Care of terminally ill / Palliative care

Pharm-AutoML: An open-source, end-to-end automated machine learning package for clinical outcome prediction.

Although there is increased interest in utilizing machine learning (ML) to support drug development, technical hurdles associated with complex algorithms have limited widespread adoption. In response, we have developed Pharm-AutoML, an open-source Python package that enables users to automate the construction of ML models and predict clinical outcomes, especially in the context of pharmacological ...

ELVISort: encoding latent variables for instant sorting, an artificial intelligence-based end-to-end solution.

The growing number of recording sites of silicon-based probes means that an increasing amount of neural cell activities can be recorded simultaneously, facilitating the investigation of underlying complex neural dynamics. In order to overcome the challenges generated by the increasing number of channels, highly automated signal processing tools are needed. Our goal was to build a spike sorting mod...

Development of a Planar Haptic Robot With Minimized Impedance.

Several studies have reported that stroke survivors displayed improved voluntary planar movements when forces supporting the upper limb increased, and...

Deep neural network-based generalized sidelobe canceller for dual-channel far-field speech recognition.

The traditional generalized sidelobe canceller (GSC) is a common speech enhancement front end to improve the noise robustness of automatic speech reco...

End-to-end keyword search system based on attention mechanism and energy scorer for low resource languages.

Keyword search (KWS) means searching for keywords given by the user from continuous speech. Conventional KWS systems are based on Automatic Speech Rec...

ncRFP: A Novel end-to-end Method for Non-Coding RNAs Family Prediction Based on Deep Learning.

Evidence has accumulated enough to prove non-coding RNAs (ncRNAs) play important roles in cellular biological processes and disease pathogenesis. High...

Design and independent training of composable and reusable neural modules.

Monolithic neural networks and end-to-end training have become the dominating trend in the field of deep learning, but the steady increase in complexi...

From convolutional neural networks to models of higher-level cognition (and back again).

The remarkable successes of convolutional neural networks (CNNs) in modern computer vision are by now well known, and they are increasingly being expl...

Imbalanced Loss-Integrated Deep-Learning-Based Ultrasound Image Analysis for Diagnosis of Rotator-Cuff Tear.

A rotator cuff tear (RCT) is an injury in adults that causes difficulty in moving, weakness, and pain. Only limited diagnostic tools such as magnetic ...

Speaker recognition based on deep learning: An overview.

Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. H...

Cycle consistent network for end-to-end style transfer TTS training.

In this paper, we propose a cycle consistent network based end-to-end TTS for speaking style transfer, including intra-speaker, inter-speaker, and uns...

Uncorrelated feature encoding for faster image style transfer.

Recent image style transfer methods use a pre-trained convolutional neural network as their feature encoder. However, the pre-trained network is not o...

Towards Robust Robot Control in Cartesian Space Using an Infrastructureless Head- and Eye-Gaze Interface.

This paper presents a lightweight, infrastructureless head-worn interface for robust and real-time robot control in Cartesian space using head- and ey...

Should Peritoneal Re-Approximation Be Performed After Transperitoneal Robot-Assisted Radical Prostatectomy?

The aim of the study is to examine the effect of peritoneal re-approximation or non-approximation on the postoperative course of patients at the end ...

Accurate age classification using manual method and deep convolutional neural network based on orthopantomogram images.

Age estimation is an important challenge in many fields, including immigrant identification, legal requirements, and clinical treatments. Deep learnin...

Simulated muscle activity in locomotion: implications of co-occurrence between effort minimisation and gait modularity for robot-assisted rehabilitation therapy.

Evolution of gait rehabilitation robotic devices for stroke survivors has aimed at providing transparency to user's efforts and implementing 'assist-a...

Deep learning techniques have significantly impacted protein structure prediction and protein design.

Protein structure prediction and design can be regarded as two inverse processes governed by the same folding principle. Although progress remained st...

End-to-end novel visual categories learning via auxiliary self-supervision.

Semi-supervised learning has largely alleviated the strong demand for large amount of annotations in deep learning. However, most of the methods have ...

A deep learning methodology for the automated detection of end-diastolic frames in intravascular ultrasound images.

Coronary luminal dimensions change during the cardiac cycle. However, contemporary volumetric intravascular ultrasound (IVUS) analysis is performed in...

Feasibility of the use of deep learning classification of teat-end condition in Holstein cattle.

Infections with pathogenic bacteria entering the mammary gland through the teat canal are the most common cause of mastitis in dairy cows; therefore, ...