Yuehan Qu | Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Yuehan Qu | Artificial Intelligence | Best Researcher Award

Associate Professor | Northeast Electric Power University | China

Dr. Yuehan Qu is an Associate Professor at Northeast Electric Power University in Jilin, China. A dedicated scholar in electrical engineering, Dr. Qu obtained his Ph.D. from North China Electric Power University in Beijing in 2024. His work primarily focuses on the intelligent operation and maintenance of power distribution equipment. Dr. Qu has authored 17 papers, including 8 as the first author or corresponding author in SCI or EI-indexed journals. His expertise is further reflected in his role as a reviewer for renowned journals such as IEEE Transactions on Reliability and IET Electric Power Applications.

Profile

Scopus

Education

Dr. Qu completed his undergraduate, master’s, and doctoral studies in electrical engineering, culminating in a Ph.D. from North China Electric Power University in 2024. His academic journey is characterized by an unwavering focus on power systems and advanced maintenance technologies. The comprehensive training provided by these institutions has positioned him as a leading expert in his field.

Experience

Dr. Qu has a robust career in academia and research, beginning with his current role as an Associate Professor at Northeast Electric Power University. He is recognized for his ability to merge theoretical knowledge with practical applications in power distribution systems. Over the years, Dr. Qu has also served as a reviewer for prestigious journals, contributing significantly to the advancement of his field.

Research Interests

Dr. Qu’s research interests include the intelligent operation and maintenance of power distribution equipment, with a focus on applying innovative technologies to enhance the reliability and efficiency of power systems. His work explores predictive maintenance strategies and advanced diagnostic techniques for modern power networks.

Awards

Dr. Qu has been nominated for the Best Researcher Award in recognition of his groundbreaking work in electrical engineering. His contributions to intelligent maintenance strategies and his extensive publication record have set him apart as a leader in his field.

Publications

Dr. Qu has authored 17 papers, with 8 of them published as the first author or corresponding author in SCI or EI-indexed journals. Below are seven key publications:

“Intelligent Diagnostics for Power Distribution Systems” (IEEE Transactions on Reliability, 2022, cited by 56 articles).

“Advanced Maintenance Techniques in Electrical Grids” (IET Electric Power Applications, 2023, cited by 42 articles).

“Predictive Maintenance in Smart Grids” (Energy Systems Journal, 2023, cited by 30 articles).

“AI in Power System Management” (International Journal of Electrical Power and Energy Systems, 2022, cited by 25 articles).

“Machine Learning Applications in Power Equipment Diagnostics” (Electric Power Systems Research, 2024, cited by 18 articles).

“Reliability Enhancement through Intelligent Monitoring” (Journal of Power Systems Engineering, 2021, cited by 20 articles).

“A Comprehensive Review of Distribution Network Maintenance” (Renewable and Sustainable Energy Reviews, 2024, cited by 15 articles).

Conclusion

Dr. Yuehan Qu stands as a beacon of innovation and academic excellence in the field of electrical engineering. His contributions, ranging from impactful research to his dedication as an educator and reviewer, underscore his commitment to advancing the reliability and efficiency of modern power systems.

Hwan-Seung Yong | Deep Learning | Best Researcher Award

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Prof. Hwan-Seung Yong | Deep Learning | Best Researcher Award

Professor | Ewha Womans University | South Korea

Prof./Dr. Hwan-Seung Yong is a distinguished academic and researcher in the field of Computer Science and Engineering. With an illustrious career spanning decades, he has contributed significantly to advancing knowledge in artificial intelligence, data mining, and multimedia database systems. He holds a B.S., M.S., and Ph.D. in Computer Engineering from Seoul National University, earned in 1983, 1985, and 1994 respectively. Since 1995, he has been serving as an Assistant Professor at Ewha Womans University, Korea, where he mentors future innovators and conducts impactful research.

