Care of terminally ill / Palliative care

Beyond motor recovery after stroke: The role of hand robotic rehabilitation plus virtual reality in improving cognitive function.

Robot-assisted hand training adopting end-effector devices results in an additional reduction of motor impairment in comparison to usual care alone in different stages of stroke recovery. These devices often allow the patient to perform practical, attentive, and visual-spatial tasks in a semi-virtual reality (VR) setting. We aimed to investigate whether the hand end-effector robotic device Amadeo ...

Disruptive innovations in the clinical laboratory: catching the wave of precision diagnostics.

Disruptive innovation is an invention that disrupts an existing market and creates a new one by providing a different set of values, which ultimately overtakes the existing market. Typically, when disruptive innovations are introduced, their performance is initially less than existing standard technologies, but because of their ability to bring the cost down, and with gradual improvement, they end...

Reversal of thoracic sympathectomy through robot-assisted microsurgical sympathetic trunk reconstruction with sural nerve graft and additional end-to-side coaptation of the intercostal nerves: A case report.

Thoracic sympathectomy to treat palmar hyperhidrosis (PH) has widely been performed. Many patients regret the surgery due to compensatory hyperhidrosi...

End-to-end learnable EEG channel selection for deep neural networks with Gumbel-softmax.

To develop an efficient, embedded electroencephalogram (EEG) channel selection approach for deep neural networks, allowing us to match the channel sel...

Molecule Edit Graph Attention Network: Modeling Chemical Reactions as Sequences of Graph Edits.

The central challenge in automated synthesis planning is to be able to generate and predict outcomes of a diverse set of chemical reactions. In partic...

Human-in-the-Loop Low-Shot Learning.

We consider a human-in-the-loop scenario in the context of low-shot learning. Our approach was inspired by the fact that the viability of samples in n...

General Purpose Low-Level Reinforcement Learning Control for Multi-Axis Rotor Aerial Vehicles.

This paper proposes a multipurpose reinforcement learning based low-level multirotor unmanned aerial vehicles control structure constructed using neur...

BBNet: A Novel Convolutional Neural Network Structure in Edge-Cloud Collaborative Inference.

Edge-cloud collaborative inference can significantly reduce the delay of a deep neural network (DNN) by dividing the network between mobile edge and c...

Effect of age and sex on fully automated deep learning assessment of left ventricular function, volumes, and contours in cardiac magnetic resonance imaging.

Deep learning algorithms for left ventricle (LV) segmentation are prone to bias towards the training dataset. This study assesses sex- and age-depende...

Towards Semantic Integration of Machine Vision Systems to Aid Manufacturing Event Understanding.

A manufacturing paradigm shift from conventional control pyramids to decentralized, service-oriented, and cyber-physical systems (CPSs) is taking plac...

Stability threshold during seated balancing is sensitive to low back pain and safe to assess.

Challenging trunk neuromuscular control maximally using a seated balancing task is useful for unmasking impairments that may go unnoticed with traditi...

End-to-end deep learning nonrigid motion-corrected reconstruction for highly accelerated free-breathing coronary MRA.

PURPOSE: To develop an end-to-end deep learning technique for nonrigid motion-corrected (MoCo) reconstruction of ninefold undersampled free-breathing ...

Deep Learning-Based End-to-End Diagnosis System for Avascular Necrosis of Femoral Head.

As the first diagnostic imaging modality of avascular necrosis of the femoral head (AVNFH), accurately staging AVNFH from a plain radiograph is critic...

The Physiological Deep Learner: First application of multitask deep learning to predict hypotension in critically ill patients.

Critical care clinicians are trained to analyze simultaneously multiple physiological parameters to predict critical conditions such as hemodynamic in...

Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Early identification of resource needs is instrumental in promoting efficient hospital resource management. Hospital information systems, and electron...

End-to-end deep learning for recognition of ploidy status using time-lapse videos.

PURPOSE: Our retrospective study is to investigate an end-to-end deep learning model in identifying ploidy status through raw time-lapse video.

Statistical methods versus machine learning techniques for donor-recipient matching in liver transplantation.

Donor-Recipient (D-R) matching is one of the main challenges to be fulfilled nowadays. Due to the increasing number of recipients and the small amount...

Force-Free Control for Direct Teaching of a Surgical Assistant Robot End Effector with Wire-Driven Bidirectional Telescopic Mechanism.

This paper shows the design and modeling of an end effector with a bidirectional telescopic mechanism to allow a surgical assistant robot to hold and ...

Thoracic Point-of-Care Ultrasound: A SARS-CoV-2 Data Repository for Future Artificial Intelligence and Machine Learning.

Current experience suggests that artificial intelligence (AI) and machine learning (ML) may be useful in the management of hospitalized patients, incl...

CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction.

Residue co-evolution has become the primary principle for estimating inter-residue distances of a protein, which are crucially important for predictin...