Care of terminally ill / Palliative care

E2EFP-MIL: End-to-end and high-generalizability weakly supervised deep convolutional network for lung cancer classification from whole slide image.

Efficient and accurate distinction of histopathological subtype of lung cancer is quite critical for the individualized treatment. So far, artificial intelligence techniques have been developed, whose performance yet remained debatable on more heterogenous data, hindering their clinical deployment. Here, we propose an end-to-end, well-generalized and data-efficient weakly supervised deep learning-...

PPSW-SHAP: Towards Interpretable Cell Classification Using Tree-Based SHAP Image Decomposition and Restoration for High-Throughput Bright-Field Imaging.

Advancements in high-throughput microscopy imaging have transformed cell analytics, enabling functionally relevant, rapid, and in-depth bioanalytics with Artificial Intelligence (AI) as a powerful driving force in cell therapy (CT) manufacturing. High-content microscopy screening often suffers from systematic noise, such as uneven illumination or vignetting artifacts, which can result in false-neg...

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 identify their sentiment polarities. Although previous ...

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

The application of neural network models to solve combinatorial optimization has recently drawn much attention and shown promising results in dealing ...

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 of silent speech based on surface electromyogram ...

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 computer vision in recent years. This paper reviews thes...

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 risk of developing breast cancer. Accurate and relia...

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 infant neurophysiological development, and where ...

Investigating the robustness of a deep learning-based method for quantitative phase retrieval from propagation-based x-ray phase contrast measurements under laboratory conditions.

Quantitative phase retrieval (QPR) in propagation-based x-ray phase contrast imaging of heterogeneous and structurally complicated objects is challeng...

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 annotations called Chung-Ang University Hospital EEG ...

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 recognition (HAR) applications, e.g., healthcare monitoring...

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 excavatum (PE), a congenital chest wall deformity c...

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 actions, with only one of the action-outcome pairs...

Deep Learning-Based Wrist Vascular Biometric Recognition.

The need for contactless vascular biometric systems has significantly increased. In recent years, deep learning has proven to be efficient for vein se...

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 during surgery seriously hinders its development in ...

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. Pathologic examination is the gold standard for diagnos...

A 3-DoF robotic platform for the rehabilitation and assessment of reaction time and balance skills of MS patients.

The central nervous system (CNS) exploits anticipatory (APAs) and compensatory (CPAs) postural adjustments to maintain the balance. The postural adjus...

Pill Box Text Identification Using DBNet-CRNN.

The recognition process of natural scenes is complicated at present, and images themselves may be complex owing to the special features of natural sce...

UDRN: Unified Dimensional Reduction Neural Network for feature selection and feature projection.

Dimensional reduction (DR) maps high-dimensional data into a lower dimensions latent space with minimized defined optimization objectives. The two ind...

Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: An integrative review.

An integrative review investigating the incorporation of artificial intelligence (AI) and machine learning (ML) based decision support systems in ment...