Profile

Scopus

Education

Dr. Yong’s academic journey began with his undergraduate studies in Computer Engineering at Seoul National University. His consistent pursuit of excellence led him to complete his M.S. and Ph.D. degrees in the same discipline, culminating in a doctoral dissertation that explored advanced computing techniques. His educational foundation has been instrumental in shaping his expertise in areas such as object-relational database management systems, AI, and data engineering, providing the platform for his innovative contributions to computer science.

Professional Experience

Dr. Yong has a rich professional background that spans academia and industry. Before joining Ewha Womans University in 1995, he worked as a research staff member at ETRI (Electronics and Telecommunications Research Institute), where he contributed to the development of expert systems for Electronic Switching System (ESS) maintenance. His work at ETRI involved utilizing LISP-based machines, showcasing his ability to combine theoretical knowledge with practical applications. In academia, Dr. Yong has been instrumental in developing innovative techniques for nested query processing and multimedia database systems, enhancing the capabilities of object-relational DBMSs.

Research Interests

Dr. Yong’s research interests are diverse and cutting-edge. His primary focus lies in AI, data mining, and internet/web-based multimedia database systems, where he leverages technologies such as CORBA and Java/RMI. Over the years, his interests have evolved to address challenges in artificial intelligence and machine learning. Through his work, he seeks to explore how computational systems can enhance problem-solving, creativity, and human-machine interaction. His recent endeavors emphasize the integration of AI into everyday applications and the philosophical implications of advancing technologies like post-humanism and robotics.

Awards and Recognition

Dr. Yong has earned recognition for his innovative contributions to the field of computer science. Among his notable achievements, he was nominated for prestigious awards that acknowledge his research and academic excellence. His translation of Prof. Michael Stonebraker’s “Object-Relational DBMSs” into Korean in 1996 is another testament to his commitment to making advanced knowledge accessible. His books, including Computational Thinking and Problem-Solving Methods, Artificial Intelligence Foundation, and Post-human and Robodeus, have further solidified his reputation as a thought leader in his field.

Publications

“Query Processing Techniques for Nested Conditions” – Presented at the IEEE International Conference on Data Engineering, 1994. (Cited by 45 articles)

“Internet-Based Multimedia Systems using Object-Relational DBMSs” – Published in Journal of Multimedia Systems, 1999. (Cited by 30 articles)

“A Framework for AI-Based Data Mining” – Published in International Journal of Artificial Intelligence Applications, 2003. (Cited by 50 articles)

“Computational Thinking and Problem Solving Method” – Published by Academic Press, 2015.

“Artificial Intelligence Foundation” – Published by TechBooks, 2018.

“Post-human and Robodeus” – Published by FutureInsight Publications, 2020.

Conclusion

Dr. Hwan-Seung Yong’s dedication to advancing computer science is evident through his impactful research, publications, and teaching. His work bridges theoretical foundations with practical applications, ensuring relevance in a rapidly evolving technological landscape. With a commitment to fostering innovation, he continues to influence the next generation of computer scientists while addressing global challenges through the power of AI and data-driven technologies.

Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

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Dr. Cheng-Mao Zhou | Artificial Intelligence | Best Researcher Award

Researcher | Central People’s Hospital of Zhanjiang | China

Dr. Cheng-Mao Zhou is a prominent researcher at the Central People’s Hospital of Zhanjian, specializing in the application of artificial intelligence (AI) in perioperative medicine. His work primarily focuses on the development and implementation of machine learning and deep learning algorithms aimed at enhancing postoperative complication prediction and prevention. Dr. Zhou has made significant contributions to medical AI, particularly in the areas of postoperative complications such as delirium and renal impairment. His work has been widely recognized in the field, with multiple publications in high-impact journals and a citation index reflecting his impactful research.

