Unlocking the Power of ChatGPT, Artificial Intelligence, and Large Language Models: Practical Suggestions for Radiation Oncologists.

Pract Radiat Oncol

Department of Radiation Oncology and Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California. Electronic address:

Published: November 2023


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Recent advances in artificial intelligence (AI), such as generative AI and large language models (LLMs), have generated significant excitement about the potential of AI to revolutionize our lives, work, and interaction with technology. This article explores the practical applications of LLMs, particularly ChatGPT, in the field of radiation oncology. We offer a guide on how radiation oncologists can interact with LLMs like ChatGPT in their routine clinical and administrative tasks, highlighting potential use cases of the present and future. We also highlight limitations and ethical considerations, including the current state of LLMs in decision making, protection of sensitive data, and the important role of human review of AI-generated content.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.prro.2023.06.011DOI Listing

Publication Analysis

Top Keywords

artificial intelligence
8
large language
8
language models
8
radiation oncologists
8
llms chatgpt
8
unlocking power
4
power chatgpt
4
chatgpt artificial
4
intelligence large
4
models practical
4

Similar Publications

Cognitive impairment and dementia, including Alzheimer's disease (AD), pose a global health crisis, necessitating non-invasive biomarkers for early detection. This review highlights the retina, an accessible extension of the central nervous system (CNS), as a window to cerebral pathology through structural, functional, and molecular alterations. By synthesizing interdisciplinary evidence, we identify retinal biomarkers as promising tools for early diagnosis and risk stratification.

View Article and Find Full Text PDF

Introduction: Vision language models (VLMs) combine image analysis capabilities with large language models (LLMs). Because of their multimodal capabilities, VLMs offer a clinical advantage over image classification models for the diagnosis of optic disc swelling by allowing a consideration of clinical context. In this study, we compare the performance of non-specialty-trained VLMs with different prompts in the classification of optic disc swelling on fundus photographs.

View Article and Find Full Text PDF

Artificial intelligence (AI) is a technique or tool to simulate or emulate human "intelligence." Precision medicine or precision histology refers to the subpopulation-tailored diagnosis, therapeutics, and management of diseases with its sociocultural, behavioral, genomic, transcriptomic, and pharmaco-omic implications. The modern decade experiences a quantum leap in AI-based models in various aspects of daily routines including practice of precision medicine and histology.

View Article and Find Full Text PDF

Immunotherapies for Aging and Age-Related Diseases: Advances, Pitfalls, and Prospects.

Research (Wash D C)

September 2025

NHC Key Laboratory of Tropical Disease Control, School of Life Sciences and Medical Technology, Hainan Medical University, Haikou, Hainan 571199, China.

Aging is characterized by a gradual decline in the functionality of all the organs and tissues, leading to various diseases. As the global population ages, the urgency to develop effective anti-aging strategies becomes increasingly critical due to the growing severity of associated health problems. Immunotherapy offers novel and promising approaches to combat aging by utilizing approaches including vaccines, antibodies, and cytokines to target specific aging-related molecules and pathways.

View Article and Find Full Text PDF

Deep learning has rapidly emerged as a promising toolkit for protein optimization, yet its success remains limited, particularly in the realm of activity. Moreover, most algorithms lack rigorous iterative evaluation, a crucial aspect of protein engineering exemplified by classical directed evolution. This study introduces DeepDE, a robust iterative deep learning-guided algorithm leveraging triple mutants as building blocks and a compact library of ∼1,000 mutants for training.

View Article and Find Full Text PDF