AIMC Topic: Animals

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Comparison of visual quantities in untrained neural networks.

Cell reports
The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed even in newborn animals. However, how this function originates in the brain, even before visual experience, remains unknown. Here, ...

An innovative ensemble model based on deep learning for predicting COVID-19 infection.

Scientific reports
Nowadays, global public health crises are occurring more frequently, and accurate prediction of these diseases can reduce the burden on the healthcare system. Taking COVID-19 as an example, accurate prediction of infection can assist experts in effec...

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.

Investigative radiology
OBJECTIVES: Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic images beyond that attainable with the standard doses of contrast agents (CAs) normally used in the clinic, thus potentially increasing diagnostic power...

Preliminary experience with robotic cholecystectomy illustrates feasibility in a canine cadaver model.

American journal of veterinary research
OBJECTIVE: To evaluate the feasibility and describe the relevant differences between robotic cholecystectomy (RC) and laparoscopic cholecystectomy in a canine model.

Memristive Neural Networks for Predicting Seizure Activity.

Sovremennye tekhnologii v meditsine
UNLABELLED: is to assess the possibilities of predicting epileptiform activity using the neuronal activity data recorded from the hippocampus and medial entorhinal cortex of mice with chronic epileptiform activity. To reach this goal, a deep artific...

Submillimeter Multifunctional Ferromagnetic Fiber Robots for Navigation, Sensing, and Modulation.

Advanced healthcare materials
Small-scale robots capable of remote active steering and navigation offer great potential for biomedical applications. However, the current design and manufacturing procedure impede their miniaturization and integration of various diagnostic and ther...

DeepSATA: A Deep Learning-Based Sequence Analyzer Incorporating the Transcription Factor Binding Affinity to Dissect the Effects of Non-Coding Genetic Variants.

International journal of molecular sciences
Utilizing large-scale epigenomics data, deep learning tools can predict the regulatory activity of genomic sequences, annotate non-coding genetic variants, and uncover mechanisms behind complex traits. However, these tools primarily rely on human or ...

Prediction of gastrointestinal functional state based on myoelectric recordings utilizing a deep neural network architecture.

PloS one
Functional and motility-related gastrointestinal (GI) disorders affect nearly 40% percent of the population. Disturbances of GI myoelectric activity have been proposed to play a significant role in these disorders. A significant barrier to usage of t...

Feasibility of intra-operative image guidance in burn excision surgery with multispectral imaging and deep learning.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Exposing a healthy wound bed for skin grafting is an important step during burn surgery to ensure graft take and maintain good functional outcomes. Currently, the removal of non-viable tissue in the burn wound bed during excision is deter...

Rapid eye movement sleep loss associated cytomorphometric changes and neurodegeneration.

Sleep medicine
Rapid eye movement sleep (REMS) is essential for leading normal healthy living at least in higher-order mammals, including humans. In this review, we briefly survey the available literature for evidence linking cytomorphometric changes in the brain d...