AIMC Topic: Machine Learning

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Federated Learning Optimization Algorithm for Automatic Weight Optimal.

Computational intelligence and neuroscience
Federated learning (FL), a distributed machine-learning framework, is poised to effectively protect data privacy and security, and it also has been widely applied in variety of fields in recent years. However, the system heterogeneity and statistical...

A Method for Expanding the Training Set of White Blood Cell Images.

Journal of healthcare engineering
In medicine, the count of different types of white blood cells can be used as the basis for diagnosing certain diseases or evaluating the treatment effects of diseases. The recognition and counting of white blood cells have important clinical signifi...

Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method.

Computers in biology and medicine
Drug targets must be identified and positioned correctly to research and manufacture new drugs. In this study, rather than using traditional methods for drug expansion, the drug target is determined using machine learning. Machine learning has genera...

A machine learning method for predicting the probability of MODS using only non-invasive parameters.

Computer methods and programs in biomedicine
OBJECTIVES: Timely and accurate prediction of multiple organ dysfunction syndrome (MODS) is essential for the rescue and treatment of trauma patients However, existing methods are invasive, easily affected by artifacts and can be difficult to perform...

Evaluation of machine learning methods for covariate data imputation in pharmacometrics.

CPT: pharmacometrics & systems pharmacology
Missing data create challenges in clinical research because they lead to loss of statistical power and potentially to biased results. Missing covariate data must be handled with suitable approaches to prepare datasets for pharmacometric analyses, suc...

Machine-Learning Classification of Pulse Waveform Quality.

Sensors (Basel, Switzerland)
Pulse measurements made using wearable devices can aid the monitoring of human physiological condition. Accurate estimation of waveforms is often difficult for nonexperts; motion artifacts may occur during tonometry measurements when the skin-sensor ...

Multiple instance neural networks based on sparse attention for cancer detection using T-cell receptor sequences.

BMC bioinformatics
Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to ...

Inverse design of core-shell particles with discrete material classes using neural networks.

Scientific reports
The design of scatterers on demand is a challenging task that requires the investigation and development of novel and flexible approaches. In this paper, we propose a machine learning-assisted optimization framework to design multi-layered core-shell...

Systematic tissue annotations of genomics samples by modeling unstructured metadata.

Nature communications
There are currently >1.3 million human -omics samples that are publicly available. This valuable resource remains acutely underused because discovering particular samples from this ever-growing data collection remains a significant challenge. The maj...