AIMC Topic: Humans

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Efficient Perturbation Inference and Expandable Network for continual learning.

Neural networks : the official journal of the International Neural Network Society
Although humans are capable of learning new tasks without forgetting previous ones, most neural networks fail to do so because learning new tasks could override the knowledge acquired from previous data. In this work, we alleviate this issue by propo...

Natural Language Processing Model for Identifying Critical Findings-A Multi-Institutional Study.

Journal of digital imaging
Improving detection and follow-up of recommendations made in radiology reports is a critical unmet need. The long and unstructured nature of radiology reports limits the ability of clinicians to assimilate the full report and identify all the pertine...

Low-latency label-free image-activated cell sorting using fast deep learning and AI inferencing.

Biosensors & bioelectronics
Classification and sorting of cells using image-activated cell sorting (IACS) systems can bring significant insight to biomedical sciences. Incorporating deep learning algorithms into IACS enables cell classification and isolation based on complex an...

PrivacyMask: Real-world privacy protection in face ID systems.

Mathematical biosciences and engineering : MBE
Recent works have illustrated that many facial privacy protection methods are effective in specific face recognition algorithms. However, the COVID-19 pandemic has promoted the rapid innovation of face recognition algorithms for face occlusion, espec...

From sMRI to task-fMRI: A unified geometric deep learning framework for cross-modal brain anatomo-functional mapping.

Medical image analysis
Achieving predictions of brain functional activation patterns/task-fMRI maps from its underlying anatomy is an important yet challenging problem. Once successful, it will not only open up new ways to understand how brain anatomy influences functional...

Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.

Medical image analysis
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks (DNNs) require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the a...

Percutaneous Fixation of Levine-Edwards Type II Hangman's Fractures Under the Guidance of an Orthopedic Robot.

Orthopedics
There is no consensus regarding the optimal treatment for unstable hangman's fractures. Conservative treatment, although time-consuming and associated with complications such as nonunion, neck stiffness, and pseudarthrosis formation, is still preferr...

Multimodal medical image fusion algorithm based on pulse coupled neural networks and nonsubsampled contourlet transform.

Medical & biological engineering & computing
Combining two medical images from different modalities is more helpful for using the resulting image in the healthcare field. Medical image fusion means combining two or more images coming from multiple sensors. This technology obtains an output imag...