AIMC Topic: Animals

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Looking with new eyes: advanced microscopy and artificial intelligence in reproductive medicine.

Journal of assisted reproduction and genetics
Microscopy has long played a pivotal role in the field of assisted reproductive technology (ART). The advent of artificial intelligence (AI) has opened the door for new approaches to sperm and oocyte assessment and selection, with the potential for i...

Breast tumor localization and segmentation using machine learning techniques: Overview of datasets, findings, and methods.

Computers in biology and medicine
The Global Cancer Statistics 2020 reported breast cancer (BC) as the most common diagnosis of cancer type. Therefore, early detection of such type of cancer would reduce the risk of death from it. Breast imaging techniques are one of the most frequen...

ANIMAL-SPOT enables animal-independent signal detection and classification using deep learning.

Scientific reports
Bioacoustic research spans a wide range of biological questions and applications, relying on identification of target species or smaller acoustic units, such as distinct call types. However, manually identifying the signal of interest is time-intensi...

Design and control of soft biomimetic pangasius fish robot using fin ray effect and reinforcement learning.

Scientific reports
Soft robots provide a pathway to accurately mimic biological creatures and be integrated into their environment with minimal invasion or disruption to their ecosystem. These robots made from soft deforming materials possess structural properties and ...

Artificial intelligence-driven identification of morin analogues acting as Ca1.2 channel blockers: Synthesis and biological evaluation.

Bioorganic chemistry
Morin is a vasorelaxant flavonoid, whose activity is ascribable to Ca1.2 channel blockade that, however, is weak as compared to that of clinically used therapeutic agents. A conventional strategy to circumvent this drawback is to synthesize new deriv...

Cross-species cell-type assignment from single-cell RNA-seq data by a heterogeneous graph neural network.

Genome research
Cross-species comparative analyses of single-cell RNA sequencing (scRNA-seq) data allow us to explore, at single-cell resolution, the origins of the cellular diversity and evolutionary mechanisms that shape cellular form and function. Cell-type assig...

Population codes enable learning from few examples by shaping inductive bias.

eLife
Learning from a limited number of experiences requires suitable inductive biases. To identify how inductive biases are implemented in and shaped by neural codes, we analyze sample-efficient learning of arbitrary stimulus-response maps from arbitrary ...

TIRESIA: An eXplainable Artificial Intelligence Platform for Predicting Developmental Toxicity.

Journal of chemical information and modeling
Herein, a robust and reproducible eXplainable Artificial Intelligence (XAI) approach is presented, which allows prediction of developmental toxicity, a challenging human-health endpoint in toxicology. The application of XAI as an alternative method i...

Artificial intelligence (AI): a new window to revamp the vector-borne disease control.

Parasitology research
Artificial intelligence (AI) facilitates scientists to devise intelligent machines that work and behave like humans to resolve difficulties and problems by utilizing minimal resources. The Healthcare sector has benefited due to this. Mosquito-transmi...

Electronic whiskers for velocity sensing based on the liquid metal hysteresis effect.

Soft matter
The artificial biomimetic sensory hair as state-of-art electronics has drawn great attention from academic theorists of industrial production given its potential application in soft robotics, environmental exploration and health monitoring. However, ...