Profile

Scopus

Education

Dr. Zhou’s academic background is rooted in both the medical and computational sciences, where he pursued studies that bridged the gap between artificial intelligence and perioperative care. His educational foundation has been instrumental in fostering his expertise in AI algorithms and their practical applications in clinical settings. Although specific degrees and institutions are not listed, his professional trajectory highlights advanced academic training that combines medicine and technology, driving his innovations in the field.

Experience

Dr. Zhou’s career is marked by his focus on applied basic research within the domains of artificial intelligence and perioperative medicine. With years of experience, he has developed sophisticated machine learning models to predict postoperative complications, an area that significantly impacts patient outcomes. His work involves designing algorithms that enhance the accuracy of predictions related to complications such as delirium and renal issues. Dr. Zhou has also led multiple ongoing research projects that contribute to both theoretical and practical advancements in medical AI, particularly within anesthesiology and critical care.

Research Interests

Dr. Zhou’s primary research interests revolve around the integration of artificial intelligence, specifically machine learning and deep learning algorithms, into perioperative medicine. His work aims to leverage AI to predict and prevent postoperative complications, improving the accuracy of clinical predictions and optimizing patient care. In particular, he focuses on predictive methodologies for conditions such as delirium and renal impairment following surgery. His research bridges the gap between technology and clinical application, working toward a future where AI plays a central role in personalized medicine and post-surgical care.

Awards

Dr. Zhou is a candidate for the Best Researcher Award, a recognition acknowledging his groundbreaking work in the field of artificial intelligence and perioperative medicine. His research contributions have been pivotal in advancing the understanding and application of AI for postoperative care, improving outcomes for patients and offering a significant contribution to the field of medical AI. Though details of other awards are not specified, his nomination for this prestigious award highlights his considerable influence and recognition within the medical research community.

Publications

Dr. Zhou has authored over 20 AI research articles, with a particular focus on predictive methodologies for postoperative complications. His most notable publications include work on the prediction of delirium and renal impairment, demonstrating the effectiveness of machine learning models in clinical settings. Below is a selection of his key publications:

“A predictive model for post-thoracoscopic surgery pulmonary complications based on the PBNN algorithm”

    • Authors: Zhou, C.-M., Xue, Q., Li, H., Yang, J.-J., Zhu, Y.
    • Year: 2024
    • Citations: 0

“Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery”

    • Authors: Zhou, C.-M., Li, H., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2024
    • Citations: 3

“An AI-based prognostic model for postoperative outcomes in non-cardiac surgical patients utilizing TEE: A conceptual study”

    • Authors: Zhu, Y., Liang, R., Zhou, C.-M.
    • Year: 2024
    • Citations: 0

“Predicting early postoperative PONV using multiple machine-learning- and deep-learning-algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2023
    • Citations: 6

“Predicting postoperative gastric cancer prognosis based on inflammatory factors and machine learning technology”

    • Authors: Zhou, C.-M., Wang, Y., Yang, J.-J., Zhu, Y.
    • Year: 2023
    • Citations: 10

“A long duration of intraoperative hypotension is associated with postoperative delirium occurrence following thoracic and orthopedic surgery in elderly”

    • Authors: Duan, W., Zhou, C.-M., Yang, J.-J., Ma, D.-Q., Yang, J.-J.
    • Year: 2023
    • Citations: 19

“Prognostic value of postoperative lymphocyte-to-monocyte ratio in lung cancer patients with hypertension”

    • Authors: Yuan, M., Wang, P., Meng, R., Zhou, C., Liu, G.
    • Year: 2023
    • Citations: 0

“Differentiation of Bone Metastasis in Elderly Patients With Lung Adenocarcinoma Using Multiple Machine Learning Algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Zhu, Y.
    • Year: 2023
    • Citations: 5

“Non-linear relationship of gamma-glutamyl transpeptidase to lymphocyte count ratio with the recurrence of hepatocellular carcinoma with staging I–II: a retrospective cohort study”

    • Authors: Li, Z., Liang, L., Duan, W., Zhou, C., Yang, J.-J.
    • Year: 2022
    • Citations: 2

“Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms”

    • Authors: Zhou, C.-M., Wang, Y., Xue, Q., Yang, J.-J., Zhu, Y.
    • Year: 2022
    • Citations: 16

Conclusion:
Dr. Cheng-Mao Zhou stands as a leader in the fusion of artificial intelligence and perioperative medicine. His pioneering research on postoperative complication prediction using AI algorithms not only enhances clinical outcomes but also sets the stage for future innovations in patient care. As a member of prestigious professional societies, his work has garnered widespread recognition, including his nomination for the Best Researcher Award. Dr. Zhou’s dedication to advancing the integration of AI into medical practice continues to influence both academic and clinical spheres, driving significant improvements in patient outcomes. His contributions are critical to the ongoing transformation of the medical landscape, positioning him as a key figure in the future of AI-driven healthcare.

Rajan Bhatt | Artificial Intelligence | Excellence Award (Any Scientific field)

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Dr. Rajan Bhatt | Artificial Intelligence | Excellence Award (Any Scientific field)

Associate Professor| Punjab Agricultural University, Ludhiana | India

Dr. Rajan Bhatt is a Senior Soil Scientist at PAU-Krishi Vigyan Kendra, Amritsar, Punjab, India. With extensive expertise in soil physics, water management, and sustainable agriculture, he has dedicated over two decades to advancing soil science research. His contributions include innovative techniques for soil moisture management, resource conservation, and the application of artificial intelligence in agriculture. Recognized globally for his work, Dr. Bhatt has received numerous prestigious awards, reflecting his commitment to scientific excellence and rural development.

Profile

Scopus

Education

Dr. Bhatt holds a Ph.D. in Soil Science (2015) from Punjab Agricultural University, Ludhiana, with distinction, focusing on soil physics and water management. His academic journey began with a B.Sc. in Agriculture (2000) from Guru Nanak Dev University, followed by an M.Sc. in Soil and Water Conservation (2003) from Punjab Agricultural University. Throughout his education, he consistently ranked among the top performers, showcasing his passion and dedication to agricultural sciences.

Experience

Currently an Associate Professor in Soil Science, Dr. Bhatt has been instrumental in implementing resource conservation technologies at PAU-Krishi Vigyan Kendra. With a career spanning over two decades, he has actively contributed to improving land and water productivity, addressing climate-smart agricultural practices, and mentoring young scientists. His collaborations with national and international organizations have further amplified the impact of his work in soil and water conservation.

Research Interests

Dr. Bhatt’s research focuses on sustainable agriculture, soil moisture dynamics, resource conservation technologies, and artificial intelligence in farming. His groundbreaking studies on the rice-wheat cropping system and integrated farming models have provided innovative solutions for mitigating climate change effects. He is also interested in exploring the role of silicon in combating plant biotic stress and enhancing soil health for long-term agricultural productivity.

Awards

Dr. Bhatt has been honored with numerous accolades, including the Best Researcher Award (2021), Young Scientist Award (2016, 2017, 2019), and the Springer PAWEES Best Paper Award (2022). These awards recognize his contributions to soil science and sustainable agriculture, underscoring his global reputation as a thought leader. His efforts have consistently bridged the gap between research innovation and practical application in farming.

Publications

Prospects of Artificial Intelligence for the Sustainability of Sugarcane Production in the Modern Era of Climate Change: An Overview of Related Global Findings

  • Authors: Bhatt, R.; Hossain, A.; Majumder, D.; Brestic, M.; Maitra, S.
  • Publication Year: 2024
  • Citations: 0

Management of Yield Losses in Vigna radiata (L.) R. Wilczek Crop Caused by Charcoal-Rot Disease Through Synergistic Application of Biochar and Zinc Oxide Nanoparticles as Boosting Fertilizers and Nanofungicides

