine and biology
Federated learning (FL) is a computational paradigm that enables organizations to collaborate on machine learning (ML) and deep learning (DL) projects without sharing sensitive data, such as patient records, financial data, or classified secrets.Open...

Artificial intelligence in musculoskeletal oncology imaging: A critical review of current applications.

Diagnostic and interventional imaging
Artificial intelligence (AI) is increasingly being studied in musculoskeletal oncology imaging. AI has been applied to both primary and secondary bone tumors and assessed for various predictive tasks that include detection, segmentation, classificati...

Conformal prediction under feedback covariate shift for biomolecular design.

Proceedings of the National Academy of Sciences of the United States of America
Many applications of machine-learning methods involve an iterative protocol in which data are collected, a model is trained, and then outputs of that model are used to choose what data to consider next. For example, a data-driven approach for designi...