What is he best known for?
The fields of study he is best known for:
- Cancer
- Internal medicine
- Radiation therapy
Walter J. Curran spends much of his time researching Radiation therapy, Internal medicine, Oncology, Surgery and Nuclear medicine.
His Radiation therapy study combines topics from a wide range of disciplines, such as Clinical trial, Chemotherapy, Survival rate, Randomized controlled trial and Survival analysis.
The study incorporates disciplines such as Gastroenterology and Glioma in addition to Internal medicine.
His Oncology research incorporates themes from Multivariate analysis and Recursive partitioning.
Walter J. Curran has included themes like Cancer and Biopsy, Radiology in his Surgery study.
His Nuclear medicine research is multidisciplinary, relying on both Central nervous system disease, Radiosurgery, Magnetic resonance imaging, Toxicity and Glioblastoma.
His most cited work include:
- Whole brain radiation therapy with or without stereotactic radiosurgery boost for patients with one to three brain metastases: phase III results of the RTOG 9508 randomised trial (1817 citations)
- A Randomized Trial of Bevacizumab for Newly Diagnosed Glioblastoma (1528 citations)
- Recursive Partitioning Analysis of Prognostic Factors in Three Radiation Therapy Oncology Group Malignant Glioma Trials (1113 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Radiation therapy, Internal medicine, Oncology, Surgery and Artificial intelligence.
His biological study deals with issues like Nuclear medicine, which deal with fields such as Magnetic resonance imaging.
His Internal medicine research focuses on Chemotherapy, Lung cancer, Cancer, Clinical trial and Hazard ratio.
In general Oncology study, his work on Chemoradiotherapy often relates to the realm of In patient, thereby connecting several areas of interest.
His Surgery research is multidisciplinary, incorporating elements of Gastroenterology and Multivariate analysis, Univariate analysis.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Computer vision and Pattern recognition.
He most often published in these fields:
- Radiation therapy (37.67%)
- Internal medicine (33.94%)
- Oncology (29.19%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (16.18%)
- Segmentation (9.50%)
- Deep learning (7.13%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Segmentation, Deep learning, Pattern recognition and Radiation treatment planning.
His Artificial intelligence study combines topics in areas such as Transformation and Computer vision.
He interconnects Multi organ, Nuclear medicine, Prostate and Hausdorff distance in the investigation of issues within Segmentation.
His Radiation treatment planning study falls within the topics of Radiation therapy and Radiology.
His Radiation therapy research integrates issues from Cancer, Oncology and Hazard ratio.
His work in the fields of Chemoradiotherapy overlaps with other areas such as In patient.
Between 2018 and 2021, his most popular works were:
- Long-term primary results of accelerated partial breast irradiation after breast-conserving surgery for early-stage breast cancer: a randomised, phase 3, equivalence trial (94 citations)
- Long-Term Results of NRG Oncology RTOG 0617: Standard- Versus High-Dose Chemoradiotherapy With or Without Cetuximab for Unresectable Stage III Non-Small-Cell Lung Cancer. (84 citations)
- Automatic multiorgan segmentation in thorax CT images using U-net-GAN. (72 citations)
In his most recent research, the most cited papers focused on:
- Cancer
- Internal medicine
- Radiation therapy
His primary scientific interests are in Artificial intelligence, Radiation treatment planning, Radiation therapy, Deep learning and Nuclear medicine.
The Artificial intelligence study combines topics in areas such as Magnetic resonance imaging, Computer vision and Pattern recognition.
His Radiation treatment planning study deals with Computed tomography intersecting with Normal tissue.
His Radiation therapy research entails a greater understanding of Internal medicine.
He works mostly in the field of Nuclear medicine, limiting it down to topics relating to Image quality and, in certain cases, Radiosurgery and Dose-volume histogram.
His studies examine the connections between Cancer and genetics, as well as such issues in Disease, with regards to Oncology.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
