Results 11 to 20 of about 560,406 (374)

Artificial General Intelligence for Radiation Oncology [PDF]

Meta-Radiology, 2023
The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can process extensive texts and large vision models (LVMs) such as the Segment
Dai, Haixing, Ding, Yuzhen, Holmes, Jason, Li, Quanzheng, Li, Xiang, Li, Yiwei, Liu, Chenbin, Liu, Ninghao, Liu, Tianming, Liu, Wei, Liu, Zhengliang, Shen, Dinggang, Shu, Peng, Wu, Zihao, Zhang, Lian, Zhang, Lu, Zhu, Dajiang   +16 more
core   +3 more sources

Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology [PDF]

PLOS ONE, 2018
Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great potential to generate hypotheses for cancer treatment, since they directly provide medical data on a large scale. In order to gather a significant amount of patients with a high level of clinical details, multicenter studies are necessary.
Jean-Emmanuel Bibault, Eric Zapletal, Bastien Rance, Philippe Giraud, Anita Burgun   +4 more
openaire   +5 more sources

An Emerging Role for Radiation Oncology in Precision Oncology [PDF]

EBioMedicine, 2016
Precision medicine is rapidly evolving in the management of cancer, in an effort to deliver the right therapy to the right patient at the right time. The use of novel molecular or genetic signatures in decision making regarding local–regional management is in its infancy. In their recent work published in EBioMedicine, Cheng and colleagues developed
Sharad Goyal, Bruce G. Haffty
openaire   +5 more sources

RadOnc-GPT: A Large Language Model for Radiation Oncology [PDF]

arXiv, 2023
This paper presents RadOnc-GPT, a large language model specialized for radiation oncology through advanced tuning methods. RadOnc-GPT was finetuned on a large dataset of radiation oncology patient records and clinical notes from the Mayo Clinic in ...
Holmes, Jason, Li, Quanzheng, Li, Xiang, Li, Yiwei, Liu, Chenbin, Liu, Ninghao, Liu, Tianming, Liu, Wei, Liu, Zhengliang, Patel, Samir H., Shu, Peng, Sio, Terence T., Wang, Peilong, Zhang, Lian, Zhu, Dajiang   +14 more
core   +1 more source

The Radiation Oncology NLP Database [PDF]

arXiv
We present the Radiation Oncology NLP Database (ROND), the first dedicated Natural Language Processing (NLP) dataset for radiation oncology, an important medical specialty that has received limited attention from the NLP community in the past.
Cai, Hongmin, Elahi, Muhammad Ali, Feng, Hongying, Holmes, Jason, Li, Quanzheng, Li, Xiang, Liao, Wenxiong, Liu, Chenbin, Liu, Tianming, Liu, Wei, Liu, Zhengliang, Shen, Jiajian, Sun, Lichao, Wang, Peilong, Zhang, Lian   +14 more
core   +1 more source

Preclinical models in radiation oncology [PDF]

Radiation Oncology, 2012
Abstract As the incidence of cancer continues to rise, the use of radiotherapy has emerged as a leading treatment modality. Preclinical models in radiation oncology are essential tools for cancer research and therapeutics. Various model systems have been used to test radiation therapy, including in vitro cell culture assays as well as in vivo
Jenna M. Kahn, Jenna M. Kahn, Philip J. Tofilon, Kevin Camphausen   +3 more
openaire   +5 more sources

Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans [PDF]

Practical Radiation Oncology, Volume 13, Issue 3, May-June 2023, Pages e282-e291, 2022
Purpose: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans. Methods: A total of 245 VMAT HN plans were created using RapidPlan knowledge-based planning (KBP). A subset of 112 high-quality plans was selected under the supervision of an HN radiation oncologist. We trained
arxiv   +1 more source

Practitioner perceptions on the use of exercise and nutritional interventions for patients with breast cancer receiving radiation therapy

Journal of Medical Radiation Sciences, 2023
Introduction Radiation therapy treatment for breast cancer may negatively impact patients' health‐related quality of life. Evidence suggests exercise and nutrition interventions may be beneficial to patients experiencing compromised health‐related ...
Laura Feighan, Lesley MacDonald‐Wicks, Robin Callister, Yolanda Surjan   +3 more
doaj   +1 more source

ASTRO's Advances in Radiation Oncology: Success to date and future plans

Advances in Radiation Oncology, 2017
ASTRO's Advances in Radiation Oncology was launched as a new, peer-reviewed scientific journal in December 2015. More than 200 manuscripts have been submitted and 97 accepted for publication as of May 2017.
Robert C. Miller, MD, MBA, FASTRO, Sharad Goyal, MD, Shearwood McClelland, III, MD, Sabin Motwani, MD, Charles Mayo, PhD, Tasneem Kaleem, MD, Gregory Videtic, MD, Kathleen Hintenlang, PhD   +7 more
doaj   +1 more source

Increasing pediatric radiation oncology capacity in sub-saharan Africa using technology: a pilot of a pediatric radiation oncology virtual training course. [PDF]

BMC Med Educ
Background The shortage of skilled healthcare professionals in pediatric oncology and the limited access to training programs remain significant challenges in Nigeria and sub-Saharan Africa. The the Pediatric Radiation Oncology (Virtual) Course, ‘PedROC’
Joseph AO, Akinsete AM, Ajose AO, Oladipo AT, Maliki A, Akindele K, Mangongolo M, Adeneye S, Ngwa W.   +8 more
europepmc   +2 more sources