AIMC Topic: Machine Learning

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DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

Methods (San Diego, Calif.)
As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to r...

Augmented outcome-weighted learning for estimating optimal dynamic treatment regimens.

Statistics in medicine
Dynamic treatment regimens (DTRs) are sequential treatment decisions tailored by patient's evolving features and intermediate outcomes at each treatment stage. Patient heterogeneity and the complexity and chronicity of many diseases call for learning...

Learning-Based Cell Injection Control for Precise Drop-on-Demand Cell Printing.

Annals of biomedical engineering
Drop-on-demand (DOD) printing is widely used in bioprinting for tissue engineering because of little damage to cell viability and cost-effectiveness. However, satellite droplets may be generated during printing, deviating cells from the desired posit...

Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival.

Statistics in medicine
Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric...

Artificial neural networks (ANNs) and partial least squares (PLS) regression in the quantitative analysis of cocrystal formulations by Raman and ATR-FTIR spectroscopy.

Journal of pharmaceutical and biomedical analysis
The present work describes the development of an efficient, fast and accurate method for the quantification of polymer-based cocrystal formulations. Specifically, the content of carbamazepine-nicotinamide (CBZ/NIC) and ibuprofen-nicotinamide (IBU/NIC...

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

Methods (San Diego, Calif.)
Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is s...

Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society
Environmental sustainability research is dependent on accurate land cover information. Even with the increased number of satellite systems and sensors acquiring data with improved spectral, spatial, radiometric and temporal characteristics and the ne...

The effect of machine learning regression algorithms and sample size on individualized behavioral prediction with functional connectivity features.

NeuroImage
Individualized behavioral/cognitive prediction using machine learning (ML) regression approaches is becoming increasingly applied. The specific ML regression algorithm and sample size are two key factors that non-trivially influence prediction accura...

Characterizing the SEMG patterns with myofascial pain using a multi-scale wavelet model through machine learning approaches.

Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology
In this paper, we introduce a newly developed multi-scale wavelet model for the interpretation of surface electromyography (SEMG) signals and validate the model's capability to characterize changes in neuromuscular activation in cases with myofascial...

Ischemic stroke lesion segmentation using stacked sparse autoencoder.

Computers in biology and medicine
Automatic segmentation of ischemic stroke lesion volumes from multi-spectral Magnetic Resonance Imaging (MRI) sequences plays a vital role in quantifying and locating the lesion region. Most existing methods mainly rely on designing hand-crafted feat...