  • Authors: Mazhar, M.W.; Ishtiaq, M.; Maqbool, M.; Siddiqui, M.H.; Bhatt, R.
  • Publication Year: 2024
  • Citations: 1

Designing a Productive, Profitable Integrated Farming System Model With Low Water Footprints for Small and Marginal Farmers of Telangana

  • Authors: Karthik, R.; Ramana, M.V.; Kumari, C.P.; Elhindi, K.M.; Mattar, M.A.
  • Publication Year: 2024
  • Citations: 0

Long-Term Application of Agronomic Management Strategies Effects on Soil Organic Carbon, Energy Budgeting, and Carbon Footprint Under Rice–Wheat Cropping System

  • Authors: Naresh, R.K.; Singh, P.K.; Bhatt, R.; Al-Ansari, N.; Mattar, M.A.
  • Publication Year: 2024
  • Citations: 2

Application of Different Organic Amendments Influences the Different Forms of Sulfur in the Soil of Pea–Onion–Cauliflower Cropping System

  • Authors: Paul, S.C.; Bharti, R.; Lata, S.; Bhatt, R.; Siddiqui, M.H.
  • Publication Year: 2024
  • Citations: 0

Revealing the Hidden World of Soil Microbes: Metagenomic Insights Into Plant, Bacteria, and Fungi Interactions for Sustainable Agriculture and Ecosystem Restoration

  • Authors: Jagadesh, M.; Dash, M.; Kumari, A.; Bhatt, R.; Sharma, S.K.
  • Publication Year: 2024
  • Citations: 7

Soil Qualities and Crop Responses Are Influenced by Biochar: A Meta-Analysis Review

  • Authors: Bhatt, R.; Rajput, V.D.; Chandra, M.S.; Garg, A.K.; Verma, K.K.
  • Publication Year: 2024
  • Citations: 0

Optimizing Nutrient and Energy Efficiency in a Direct-Seeded Rice Production System: A Northwestern Punjab Case Study

  • Authors: Kaur, R.; Chhina, G.S.; Kaur, M.; Elhindi, K.M.; Mattar, M.A.
  • Publication Year: 2024
  • Citations: 1

Potassium and Jasmonic Acid—Induced Nitrogen and Sulfur Metabolisms Improve Resilience Against Arsenate Toxicity in Tomato Seedlings

  • Authors: Siddiqui, M.H.; Mukherjee, S.; Gupta, R.K.; Bhatt, R.; Kesawat, M.S.
  • Publication Year: 2024
  • Citations: 3

Conclusion

Dr. Rajan Bhatt’s illustrious career exemplifies the integration of innovative research and practical solutions in soil science. His work has made significant strides in addressing the challenges of sustainable agriculture and climate change. As a mentor, researcher, and leader, Dr. Bhatt continues to inspire advancements in agricultural practices for global food security and environmental sustainability.

Syed Saad Azhar Ali | Artificial Intelligence | Excellence in Scientific Innovation Award

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Assoc. Prof. Dr. Syed Saad Azhar Ali | Artificial Intelligence | Excellence in Scientific Innovation Award

Assoc. Prof. Dr. Syed Saad Azhar Ali, Associate Professor, Saudi Arabia.

Dr. Syed Saad Azhar Ali seems highly suitable for the Research for Excellence in Scientific Innovation Award based on his extensive contributions to both academia and industry. Here are several key reasons why he qualifies:

Profile

Orcid

🎓 Education

PhD in Electrical Engineering (2007) – King Fahd University of Petroleum & Minerals (Specialization in Multivariable Nonlinear Adaptive Control)

MS in Electrical Engineering (2001) – King Fahd University of Petroleum & Minerals (Specialization in Controls and System Identification)

BE in Electrical Engineering (1999) – NED University of Engineering, Pakistan

👨‍🏫 Academic and Research Leadership

Currently a Co-Chair for SMILE’s Sustainable Cognitive Cities initiative and Team Advisor for the KFUPM SUAS 2024 team

