AIMC Topic: Animals

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A demonstration of unsupervised machine learning in species delimitation.

Molecular phylogenetics and evolution
One major challenge to delimiting species with genetic data is successfully differentiating population structure from species-level divergence, an issue exacerbated in taxa inhabiting naturally fragmented habitats. Many fields of science are now usin...

Deep learning reveals untapped information for local white-matter fiber reconstruction in diffusion-weighted MRI.

Magnetic resonance imaging
PURPOSE: Diffusion-weighted magnetic resonance imaging (DW-MRI) is of critical importance for characterizing in-vivo white matter. Models relating microarchitecture to observed DW-MRI signals as a function of diffusion sensitization are the lens thro...

If machines can learn, who needs scientists?

Journal of magnetic resonance (San Diego, Calif. : 1997)
Machine learning has been used in NMR in for decades, but recent developments signal explosive growth is on the horizon. An obstacle to the application of machine learning in NMR is the relative paucity of available training data, despite the existen...

A comparison of three data mining time series models in prediction of monthly brucellosis surveillance data.

Zoonoses and public health
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health planning. The present study investigated and compared the performance of the three data mining techniqu...

Bayesian Computation through Cortical Latent Dynamics.

Neuron
Statistical regularities in the environment create prior beliefs that we rely on to optimize our behavior when sensory information is uncertain. Bayesian theory formalizes how prior beliefs can be leveraged and has had a major impact on models of per...

Advancing Drug Discovery via Artificial Intelligence.

Trends in pharmacological sciences
Drug discovery and development are among the most important translational science activities that contribute to human health and wellbeing. However, the development of a new drug is a very complex, expensive, and long process which typically costs 2....

Magnetically Actuated Heterogeneous Microcapsule-Robot for the Construction of 3D Bioartificial Architectures.

ACS applied materials & interfaces
Core-shell microcapsules as one type of the most attractive carriers and reactors have been widely applied in the fields of drug screening and tissue engineering owing to their excellent biocompatibility and semi-permeability. Yet, the spatial organi...

Photomorphogenesis for robot self-assembly: adaptivity, collective decision-making, and self-repair.

Bioinspiration & biomimetics
Self-assembly in biology is an inspiration for engineered large-scale multi-modular systems with desirable characteristics, such as robustness, scalability, and adaptivity. Previous works have shown that simple mobile robots can be used to emulate an...

AI- modelling of molecular identification and feminization of wolbachia infected Aedes aegypti.

Progress in biophysics and molecular biology
BACKGROUND: The genetic control strategies of vector borne diseases includes the replacement of a vector population by "disease-refractory" mosquitoes and the release of mosquitoes with a gene to control the vector's reproduction rates. Wolbachia are...

Recurrent neural networks for hydrodynamic imaging using a 2D-sensitive artificial lateral line.

Bioinspiration & biomimetics
The lateral line is a mechanosensory organ found in fish and amphibians that allows them to sense and act on their near-field hydrodynamic environment. We present a 2D-sensitive artificial lateral line (ALL) comprising eight all-optical flow sensors,...