AIMC Topic: Humans

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Study on the Effects of Different Seat and Leg Support Conditions of a Trunk Rehabilitation Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Performance of trunk rehabilitation exercises while sitting on movable surfaces with feet on the ground can increase trunk and leg muscle activations, and constraining the feet to move with the seat isolates control of the trunk. However, there are n...

Quantitative Patient-Reported Experience Measures Derived From Natural Language Processing Have a Normal Distribution and No Ceiling Effect.

Quality management in health care
BACKGROUND AND OBJECTIVES: Patient-reported experience measures have the potential to guide improvement in health care delivery. Many patient-reported experience measures are limited by the presence of strong ceiling effects that limit their analytic...

Machine learning predicts blood lactate levels in children after cardiac surgery in paediatric ICU.

Cardiology in the young
BACKGROUND: Although serum lactate levels are widely accepted markers of haemodynamic instability, an alternative method to evaluate haemodynamic stability/instability continuously and non-invasively may assist in improving the standard of patient ca...

Machine learning strategy identification: A paradigm to uncover decision strategies with high fidelity.

Behavior research methods
We propose a novel approach, which we call machine learning strategy identification (MLSI), to uncovering hidden decision strategies. In this approach, we first train machine learning models on choice and process data of one set of participants who a...

CardiSort: a convolutional neural network for cross vendor automated sorting of cardiac MR images.

European radiology
OBJECTIVES: To develop an image-based automatic deep learning method to classify cardiac MR images by sequence type and imaging plane for improved clinical post-processing efficiency.

An Interpretable Chest CT Deep Learning Algorithm for Quantification of COVID-19 Lung Disease and Prediction of Inpatient Morbidity and Mortality.

Academic radiology
RATIONALE AND OBJECTIVES: The burden of coronavirus disease 2019 (COVID-19) airspace opacities is time consuming and challenging to quantify on computed tomography. The purpose of this study was to evaluate the ability of a deep convolutional neural ...

The Multi-Institutional Experience in Single-Port Robotic Transvesical Simple Prostatectomy for Benign Prostatic Hyperplasia Management.

The Journal of urology
PURPOSE: Single-port (SP) robotic-assisted simple prostatectomy (RASP) through the transvesical approach is a novel surgical option in the management of large prostatic glands. We present the first multi-institutional study to further assess the peri...

The impact of transfer learning on 3D deep learning convolutional neural network segmentation of the hippocampus in mild cognitive impairment and Alzheimer disease subjects.

Human brain mapping
Research on segmentation of the hippocampus in magnetic resonance images through deep learning convolutional neural networks (CNNs) shows promising results, suggesting that these methods can identify small structural abnormalities of the hippocampus,...

Automatic prosthetic-parameter estimation from anteroposterior pelvic radiographs after total hip arthroplasty using deep learning-based keypoint detection.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: X-ray is a necessary tool for post-total hip arthroplasty (THA) check-ups; however, parameter measurements are time-consuming. We proposed a deep learning tool, BKNet that automates localization of landmarks with parameter measurements.