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Care of terminally ill / Palliative care

Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.

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Fake metabolomics chromatogram generation for facilitating deep learning of peak-picking neural networks.

Finding peaks in chromatograms and determining their start and end points (peak picking) is a core t...

Transfer learning in deep neural network based under-sampled MR image reconstruction.

In Magnetic Resonance Imaging (MRI), the success of deep learning-based under-sampled MR image recon...

Updates on Deep Learning and Glioma: Use of Convolutional Neural Networks to Image Glioma Heterogeneity.

Deep learning represents end-to-end machine learning in which feature selection from images and clas...

Prediction of End-Of-Season Tuber Yield and Tuber Set in Potatoes Using In-Season UAV-Based Hyperspectral Imagery and Machine Learning.

Potato is the largest non-cereal food crop in the world. Timely estimation of end-of-season tuber pr...

Robotic Rehabilitation in Spinal Cord Injury: A Pilot Study on End-Effectors and Neurophysiological Outcomes.

Robot-aided gait training (RAGT) has been implemented to provide patients with spinal cord injury (S...

Pain intensity estimation based on a spatial transformation and attention CNN.

Models designed to detect abnormalities that reflect disease from facial structures are an emerging ...

Robot-assisted pelvic urologic surgeries: is it feasible to perform under reduced tilt?

To evaluate the feasibility and outcomes of performing robot-assisted pelvic surgery at a reduced an...

A robust and interpretable end-to-end deep learning model for cytometry data.

Cytometry technologies are essential tools for immunology research, providing high-throughput measur...

Improved recurrent neural network-based manipulator control with remote center of motion constraints: Experimental results.

In this paper, an improved recurrent neural network (RNN) scheme is proposed to perform the trajecto...

Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients.

Opioids play a critical role in acute postoperative pain management. Our objective was to develop ma...

An efficient end-to-end CNN for segmentation of bone surfaces from ultrasound.

The application of ultrasound (US) imaging in orthopedic surgery has always been a research directio...

Toward Task Autonomy in Robotic Cardiac Ablation: Learning-Based Kinematic Control of Soft Tendon-Driven Catheters.

The goal of this study was to propose and validate a control framework with level-2 autonomy (task a...

CAB U-Net: An end-to-end category attention boosting algorithm for segmentation.

With the development of machine learning and artificial intelligence, many convolutional neural netw...

Hiding a plane with a pixel: examining shape-bias in CNNs and the benefit of building in biological constraints.

When deep convolutional neural networks (CNNs) are trained "end-to-end" on raw data, some of the fea...

Machine-learning-based diagnostics of EEG pathology.

Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be cate...

Amino acid encoding for deep learning applications.

BACKGROUND: The number of applications of deep learning algorithms in bioinformatics is increasing a...

A Real-Time Depth of Anesthesia Monitoring System Based on Deep Neural Network With Large EDO Tolerant EEG Analog Front-End.

In this article, we present a real-time electroencephalogram (EEG) based depth of anesthesia (DoA) m...

An end-to-end exemplar association for unsupervised person Re-identification.

Tracklet association methods learn the cross camera retrieval ability though associating underlying ...

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