AIMC Topic: Machine Learning

Clear Filters Showing 26521 to 26530 of 34417 articles

Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: Critical care patient events like sepsis or septic shock in intensive care units (ICUs) are dangerous complications which can cause multiple organ failures and eventual death. Preventive prediction of such events will allow ...

Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder.

PloS one
The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-year old children in multiple US sites. To classify ASD, trained clinicians review developmental eval...

A ternary classification using machine learning methods of distinct estrogen receptor activities within a large collection of environmental chemicals.

The Science of the total environment
Endocrine-disrupting chemicals (EDCs), which can threaten ecological safety and be harmful to human beings, have been cause for wide concern. There is a high demand for efficient methodologies for evaluating potential EDCs in the environment. Herein ...

acdc - Automated Contamination Detection and Confidence estimation for single-cell genome data.

BMC bioinformatics
BACKGROUND: A major obstacle in single-cell sequencing is sample contamination with foreign DNA. To guarantee clean genome assemblies and to prevent the introduction of contamination into public databases, considerable quality control efforts are put...

Comparison of Classifier Architectures for Online Neural Spike Sorting.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
High-density, intracranial recordings from micro-electrode arrays need to undergo Spike Sorting in order to associate the recorded neuronal spikes to particular neurons. This involves spike detection, feature extraction, and classification. To reduce...

Toward amino acid typing for proteins in FFLUX.

Journal of computational chemistry
Continuing the development of the FFLUX, a multipolar polarizable force field driven by machine learning, we present a modern approach to atom-typing and building transferable models for predicting atomic properties in proteins. Amino acid atomic cha...

Robust differential expression analysis by learning discriminant boundary in multi-dimensional space of statistical attributes.

BMC bioinformatics
BACKGROUND: Performing statistical tests is an important step in analyzing genome-wide datasets for detecting genomic features differentially expressed between conditions. Each type of statistical test has its own advantages in characterizing certain...

Dendritic spine classification using shape and appearance features based on two-photon microscopy.

Journal of neuroscience methods
BACKGROUND: Neuronal morphology and function are highly coupled. In particular, dendritic spine morphology is strongly governed by the incoming neuronal activity. The first step towards understanding the structure-function relationships is to classif...