About

Ying Xiao, Ph.D., is a Professor of Radiation Oncology at the Hospital of the University of Pennsylvania. He serves as the Director of Clinical Research and Informatics in the Physics Division within the Radiation Oncology Department. His educational background includes a BS in Optical Engineering from Tsinghua University, an MS in Physics from Temple University, and a Ph.D. in Physics from Temple University. Dr. Xiao's research focuses on radiotherapy, quality assurance research, clinical trial research, and big data applications in medicine. His work involves advancing clinical research and informatics in radiation oncology to improve patient care and treatment outcomes.

Research topics

• Computer Science
• Medicine
• Medical physics
• Artificial Intelligence
• Data science
• Physics
• Political Science
• Engineering
• Nuclear physics
• Oncology
• Optics
• Surgery
• Radiology
• Nuclear medicine
• Knowledge management
• Internal medicine
• Medical education
• Engineering management
• Statistics
• Mathematics
• Business

Selected publications

• Design of Intelligent Investment Evaluation Model for Technology Transformation Projects Driven by Informatization

  Frontiers in artificial intelligence and applications · 2026-04-28

  book-chapter

  This study proposes an economic evaluation framework for power grid production technological transformation projects by integrating (i) a present-value cost model, (ii) a present-value benefit model, and (iii) investment economic analysis (NPV, dynamic return, and IRR). Costs are discounted as a one-time investment plus potential future additions over the equipment life T, while benefits include risk-loss reduction, reduced inspection/patrol costs, and energy-saving gains. A 500 kV substation case—installing online monitoring devices for a main transformer iron core, clamp grounding current, and N600 grounding current—verifies the model. With a one-time investment of CNY 850,000, discount rate 4.9%, and life 15 years, the project yields a present-value benefit of CNY 1.0148 million and a positive NPV of CNY 164,800. Risk-loss probability declines from 0.19% to 0.16%, daily patrol frequency drops from 24 to 12 times/year (-50%), and professional maintenance decreases from 1 to 0 time/year. The resulting dynamic return is 19.39% and IRR is 7.45%, exceeding the discount rate. Overall, the framework quantifies both operational improvements and financial feasibility for similar grid retrofits.

  PublisherDOI

• Advancing flexible sensing systems: Deep learning-driven insights and future perspectives

  Sensors and Actuators A Physical · 2026-05-05

  article1st author
  PublisherDOI

• Following intravenous thrombolysis, the outcome of diabetes mellitus associated with acute ischemic stroke was predicted via machine learning

  Frontiers in Pharmacology · 2025-01-27 · 1 citations

  articleOpen access

  This cohort study aimed to evaluate the prognostic outcomes of patients with acute ischemic stroke (AIS) and diabetes mellitus following intravenous thrombolysis, utilizing machine learning techniques. The analysis was conducted using data from Shenyang First People's Hospital, involving 3,478 AIS patients with diabetes who received thrombolytic therapy from January 2018 to December 2023, ultimately focusing on 1,314 patients after screening. The primary outcome measured was the 90-day Modified Rankin Scale (MRS). An 80/20 train-test split was implemented for model development and validation, employing various machine learning classifiers, including artificial neural networks (ANN), random forest (RF), XGBoost (XGB), and LASSO regression. Results indicated that the average accuracy of the XGB model was 0.7355 (±0.0307), outperforming the other models. Key predictors for prognosis post-thrombolysis included the National Institutes of Health Stroke Scale (NIHSS) and blood platelet count. The findings underscore the effectiveness of machine learning algorithms, particularly XGB, in predicting functional outcomes in diabetic AIS patients, providing clinicians with a valuable tool for treatment planning and improving patient outcome predictions based on receiver operating characteristic (ROC) analysis and accuracy assessments.

  PublisherOA PDFDOI

• Implementation of regional Acute Stroke Care Map increases thrombolysis rates in urban areas of China: an interrupted time series analysis

  International Journal for Quality in Health Care · 2025-04-01 · 1 citations

  article

  BACKGROUND: Stroke, a leading cause of global disability, where timely thrombolysis is crucial for favorable outcomes. Despite initiatives like Acute Stroke Care Maps (ASCaMs) in China aiming to improve care continuity and thrombolysis rates, the long-term effectiveness of these interventions in urban settings remains underexplored. METHODS: This retrospective cohort study investigates the role of the Shenyang ASCaM in improving the thrombolysis rate with tissue plasminogen activator within 4.5 hours of ischemic stroke onset in 30 hospitals. Using interrupted time series (ITS) analysis, it compares outcomes before and after ASCaM's implementation from April 2019 to December 2021. The ASCaM strategy, featuring EMS prenotification, rapid triage, and immediate neuroimaging, is assessed. Regression models, adjusted for patient demographics and clinical scores, evaluate the intervention's impact, controlling for potential confounders. RESULTS: In the study, 2676 patients were evaluated before the implementation of the Shenyang ASCaM, and 8277 patients were assessed during its implementation. Thrombolysis rates within the vital 4.5-hour window rose significantly from 59% before ASCaM to 72% during its implementation (P < .001), and door-to-needle time (DNT) decreased significantly by 12.269 minutes (P < .0001). Early neurological deterioration (END) incidents decreased significantly from 44% to 39.2% (adjusted OR = 0.820, P = .001), indicating improved stroke care efficiency and outcomes. ITS analysis showed a pre-implementation monthly decrease in thrombolysis rates of 0.95%, countered by a post-implementation immediate surge of 6.21% and a sustained improvement at a rate of 0.13% per month. Furthermore, Post-ASCaM, DNT reduced to 52.42 minutes, thrombolysis rates increased to 72.3%, and END incidence decreased (adjusted OR = 0.820, P = .001), indicating improved stroke care efficiency and outcomes. CONCLUSION: Our findings confirm that China's ASCaMs significantly enhance thrombolysis rates and ensure care continuity in managing acute stroke, indicating their long-term effectiveness in urban settings. This contributes to global stroke care improvements, emphasizing the potential for wider application and further research on sustained interventions.

