Care of terminally ill / Palliative care

DeepPET: A deep encoder-decoder network for directly solving the PET image reconstruction inverse problem.

The purpose of this research was to implement a deep learning network to overcome two of the major b...

Training Convolutional Neural Networks and Compressed Sensing End-to-End for Microscopy Cell Detection.

Automated cell detection and localization from microscopy images are significant tasks in biomedical...

A novel end-to-end brain tumor segmentation method using improved fully convolutional networks.

Accurate brain magnetic resonance imaging (MRI) tumor segmentation continues to be an active researc...

Learning joint space-time-frequency features for EEG decoding on small labeled data.

Brain-computer interfaces (BCIs), which control external equipment using cerebral activity, have rec...

Towards end-to-end likelihood-free inference with convolutional neural networks.

Complex simulator-based models with non-standard sampling distributions require sophisticated design...

End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning.

We study active object tracking, where a tracker takes visual observations (i.e., frame sequences) a...

Acceleration of spleen segmentation with end-to-end deep learning method and automated pipeline.

Delineation of Computed Tomography (CT) abdominal anatomical structure, specifically spleen segmenta...

SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging.

Automatic sleep staging has been often treated as a simple classification problem that aims at deter...

Harnessing networks and machine learning in neuropsychiatric care.

The development of next-generation therapies for neuropsychiatric illness will likely rely on a prec...

Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals.

Non-invasive, electroencephalography (EEG)-based brain-computer interfaces (BCIs) on motor imagery m...

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.

Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG workfl...

Effects of Two Doses of Organic Extract-Based Biostimulant on Greenhouse Lettuce Grown Under Increasing NaCl Concentrations.

The enhancement of plant tolerance toward abiotic stresses is increasingly being supported by the ap...

Effects of small tidal volume and positive end-expiratory pressure on oxygenation in pressure-controlled ventilation-volume guaranteed mode during one-lung ventilation.

BACKGROUND: The purpose of this study was to investigate whether tidal volume (TV) of 8 mL/kg withou...

Towards cross-modal organ translation and segmentation: A cycle- and shape-consistent generative adversarial network.

Synthesized medical images have several important applications. For instance, they can be used as an...

In vitro survival, growth, and maturation of sheep oocytes from secondary follicles cultured in serum-free conditions: impact of a constant or a sequential medium containing recombinant human FSH.

This study evaluated the in vitro development and maturation of ovine oocytes from secondary follicl...

Inter-subject transfer learning with an end-to-end deep convolutional neural network for EEG-based BCI.

OBJECTIVE: Despite the effective application of deep learning (DL) in brain-computer interface (BCI)...

Comparison of Muscular Activity and Movement Performance in Robot-Assisted and Freely Performed Exercises.

End-effector-based robotic systems are, in particular, suitable for extending physical therapy in st...

Natural language generation for electronic health records.

One broad goal of biomedical informatics is to generate fully-synthetic, faithfully representative e...

Use of a robotic walking aid in rehabilitation to reduce fear of falling is feasible and acceptable from the end user's perspective: A randomised comparative study.

Objectives To determine the acceptability and feasibility of the use of a robotic walking aid to sup...

Multi-level features combined end-to-end learning for automated pathological grading of breast cancer on digital mammograms.

We propose to discriminate the pathological grades directly on digital mammograms instead of patholo...

Response to Barry re: Learning Curves and Timing of Surgical Trials: Robotic Kidney Transplantation with Regional Hypothermia by Ahlawat et al. (From: Barry JM. J Endourolo 2018;32:1166; DOI: 1089/end.2018.0419).