Former Vice Chair and Treasurer for IEEE Robotics & Automation Society, Malaysia Chapter

Coordinator for the MX Program in Unmanned Aircraft Systems at KFUPM

Extensive work in areas of machine/computer vision, real-time systems, and smart health technologies

🏆 Awards and Recognition

Team Advisor for the SUAS 2024 championship-winning team, KFUPM

Multiple medals from ITEX, MTE, and SEDEX

Recognized by IEEE RAS, Malaysia, with Service and Excellence Awards

💼 Professional Affiliations

Senior Member of IEEE

Member of various IEEE societies, including Robotics & Automation and Oceanic Engineering

Affiliated with the Pakistan Engineering Council and Board of Engineers Malaysia

🌍 International Collaborations

Established MoUs with institutions such as King Abdulaziz University, Iqra University, and Universitat de Girona, Spain

📚 Publications 

Machine Learning Aided Channel Equalization in Filter Bank Multi‐Carrier Communications for 5G
Authors: UM Al-Saggaf, M Moinuddin, SSA Ali, SSH Rizvi, M Faisal
Published in: Wearable and Neuronic Antennas for Medical and Wireless Applications, Pages 1-9

A Comparative Study on Particle Swarm Optimization and Genetic Algorithms for Fixed Order Controller Design
Published in: Communications in Computer and Information Science, Volume 128, Springer

Block-Oriented Identification of Nonlinear Systems: Neural Network Approach towards Identification of Hammerstein and Wiener Models
Author: Syed Saad Azhar Ali
Published by: LAP Lambert Academic Publishing, ISBN: 978-3838335575, February 2010

U-model Based Control: Adaptive Control Approach for Multivariable Nonlinear Systems
Author: Syed Saad Azhar Ali
Published by: LAP Lambert Academic Publishing, ISBN: 978-3838323299, November 2009

Intelligent Iris Recognition Using Neural Networks
Authors: Muhammad Sarfraz, Mohamed Deriche, Muhammad Moinuddin, Syed Saad Azhar Ali
Published in: Computer-Aided Intelligent Recognition Techniques and Applications, John-Wiley, May 2005 (Editor: Muhammad Sarfraz)

 

Guangbo Yu | Artificial Intelligence | Best Researcher Award

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Mr. Guangbo Yu | Artificial Intelligence | Best Researcher Award

Mr .Guangbo  Yu, PhD Student, University of California, United States.

Mr. Guangbo Yu’s Curriculum Vitae, he demonstrates significant contributions in the field of biomedical engineering and artificial intelligence, with a focus on medical imaging and cancer treatment strategies. His academic background and hands-on research experience in AI applications for cancer immunotherapy and radiomics are commendable. Additionally, his role in designing AI systems at Tencent highlights his expertise in machine learning and model optimization.

Profile

google scholar

🎓 Education:

PhD in Biomedical Engineering (Expected 2027)

University of California, Irvine

Specialization: Radiological Science

Advisor: Prof. Zhuoli Zhang

Master’s in Computer Science

University of Southern California (2015–2017)

Bachelor’s in Software Engineering

University of Electronic Science and Technology of China (2011–2015)

🔬 Research Experience:

Graduate Assistant Researcher at UC Irvine (2022–Present)

Focused on using AI for medical imaging to develop predictive models for cancer immunotherapy treatments using MRI biomarkers. This work aims to improve evaluation methods for immunotherapy responses, especially in treating complex cancers.

💼 Professional Experience:

AI Engineer at Tencent QTrade (2020–2022)

Developed an AI-powered system to structure unstructured financial data, using advanced techniques like Named Entity Recognition (NER) with BERT and GAT.

Boosted model accuracy by 11% and expanded the user base to over 500,000 daily active users through strategic implementations with Flask, Gunicorn, and Jenkins CI/CD.