  PublisherDOI

• PROTON VERSUS PHOTON RADIATION TO IMMUNE CELLS AND ORGANS-AT-RISK IN LA-NSCLC: DOSIMETRIC ANALYSIS OF RTOG 1308, A PHASE III RCT

  International Journal of Particle Therapy · 2025-11-25

  articleOpen accessSenior author
  PublisherDOI

• Ultra-Stretchable and Subzero-Healable Epidermal Electrodes Enabled by Kirigami-Networked Microcrack Engineering for Human-Machine Interactions

  SSRN Electronic Journal · 2025-01-01

  preprintOpen access1st authorCorresponding
  PublisherDOI

• Semicentennial Tillage Significantly Affects the Soil Evolution in Arid Regions of China

  Preprints.org · 2025-01-14

  preprintOpen access1st authorCorresponding

  Quantifying the rates of soil evolution greatly benefits our understanding of soil formation and management, especially in the context of strong anthropogenic activities and climate change. This study investigated soil evolution in an artificial oasis region with a reclamation history of more than 50 years, and critical soil properties were measured at 77 sites. A total of 462 soil samples were collected down to a depth of 1 m. A total of seven critical soil properties were analysed, and four (i.e., soil organic carbon (SOC), total phosphorus (TP), pH, and ammonium nitrogen (NH4+)), which were not closely correlated with each other, were selected for further investigation. Through comparison with desert soils, this investigation found that semicentennial cultivation resulted in significant changes in soil properties, with strong vertical variations, including increases in the C, N and P contents and decreases in pH throughout the whole profile. The temperature, clay content, evaporation rate between the topsoil and subsoil, low vegetation cover, cotton lateral roots, irrigation and fertilization played crucial roles in promoting SOC decomposition and reducing soil alkalinity, thereby contributing to rapid soil evolution. Thus, reclaimed desert soil was scientifically confirmed to be suitable for agricultural use, which will ease the food production crisis, protect the environment, and promote soil evolution. Furthermore, three-dimensional digital soil mapping was performed to investigate the effects of long-term cultivation on the distributions of soil properties at unvisited sites. The soil depth functions were separately fitted to model the vertical variation in the soil properties, including the exponential function, power function, logarithmic function and cubic polynomial function, and the parameters were extrapolated to unvisited sites via the quantile regression forest (QRF), boosted regression tree and multiple linear regression techniques. The QRF technique yielded the best performance for SOC (R2= 0.78 and RMSE = 0.62), TP (R2 = 0.79 and RMSE = 0.12), pH (R2 = 0.78 and RMSE = 0.10) and NH4+ (R2 = 0.71 and RMSE = 0.38). The results showed that depth function coupled with machine learning methods can predict the spatial distribution of soil properties in arid areas efficiently and accurately. These research conclusions will lead to more effective targeted measures and guarantees for local agricultural development and food security.

  PublisherOA PDFDOI

• [Advances in the Treatment of Multiple Primary Lung Cancer].

  PubMed · 2025-06-20

  reviewOpen access1st authorCorresponding

  In recent years, the incidence of multiple primary lung cancer (MPLC) has been increasing, and it cannot be ignored in clinical practice. The treatment of MPLC is still controversial, but surgical treatment is recognized as the most important treatment. However, current studies have shown that the treatment of MPLC needs to develop multimodal treatment according to different patients. This review summarizes multiple treatment method for MPLC, including surgery, ablation, chemotherapy, radiotherapy, targeted therapy, and immunotherapy in order to enhance understanding of MPLC treatment. .

  PublisherOA PDFDOI

• ROBUSTNESS EVALUATION AND OPTIMISATION IN PARTICLE THERAPY: RESULTS OF A GLOBAL HARMONIZATION GROUP WORLDWIDE SURVEY

  International Journal of Particle Therapy · 2025-11-25

  articleOpen access
  PublisherDOI

• Quantitative Evaluation of Artificial Intelligence-Based Organ Segmentation Across Multiple Anatomic Sites Using 8 Commercial Software Platforms

  Practical Radiation Oncology · 2025-08-23 · 2 citations

  articleOpen access
  PublisherOA PDFDOI

Recent grants

• Imaging and Radiation Oncology Core (IROC) Group

  NIH · $107.5M · 2014–2026

Frequent coauthors

• Yunfeng Cui

  Duke Medical Center

  271 shared

• James M. Galvin

  RTOG Foundation

  238 shared

• J.M. Galvin

  154 shared

• Feng‐Ming Kong

  University of Hong Kong - Shenzhen Hospital

  128 shared

• W Chen

  Thomas Jefferson University

  125 shared

• Jason W. Sohn

  118 shared

• Jatinder Palta

  Virginia Commonwealth University

  116 shared

• Anthony Doemer

  112 shared

Labs

• Ying Xiao LaboratoryPI