AIMC Topic: Mice

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LiftPose3D, a deep learning-based approach for transforming two-dimensional to three-dimensional poses in laboratory animals.

Nature methods
Markerless three-dimensional (3D) pose estimation has become an indispensable tool for kinematic studies of laboratory animals. Most current methods recover 3D poses by multi-view triangulation of deep network-based two-dimensional (2D) pose estimate...

Deep-learning-based motion correction in optical coherence tomography angiography.

Journal of biophotonics
Optical coherence tomography angiography (OCTA) is a widely applied tool to image microvascular networks with high spatial resolution and sensitivity. Due to limited imaging speed, the artifacts caused by tissue motion can severely compromise visuali...

A database and deep learning toolbox for noise-optimized, generalized spike inference from calcium imaging.

Nature neuroscience
Inference of action potentials ('spikes') from neuronal calcium signals is complicated by the scarcity of simultaneous measurements of action potentials and calcium signals ('ground truth'). In this study, we compiled a large, diverse ground truth da...

Interpreting wide-band neural activity using convolutional neural networks.

eLife
Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires considerable knowledge about the nature of the repres...

Development of quantitative model of a local lymph node assay for evaluating skin sensitization potency applying machine learning CatBoost.

Regulatory toxicology and pharmacology : RTP
The estimated concentrations for a stimulation index of 3 (EC3) in murine local lymph node assay (LLNA) is an important quantitative value for determining the strength of skin sensitization to chemicals, including cosmetic ingredients. However, anima...

A deep learning approach to quantify auditory hair cells.

Hearing research
Hearing loss affects millions of people worldwide. Yet, there are still no curative therapies for sensorineural hearing loss. Frequent causes of sensorineural hearing loss are due to damage or loss of the sensory hair cells, the spiral ganglion neuro...

A deep learning algorithm for sleep stage scoring in mice based on a multimodal network with fine-tuning technique.

Neuroscience research
Sleep stage scoring is important to determine sleep structure in preclinical and clinical research. The aim of this study was to develop an automatic sleep stage classification system for mice with a new deep neural network algorithm. For the purpose...

An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging.

Nature aging
While many diseases of aging have been linked to the immunological system, immune metrics capable of identifying the most at-risk individuals are lacking. From the blood immunome of 1,001 individuals aged 8-96 years, we developed a deep-learning meth...

Partial information decomposition reveals that synergistic neural integration is greater downstream of recurrent information flow in organotypic cortical cultures.

PLoS computational biology
The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration-a type of co...