Care of terminally ill / Palliative care

Responsive Hydrogel-Based Modular Microrobots for Multi-Functional Micromanipulation.

Microrobots show great potential in biomedical applications such as drug delivery and cell manipulations. However, current microrobots are mostly fabricated as a single entity and type and the tasks they can perform are limited. In this paper, modular microrobots, with an overall size of 120 µm × 200 µm, are proposed with responsive mating components, made from stimuli-responsive hydrogels, and ap...

Wall-climbing performance of gecko-inspired robot with soft feet and digits enhanced by gravity compensation.

Gravitational forces can induce deviations in body posture from desired configurations in multi-legged arboreal robot locomotion with low leg stiffness, affecting the contact angle between the swing leg's end-effector and the climbing surface during the gait cycle. The relationship between desired and actual foot positions is investigated here in a leg-stiffness-enhanced model under external force...

Detection and Localization of Spine Disorders from Plain Radiography.

Spine disorders can cause severe functional limitations, including back pain, decreased pulmonary function, and increased mortality risk. Plain radiog...

STaRNet: A spatio-temporal and Riemannian network for high-performance motor imagery decoding.

Brain-computer interfaces (BCIs), representing a transformative form of human-computer interaction, empower users to interact directly with external e...

GeneWorker: An end-to-end robotic reinforcement learning approach with collaborative generator and worker networks.

Reinforcement learning aided by the skill conception exhibits potent capabilities in guiding autonomous agents toward acquiring meaningful behaviors. ...

CAManim: Animating end-to-end network activation maps.

Deep neural networks have been widely adopted in numerous domains due to their high performance and accessibility to developers and application-specif...

End-to-end pseudonymization of fine-tuned clinical BERT models : Privacy preservation with maintained data utility.

Many state-of-the-art results in natural language processing (NLP) rely on large pre-trained language models (PLMs). These models consist of large amo...

An end-to-end multi-task motor imagery EEG classification neural network based on dynamic fusion of spectral-temporal features.

Electroencephalograph (EEG) brain-computer interfaces (BCI) have potential to provide new paradigms for controlling computers and devices. The accurac...

Artificial Intelligence in Drug Identification and Validation: A Scoping Review.

The end-to-end process in the discovery of drugs involves therapeutic candidate identification, validation of identified targets, identification of hi...

Reinforcement learning-guided control strategies for CAR T-cell activation and expansion.

Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of ...

PyHFO: lightweight deep learning-powered end-to-end high-frequency oscillations analysis application.

. This study aims to develop and validate an end-to-end software platform, PyHFO, that streamlines the application of deep learning (DL) methodologies...

Characterization of clinical data for patient stratification in moderate osteoarthritis with support vector machines, regulatory network models, and verification against osteoarthritis Initiative data.

Knee osteoarthritis (OA) diagnosis is based on symptoms, assessed through questionnaires such as the WOMAC. However, the inconsistency of pain recordi...

Epileptic Seizure Prediction Using Spatiotemporal Feature Fusion on EEG.

Electroencephalography (EEG) plays a crucial role in epilepsy analysis, and epileptic seizure prediction has significant value for clinical treatment ...

Oscillating latent dynamics in robot systems during walking and reaching.

Sensorimotor control of complex, dynamic systems such as humanoids or quadrupedal robots is notoriously difficult. While artificial systems traditiona...

Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality.

. To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mam...

ECG waveform generation from radar signals: A deep learning perspective.

Cardiovascular diagnostics relies heavily on the ECG (ECG), which reveals significant information about heart rhythm and function. Despite their signi...

HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos.

In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essential foundation for diagnosing congenital heart dise...

Motion correction and super-resolution for multi-slice cardiac magnetic resonance imaging via an end-to-end deep learning approach.

Accurate reconstruction of a high-resolution 3D volume of the heart is critical for comprehensive cardiac assessments. However, cardiac magnetic reson...

End-to-End Ultrasonic Hand Gesture Recognition.

As the number of electronic gadgets in our daily lives is increasing and most of them require some kind of human interaction, this demands innovative,...

Joint reconstruction and segmentation in undersampled 3D knee MRI combining shape knowledge and deep learning.

Task-adapted image reconstruction methods using end-to-end trainable neural networks (NNs) have been proposed to optimize reconstruction for subsequen...