AIMC Topic: Animals

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Machines That Feel and Think: The Role of Affective Feelings and Mental Action in (Artificial) General Intelligence.

Artificial life
What role do affective feelings (feelings/emotions/moods) play in adaptive behaviour? What are the implications of this for understanding and developing artificial general intelligence? Leading theoretical models of brain function are beginning to sh...

Intratumoral Resolution of Driver Gene Mutation Heterogeneity in Renal Cancer Using Deep Learning.

Cancer research
UNLABELLED: Intratumoral heterogeneity arising from tumor evolution poses significant challenges biologically and clinically. Dissecting this complexity may benefit from deep learning (DL) algorithms, which can infer molecular features from ubiquitou...

Fear memory-associated synaptic and mitochondrial changes revealed by deep learning-based processing of electron microscopy data.

Cell reports
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information of the brain with exceptional computational cost. Targeted reconstruction of subcellular structures from ssEM datasets is less computationally demandin...

A Novel Microsurgical Robot: Preliminary Feasibility Test in Ophthalmic Field.

Translational vision science & technology
PURPOSE: This study investigated the feasibility and potential advantage of using a new microsurgical teleoperated robot, Symani Surgical System, in the ophthalmology field. In particular, considering the extreme precision of the system and the dexte...

[Development of Nasal Continuum Minimally Invasive Surgical Robot System].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
In order to improve the operation difficulties in the narrow space of the nasal maxillary sinus, the nasal continuum minimally invasive surgical robot system is designed. The ball-and-socket joints and NiTiNol tubes are used as the main body of the c...

Convolutional neural network-based common-path optical coherence tomography A-scan boundary-tracking training and validation using a parallel Monte Carlo synthetic dataset.

Optics express
We present a parallel Monte Carlo (MC) simulation platform for rapidly generating synthetic common-path optical coherence tomography (CP-OCT) A-scan image dataset for image-guided needle insertion. The computation time of the method has been evaluate...

[Research on grading prediction model of traumatic hemorrhage volume based on deep learning].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To develop a grading prediction model of traumatic hemorrhage volume based on deep learning and assist in predicting traumatic hemorrhage volume.

Development of Needle Guide Unit Considering Buckling Bone-Perforation Control Strategy Based on Computed Tomography-Guided Needle Insertion Robot.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A computed tomography (CT)-guided robotic assistance system is useful for needle insertion into metastatic carcinoma of vertebrae, which has limited pathways. However, the use of conventional needles in this procedure can result in bone fracture in t...

Machine Learning Approaches to Classify Anatomical Regions in Rodent Brain from High Density Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Identifying different functional regions during a brain surgery is a challenging task usually performed by highly specialized neurophysiologists. Progress in this field may be used to improve in situ brain navigation and will serve as an important bu...

Learning to Segment Fine Structures Under Image-Level Supervision With an Application to Nematode Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Image segmentation models trained only with image-level labels have become increasingly popular as they require significantly less annotation effort than models trained with scribble, bounding box or pixel-wise annotations. While methods utilizing im...