AIMC Topic: Machine Learning

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Multi-task prediction of infant cognitive scores from longitudinal incomplete neuroimaging data.

NeuroImage
Early postnatal brain undergoes a stunning period of development. Over the past few years, research on dynamic infant brain development has received increased attention, exhibiting how important the early stages of a child's life are in terms of brai...

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

Computers in biology and medicine
A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biop...

Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging.

Nature communications
Cell protrusion is morphodynamically heterogeneous at the subcellular level. However, the mechanism of cell protrusion has been understood based on the ensemble average of actin regulator dynamics. Here, we establish a computational framework called ...

Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access.

Journal of medical Internet research
BACKGROUND: On December 6 and 7, 2017, the US Department of Health and Human Services (HHS) hosted its first Code-a-Thon event aimed at leveraging technology and data-driven solutions to help combat the opioid epidemic. The authors—an interdisciplina...

How Much Does Movement and Location Encoding Impact Prefrontal Cortex Activity? An Algorithmic Decoding Approach in Freely Moving Rats.

eNeuro
Specialized brain structures encode spatial locations and movements, yet there is growing evidence that this information is also represented in the rodent medial prefrontal cortex (mPFC). Disambiguating such information from the encoding of other typ...

Control of Gene Regulatory Networks Using Bayesian Inverse Reinforcement Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Control of gene regulatory networks (GRNs) to shift gene expression from undesirable states to desirable ones has received much attention in recent years. Most of the existing methods assume that the cost of intervention at each state and time point,...

Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning.

NMR in biomedicine
The diffusion-weighted (DW) MR signal sampled over a wide range of b-values potentially allows for tissue differentiation in terms of cellularity, microstructure, perfusion, and T relaxivity. This study aimed to implement a machine learning algorithm...

Intuitive Assessment of Mortality Based on Facial Characteristics: Behavioral, Electrocortical, and Machine Learning Analyses.

Explore (New York, N.Y.)
Studies of various characteristics of the human face indicate that it contains a wealth of information about health status. Most studies involve objective measurement of facial features as correlated with historical health information. But some indiv...