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Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

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Published on: October 6, 2023

Mapping study on AI-based technologies in palliative care - a scoping study.

Mariana Silva-Ferreira^1,2,3, Sara Cruz^3,4,5,6, Michael Sapateiro Luís⁷

¹Cancer Biology & Epigenetics Group, IPO Porto Research Center (CI-IPOP) Portuguese Oncology Institute of Porto (IPO Porto), R. Dr. António Bernardino de Almeida, Porto, 4200-072, Portugal.

BMC Palliative Care

|October 29, 2025

Summary

This summary is machine-generated.

Artificial Intelligence (AI) enhances palliative care (PC) by improving symptom management, communication, and decision support. This review maps AI applications in PC, identifying benefits and challenges for ethical implementation.

Keywords:

Artificial Intelligence Digital Health Technology Palliative Care Patient-Centered Care Scoping Review

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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

Published on: July 11, 2025

Area of Science:

Palliative Care
Artificial Intelligence
Health Informatics

Background:

Palliative care (PC) is crucial for improving quality of life in aging populations and those with chronic illnesses.
Artificial Intelligence (AI) and machine learning (ML) are transforming healthcare with tools like Clinical Decision Support Systems (CDSS).
AI shows potential in PC for early diagnosis, personalized care, and predicting complications, but faces challenges in data privacy and clinical integration.

Purpose of the Study:

To map and analyze the applications of AI in palliative care (PC).
To identify trends, benefits, and limitations of AI tools in PC.
To provide insights for the ethical and effective implementation of AI in PC.

Main Methods:

A scoping review was conducted, analyzing studies published until May 2024.
Two electronic databases were searched, yielding 57 relevant studies from 542 initial records.
The review focused on AI applications for diagnostics, prognostics, symptom tracking, and communication.

Main Results:

AI and digital technologies are revolutionizing PC by enhancing communication, care coordination, and symptom control, enabling remote care.
Key advancements were identified in symptom management, communication, decision support, telemedicine, and education.
Barriers such as ethical, legal, and accessibility concerns were also addressed.

Conclusions:

AI integration in PC can empower professionals and policymakers to develop more effective, ethical, and person-centered strategies.
Insights are provided for developing new technologies and protocols for safe and equitable AI implementation in PC.
Prioritizing early patient needs identification and integrating hospital with community care are essential for AI in PC.