AIMC Topic: Humans

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Robot-assisted flexible needle insertion using universal distributional deep reinforcement learning.

International journal of computer assisted radiology and surgery
PURPOSE: Flexible needle insertion is an important minimally invasive surgery approach for biopsy and radio-frequency ablation. This approach can minimize intraoperative trauma and improve postoperative recovery. We propose a new path planning framew...

A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification.

International journal of computer assisted radiology and surgery
PURPOSE: Diagnosis of lung cancer requires radiologists to review every lung nodule in CT images. Such a process can be very time-consuming, and the accuracy is affected by many factors, such as experience of radiologists and available diagnosis time...

Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.

European journal of nuclear medicine and molecular imaging
PURPOSE: Although functional brain imaging has been used for the early and objective assessment of cognitive dysfunction, there is a lack of generalized image-based biomarker which can evaluate individual's cognitive dysfunction in various disorders....

DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

Nature methods
We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves t...

The Effect of Optic Flow Speed on Active Participation During Robot-Assisted Treadmill Walking in Healthy Adults.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This study aimed to investigate: 1) the effect of optic flow speed manipulation on active participation during robot-assisted treadmill walking (RATW), 2) the influence of the type of virtual environment, and 3) the level of motion sickness and enjoy...

Machine learning for the prediction of acute kidney injury and paraplegia after thoracoabdominal aortic aneurysm repair.

Journal of cardiac surgery
OBJECTIVE: Prediction of acute renal failure (ARF) and paraplegia after thoracoabdominal aortic aneurysm repair (TAAAR) is helpful for decision-making during the postoperative phase. To find a more efficient method for making a prediction, we perform...

Finding Reactive Configurations: A Machine Learning Approach for Estimating Energy Barriers Applied to Sirtuin 5.

Journal of chemical theory and computation
Sirtuin 5 is a class III histone deacetylase that, unlike its classification, mainly catalyzes desuccinylation and demanoylation reactions. It is an interesting drug target that we use here to test new ideas for calculating reaction pathways of large...

Automated detection of hippocampal sclerosis using clinically empirical and radiomics features.

Epilepsia
OBJECTIVE: Temporal lobe epilepsy is a common form of epilepsy that might be amenable to surgery. However, magnetic resonance imaging (MRI)-negative hippocampal sclerosis (HS) can hamper early diagnosis and surgical intervention for patients in clini...