AIMC Topic: Humans

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CT-based deep learning enables early postoperative recurrence prediction for intrahepatic cholangiocarcinoma.

Scientific reports
Preoperatively accurate evaluation of risk for early postoperative recurrence contributes to maximizing the therapeutic success for intrahepatic cholangiocarcinoma (iCCA) patients. This study aimed to investigate the potential of deep learning (DL) a...

Leveraging clinical data across healthcare institutions for continual learning of predictive risk models.

Scientific reports
The inherent flexibility of machine learning-based clinical predictive models to learn from episodes of patient care at a new institution (site-specific training) comes at the cost of performance degradation when applied to external patient cohorts. ...

Prediction of protein-protein interaction using graph neural networks.

Scientific reports
Proteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein-protein interactio...

A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology.

Nature communications
Epstein-Barr virus-associated gastric cancer (EBVaGC) shows a robust response to immune checkpoint inhibitors. Therefore, a cost-efficient and accessible tool is needed for discriminating EBV status in patients with gastric cancer. Here we introduce ...

Deep Learning Method for Grasping Novel Objects Using Dexterous Hands.

IEEE transactions on cybernetics
Robotic grasping ability lags far behind human skills and poses a significant challenge in the robotics research area. According to the grasping part of an object, humans can select the appropriate grasping postures of their fingers. When humans gras...

Unsupervised Visual-Textual Correlation Learning With Fine-Grained Semantic Alignment.

IEEE transactions on cybernetics
With the rapid growth of multimedia data on the Internet, there has been a rapid rise in the demand for visual-textual cross-media retrieval between images and sentences. However, the heterogeneous property of visual and textual data brings huge chal...

Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services.

IEEE transactions on cybernetics
Endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects, and moods of humans in their context is an important challenge, which requires sophisticated and novel approaches of emotion recognition. Most studi...

Predicting Network Controllability Robustness: A Convolutional Neural Network Approach.

IEEE transactions on cybernetics
Network controllability measures how well a networked system can be controlled to a target state, and its robustness reflects how well the system can maintain the controllability against malicious attacks by means of node removals or edge removals. T...

Data-Driven Real-Time Magnetic Tracking Applied to Myokinetic Interfaces.

IEEE transactions on biomedical circuits and systems
A new concept of human-machine interface to control hand prostheses based on displacements of multiple magnets implanted in the limb residual muscles, the myokinetic control interface, has been recently proposed. In previous works, magnets localizati...