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Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Updated: Jul 14, 2025

Author Spotlight: Improving Radiation Therapy Access with Radiation Planning Assistant

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Published on: October 6, 2023

Improving radiology workflow using ChatGPT and artificial intelligence.

Ismail Mese¹, Ceylan Altintas Taslicay², Ali Kemal Sivrioglu³

¹Department of Radiology, Health Sciences University, Erenkoy Mental Health and Neurology Training and Research Hospital, 19 Mayıs, Sinan Ercan Cd. No: 23, Kadıköy/Istanbul 34736, Turkey.

Clinical Imaging

|October 9, 2023

Summary

This summary is machine-generated.

Artificial intelligence (AI), including ChatGPT, can enhance radiology workflows for better efficiency and patient care. Addressing AI bias and ethical concerns is crucial for its successful integration in healthcare.

Keywords:

Artificial intelligence ChatGPT Diagnostic techniques Natural language processing Radiology

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Area of Science:

Computer Science
Medical Imaging
Natural Language Processing

Background:

Artificial Intelligence (AI) is revolutionizing various fields, including medicine.
Natural Language Processing (NLP) enables machines to understand and interact with human language.
ChatGPT is an advanced NLP tool with potential applications in healthcare.

Purpose of the Study:

To explore the integration of AI, specifically ChatGPT, into radiology workflows.
To identify how AI can improve efficiency, accuracy, and patient care in radiology.
To discuss the potential benefits and limitations of using ChatGPT in medical imaging.

Main Methods:

Review of AI and NLP capabilities relevant to healthcare.
Analysis of ChatGPT's potential to streamline radiology processes.
Identification of challenges and ethical considerations for AI implementation in radiology.

Main Results:

ChatGPT can optimize radiology workflows from patient registration to reporting.
AI integration promises enhanced efficiency and accuracy in diagnostic processes.
Potential benefits include improved patient scheduling, faster image interpretation, and streamlined reporting.

Conclusions:

AI, particularly ChatGPT, holds significant promise for transforming radiology.
Addressing algorithmic bias and ethical concerns is paramount for responsible AI adoption.
Continued advancements in AI are expected to further enhance its role in radiology and broader healthcare settings.