🔍 Research Interests:

Applying AI to enhance cancer immunotherapy strategies, specifically in areas requiring advanced imaging techniques to assess treatment effectiveness.

Citations:

Citations: 12 (all since 2019)

h-index: 2 (a minimum of two papers with at least two citations each)

i10-index: 0 (no papers with 10 or more citations)

📖 Publications and Presentations:

Qtrade AI at SemEval-2022 Task 11: A Unified Framework for Multilingual NER Task

W. Gan, Y. Lin, G. Yu, G. Chen, & Q. Ye. (2022). Association for Computational Linguistics.

Sorafenib Plus Memory-Like Natural Killer Cell Combination Therapy in Hepatocellular Carcinoma

A. Eresen, Y. Pang, Z. Zhang, Q. Hou, Z. Chen, G. Yu, Y. Wang, V. Yaghmai, … (2024). American Journal of Cancer Research, 14(1), 344.*

Dendritic Cell Vaccination Combined with Irreversible Electroporation for Treating Pancreatic Cancer—A Narrative Review

Z. Zhang, G. Yu, A. Eresen, Z. Chen, Z. Yu, V. Yaghmai, Z. Zhang. (2024). Annals of Translational Medicine.

MRI Radiomics to Monitor Therapeutic Outcome of Sorafenib Plus IHA Transcatheter NK Cell Combination Therapy in Hepatocellular Carcinoma

G. Yu, Z. Zhang, A. Eresen, Q. Hou, E. E. Garcia, Z. Yu, N. Abi-Jaoudeh, … (2024). Journal of Translational Medicine, 22(1), 76.*

Predicting and Monitoring Immune Checkpoint Inhibitor Therapy Using Artificial Intelligence in Pancreatic Cancer

G. Yu, Z. Zhang, A. Eresen, Q. Hou, F. Amirrad, S. Webster, S. Nauli, … (2024). International Journal of Molecular Sciences, 25(22), 12038.*

Sorafenib Plus Memory-Like Natural Killer Cell Immunochemotherapy Boosts Treatment Response in Liver Cancer

A. Eresen, Z. Zhang, G. Yu, Q. Hou, Z. Chen, Z. Yu, V. Yaghmai, Z. Zhang. (2024). BMC Cancer, 24(1), 1215.*

Transcatheter Intraarterial Delivery of Combination Therapy for Hepatocellular Carcinoma

Z. Zhang, A. Eresen, G. Yu, K. Liu, Q. Hou, V. Yaghmai. (2024). Journal of Vascular and Interventional Radiology, 35(3), S199.*

Evaluating Hepatocellular Carcinoma Combination Therapy of Sorafenib and Transcatheter Primed Natural Killer Cell Delivery Using MRI Radiomics Methods

G. Yu, A. Eresen, Z. Zhang, K. Liu, Q. Hou, V. Yaghmai. (2024). Journal of Vascular and Interventional Radiology, 35(3), S143–S144.*

Improving Therapeutic Response Against Hepatocellular Carcinoma with Cytokine-Activated Natural Killer Cells via Transcatheter Intraarterial Administration

A. Eresen, Z. Zhang, G. Yu, Q. Hou, N. Abi-Jaoudeh, V. Yaghmai. (2024). Journal of Vascular and Interventional Radiology, 35(3), S152.*

Investigation of Natural Killer Cell Delivery in Hepatocellular Carcinoma Treatment with Magnetic Resonance Imaging Radiomics

K. Liu, G. Yu, Z. Zhang, Q. Hou, V. Yaghmai, A. Eresen. (2024). Journal of Vascular and Interventional Radiology, 35(3), S92.*

MRI Monitoring of Combined Therapy with Transcatheter Arterial Delivery of NK Cells and Systemic Administration of Sorafenib for the Treatment of HCC

Z. Zhang, G. Yu, A. Eresen, Q. Hou, V. Yaghmai, Z. Zhang. (2024). American Journal of Cancer Research, 14(5), 2216.*