AIMC Topic: Animals

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Robot-Assisted SpiderMass for Real-Time Topography Mass Spectrometry Imaging.

Analytical chemistry
Mass spectrometry imaging (MSI) has shown to bring invaluable information for biological and clinical applications. However, conventional MSI is generally performed from tissue sections. Here, we developed a novel MS-based method for mass spectrome...

Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging.

NMR in biomedicine
Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classifying tumors based on their aggressiveness, but CEST contrast is complicated by multiple signal sources and thus prolonged acquisition times are often...

Microscale characterisation of the time-dependent mechanical behaviour of brain white matter.

Journal of the mechanical behavior of biomedical materials
Brain mechanics is a topic of deep interest because of the significant role of mechanical cues in both brain function and form. Specifically, capturing the heterogeneous and anisotropic behaviour of cerebral white matter (WM) is extremely challenging...

Application of Machine Learning to Predict Dielectric Properties of In Vivo Biological Tissue.

Sensors (Basel, Switzerland)
In this paper we revisited a database with measurements of the dielectric properties of rat muscles. Measurements were performed both in vivo and ex vivo; the latter were performed in tissues with varying levels of hydration. Dielectric property meas...

Prioritization of Mycotoxins Based on Their Genotoxic Potential with an In Silico-In Vitro Strategy.

Toxins
Humans are widely exposed to a great variety of mycotoxins and their mixtures. Therefore, it is important to design strategies that allow prioritizing mycotoxins based on their toxic potential in a time and cost-effective manner. A strategy combining...

Should we replace radiologists with deep learning? Pigeons, error and trust in medical AI.

Bioethics
The sudden rise in the ability of machine learning methodology, such as deep neural networks, to identify and predict with great accuracy instances of malignant cell growth from radiological images has led prominent developers of this technology, suc...

Meta-learning, social cognition and consciousness in brains and machines.

Neural networks : the official journal of the International Neural Network Society
The intersection between neuroscience and artificial intelligence (AI) research has created synergistic effects in both fields. While neuroscientific discoveries have inspired the development of AI architectures, new ideas and algorithms from AI rese...

Probabilistic generative modeling and reinforcement learning extract the intrinsic features of animal behavior.

Neural networks : the official journal of the International Neural Network Society
It is one of the ultimate goals of ethology to understand the generative process of animal behavior, and the ability to reproduce and control behavior is an important step in this field. However, it is not easy to achieve this goal in systems with co...

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer research
Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and identifying these patients is difficult due to a lack of reliable biomarkers for prediction and evaluation of treatment response. Here, we demonstrate th...

MesoNet allows automated scaling and segmentation of mouse mesoscale cortical maps using machine learning.

Nature communications
Understanding the basis of brain function requires knowledge of cortical operations over wide spatial scales and the quantitative analysis of brain activity in well-defined brain regions. Matching an anatomical atlas to brain functional data requires...