AIMC Topic: Humans

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Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound.

Journal of visualized experiments : JoVE
With the potential for high precision, dexterity, and repeatability, a self-tracked robotic system can be employed to assist the acquisition of real-time ultrasound. However, limited numbers of robots designed for extra-corporeal ultrasound have been...

Faster R-CNN and Geometric Transformation-Based Detection of Driver's Eyes Using Multiple Near-Infrared Camera Sensors.

Sensors (Basel, Switzerland)
Studies are being actively conducted on camera-based driver gaze tracking in a vehicle environment for vehicle interfaces and analyzing forward attention for judging driver inattention. In existing studies on the single-camera-based method, there are...

Machine Learning Models for the Prediction of Chemotherapy-Induced Peripheral Neuropathy.

Pharmaceutical research
PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) is a common adverse side effect of cancer chemotherapy that can be life debilitating and cause extreme pain. The multifactorial and poorly understood mechanisms of toxicity have impeded the i...

Effects of robot-assisted gait training in patients with Parkinson's disease: study protocol for a randomized controlled trial.

Trials
BACKGROUND: Robot-assisted gait training (RAGT) was developed to restore gait function by promoting neuroplasticity through repetitive locomotor training and has been utilized in gait training. However, contradictory outcomes of RAGT have been report...

A clinical text classification paradigm using weak supervision and deep representation.

BMC medical informatics and decision making
BACKGROUND: Automatic clinical text classification is a natural language processing (NLP) technology that unlocks information embedded in clinical narratives. Machine learning approaches have been shown to be effective for clinical text classificatio...

BO-LSTM: classifying relations via long short-term memory networks along biomedical ontologies.

BMC bioinformatics
BACKGROUND: Recent studies have proposed deep learning techniques, namely recurrent neural networks, to improve biomedical text mining tasks. However, these techniques rarely take advantage of existing domain-specific resources, such as ontologies. I...

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning ha...

MRI-based attenuation correction for brain PET/MRI based on anatomic signature and machine learning.

Physics in medicine and biology
Deriving accurate attenuation maps for PET/MRI remains a challenging problem because MRI voxel intensities are not related to properties of photon attenuation and bone/air interfaces have similarly low signal. This work presents a learning-based meth...

High-performance medicine: the convergence of human and artificial intelligence.

Nature medicine
The use of artificial intelligence, and the deep-learning subtype in particular, has been enabled by the use of labeled big data, along with markedly enhanced computing power and cloud storage, across all sectors. In medicine, this is beginning to ha...
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