AIMC Topic: Machine Learning

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DiversityScanner: Robotic handling of small invertebrates with machine learning methods.

Molecular ecology resources
Invertebrate biodiversity remains poorly understood although it comprises much of the terrestrial animal biomass, most species and supplies many ecosystem services. The main obstacle is specimen-rich samples obtained with quantitative sampling techni...

Advancing primary care with Artificial Intelligence and Machine Learning.

Healthcare (Amsterdam, Netherlands)
Primary care is the largest healthcare delivery platform in the US. Facing the Artificial Intelligence and Machine Learning technology (AI/ML) revolution, the primary care community would benefit from a roadmap revealing priority areas and opportunit...

A literature review of machine learning algorithms for crash injury severity prediction.

Journal of safety research
INTRODUCTION: Road traffic crashes represent a major public health concern, so it is of significant importance to understand the factors associated with the increase of injury severity of its interveners when involved in a road crash. Determining suc...

Artificial intelligence based methods for hot spot prediction.

Current opinion in structural biology
Proteins interact through their interfaces to fulfill essential functions in the cell. They bind to their partners in a highly specific manner and form complexes that have a profound effect on understanding the biological pathways they are involved i...

An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology.

Medical & biological engineering & computing
Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue p...

Machine learning and deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry.

Future medicinal chemistry
Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) h...

MLCV: Bridging Machine-Learning-Based Dimensionality Reduction and Free-Energy Calculation.

Journal of chemical information and modeling
Importance-sampling algorithms leaning on the definition of a model reaction coordinate (RC) are widely employed to probe processes relevant to chemistry and biology alike, spanning time scales not amenable to common, brute-force molecular dynamics (...

Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning.

IEEE transactions on bio-medical engineering
Pain assessment in children continues to challenge clinicians and researchers, as subjective experiences of pain require inference through observable behaviors, both involuntary and deliberate. The presented approach supplements the subjective self-r...

Transparent Photovoltaics for Self-Powered Bioelectronics and Neuromorphic Applications.

The journal of physical chemistry letters
Inspired by the brain, future computation depends on creating a neuromorphic device that is energy-efficient for information processing and capable of sensing and learning. The current computation-chip platform is not capable of self-power and neurom...