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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 64-84 of 6,157 articles
End-To-End Deep Learning Explains Antimicrobial Resistance in Peak-Picking-Free MALDI-MS Data.

Mass spectrometry is used to determine infectious microbial species in thousands of clinical laborat...

Use of Artificial Intelligence in Lower Gastrointestinal and Small Bowel Disorders: An Update Beyond Polyp Detection.

Machine learning and its specialized forms, such as Artificial Neural Networks and Convolutional Neu...

Deep one-class probability learning for end-to-end image classification.

One-class learning has many application potentials in novelty, anomaly, and outlier detection system...

A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario.

BACKGROUND: Malaria is a critical and potentially fatal disease caused by the Plasmodium parasite an...

The Use of AI in Mental Health Services to Support Decision-Making: Scoping Review.

BACKGROUND: Recent advancements in artificial intelligence (AI) have changed the care processes in m...

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects...

Kernel representation-based End-to-End network-enabled decoding strategy for precise and medical diagnosis.

Artificial intelligence-assisted imaging biosensors have attracted increasing attention due to their...

Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound usin...

When multiple instance learning meets foundation models: Advancing histological whole slide image analysis.

Deep multiple instance learning (MIL) pipelines are the mainstream weakly supervised learning method...

Current state and promise of user-centered design to harness explainable AI in clinical decision-support systems for patients with CNS tumors.

In neuro-oncology, MR imaging is crucial for obtaining detailed brain images to identify neoplasms, ...

Haptic Shared Control Framework with Interaction Force Constraint Based on Control Barrier Function for Teleoperation.

Current teleoperated robotic systems for retinal surgery cannot effectively control subtle tool-to-t...

End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe ...

Automated stenosis estimation of coronary angiographies using end-to-end learning.

The initial evaluation of stenosis during coronary angiography is typically performed by visual asse...

Constructing a metadata knowledge graph as an atlas for demystifying AI pipeline optimization.

The emergence of advanced artificial intelligence (AI) models has driven the development of framewor...

An end-to-end implicit neural representation architecture for medical volume data.

Medical volume data are rapidly increasing, growing from gigabytes to petabytes, which presents sign...

The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children.

The rising prevalence of myopia is a significant global health concern. Atropine eye drops are comm...

Combination of deep learning reconstruction and quantification for dynamic contrast-enhanced (DCE) MRI.

Dynamic contrast-enhanced (DCE) MRI is an important imaging tool for evaluating tumor vascularity th...

An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontology-Enhanced Large Language Models: Development Study.

BACKGROUND: Rare diseases affect millions worldwide but sometimes face limited research focus indivi...

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