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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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Showing 232-252 of 6,157 articles
Block-level dependency syntax based model for end-to-end aspect-based sentiment analysis.

End-to-End aspect-based sentiment analysis (E2E-ABSA) aims to jointly extract aspect terms and ident...

An accelerated end-to-end method for solving routing problems.

The application of neural network models to solve combinatorial optimization has recently drawn much...

Versatile end effector for laparoscopic robotic scrub nurse.

PURPOSE: Integrating robotic scrub nurses in the operating room has the potential to help overcome s...

Decoding Silent Speech Based on High-Density Surface Electromyogram Using Spatiotemporal Neural Network.

Finer-grained decoding at a phoneme or syllable level is a key technology for continuous recognition...

Deep learning methods for medical image fusion: A review.

The image fusion methods based on deep learning has become a research hotspot in the field of comput...

The effect of variable labels on deep learning models trained to predict breast density.

. High breast density is associated with reduced efficacy of mammographic screening and increased ri...

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot.

Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor functi...

Comparison of End-to-End Neural Network Architectures and Data Augmentation Methods for Automatic Infant Motility Assessment Using Wearable Sensors.

Infant motility assessment using intelligent wearables is a promising new approach for assessment of...

An end-to-end pipeline based on open source deep learning tools for reliable analysis of complex 3D images of ovaries.

Computational analysis of bio-images by deep learning (DL) algorithms has made exceptional progress ...

Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset.

For automatic EEG diagnosis, this paper presents a new EEG data set with well-organized clinical ann...

X-CHAR: A Concept-based Explainable Complex Human Activity Recognition Model.

End-to-end deep learning models are increasingly applied to safety-critical human activity recogniti...

An End-to-End Natural Language Processing System for Automatically Extracting Radiation Therapy Events From Clinical Texts.

PURPOSE: Real-world evidence for radiation therapy (RT) is limited because it is often documented on...

Automatic implant shape design for minimally invasive repair of pectus excavatum using deep learning and shape registration.

Minimally invasive repair of pectus excavatum (MIRPE) is an effective method for correcting pectus e...

Learning end-to-end patient representations through self-supervised covariate balancing for causal treatment effect estimation.

A causal effect can be defined as a comparison of outcomes that result from two or more alternative ...

Deep Learning-Based Wrist Vascular Biometric Recognition.

The need for contactless vascular biometric systems has significantly increased. In recent years, de...

Artificial Muscles and Soft Robotic Devices for Treatment of End-Stage Heart Failure.

Medical soft robotics constitutes a rapidly developing field in the treatment of cardiovascular dise...

Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots.

The lack of intuitive and active human-robot interaction makes it difficult to use upper-limb-assist...

Time-varying modeling and intelligent compensation control of singletendon-sheath structure of surgical robot.

The inaccurate force and position control of tendon sheath system (TSS) due to nonlinear friction du...

A Two-Stage End-to-End Deep Learning Framework for Pathologic Examination in Skin Tumor Diagnosis.

Neurofibromas (NFs), Bowen disease (BD), and seborrheic keratosis (SK) are common skin tumors. Patho...

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