Bo Zhai | Healthcare Data Analysis | Best Researcher Award

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Prof Dr. Bo Zhai | Healthcare Data Analysis | Best Researcher Award

The Fourth Hospital of Harbin Medical University, China

Author Profile

Scopus

Early Academic Pursuits 📚

Dr. Bo Zhai, a highly respected Chief Physician and Associate Professor at The Fourth Hospital of Harbin Medical University, began his academic journey with a focus on hepatology and cell biology. After earning his MD, Dr. Zhai pursued advanced training as a Postdoctoral Fellow and later became a Fellow of the American College of Surgeons (FACS). His early academic work laid the foundation for his ongoing contributions to liver cancer research, particularly in the realm of hepatocellular carcinoma (HCC).

Professional Endeavors 🏥

Dr. Zhai has had a distinguished professional career, having served as a visiting scholar at the Liver Research Center of Brown University in the USA, sponsored by the National Foreign Experts Bureau. His work on liver cancer has been pivotal in understanding the complexities of HCC, a disease known for its resistance to conventional therapies like sorafenib. His international experience has broadened his research scope and enriched his academic and clinical expertise.

Contributions and Research Focus 🧬

Dr. Zhai’s primary research focus is on hepatocellular carcinoma (HCC), particularly how ASPH (Aspartate β-hydroxylase) influences cell death and contributes to chemoresistance in HCC. He has discovered that high levels of ASPH in HCC enhance proliferation, migration, and invasion, and also predict worse clinical outcomes for patients undergoing sorafenib treatment. His groundbreaking work suggests that targeting ASPH could break new ground in HCC therapy, overcoming the challenges posed by drug resistance.

Impact and Influence 🌍

Dr. Zhai’s research has had a significant impact on the field of liver cancer research, especially in understanding mechanisms of resistance to conventional cancer therapies. His studies on ASPH in HCC have opened new avenues for therapeutic interventions, providing insights into the role of autophagy, ferroptosis, and cell survival pathways in cancer progression. His work has been published in prestigious journals, including Cancer Letters, and is cited widely, underlining his contribution to the scientific community.

Academic Citations 📈

With an impressive citation index of 17.7, Dr. Zhai’s work is highly regarded in the academic community. His research publications, particularly those related to ASPH and HCC, have made substantial contributions to the understanding of liver cancer biology. His studies have provided valuable insights into the molecular mechanisms behind HCC’s resistance to chemotherapy, paving the way for new therapeutic strategies.

Technical Skills 🔬

Dr. Zhai has a wide range of technical skills, including expertise in molecular biology, cancer cell biology, and animal model studies. His proficiency in studying autophagy, ferroptosis, and tumor metastasis has made him a leader in the field of liver cancer research. Additionally, his experience with gene silencing and knockout models has allowed him to explore new potential targets for cancer treatment.

Teaching Experience 🧑‍🏫

As an Associate Professor, Dr. Zhai has contributed significantly to the education and mentoring of graduate and medical students. He has supervised numerous Master’s students and postdoctoral fellows, passing on his expertise in liver cancer research. His teaching extends beyond the classroom, as he is also involved in sharing his knowledge and findings through academic conferences and seminars.

Legacy and Future Contributions 🌱

Dr. Zhai’s legacy in liver cancer research is already well-established, with his groundbreaking work on ASPH setting the stage for future therapeutic developments. As he continues to pursue innovative approaches in HCC treatment, his research promises to lead to better clinical outcomes for patients battling liver cancer. His future contributions to the field will likely focus on developing targeted therapies that can overcome chemoresistance and improve patient survival rates.

Top Noted Publications 📖

ASPH dysregulates cell death and induces chemoresistance in hepatocellular carcinoma
    • Authors: Jingtao Li, Guocai Zhong, Fengli Hu, Qiushi Lin, Xiaoqun Dong, Bo Zhai
    • Journal: Cancer Letters
    • Year: 2024
Mechanisms of vascular co-option as a potential therapeutic target in hepatocellular carcinoma
    • Authors: Ming-Hao Qi, Jing-Tao Li, Bo Zhai
    • Journal: World Chinese Journal of Digestology
    • Year: 2024
Aspartate-β-hydroxylase as a promising prognostic and therapeutic biomarker for HBV-positive hepatocellular carcinoma
    • Authors: Jingtao Li, Zongwen Wang, Xiaohang Ren, WenYu Liu, Shicong Zeng, Bo Zhai
    • Journal: Research Square
    • Year: 2023
Is hepatic resection always a better choice than radiofrequency ablation for solitary hepatocellular carcinoma regardless of age and tumor size?
    • Authors: Shicong Zeng, Yao Zhang, Zongwen Wang, Qiankun Zhu, Yan Yan, Bo Zhai
    • Journal: Biomolecules & Biomedicine
    • Year: 2023
Identification of risk and prognostic factors for intrahepatic vascular invasion in patients with hepatocellular carcinoma: a population-based study
    • Authors: Shicong Zeng, Zongwen Wang, Qiankun Zhu, Fengli Hu, Lishan Xu, Bo Zhai
    • Journal: Translational Cancer Research
    • Year: 2022

Wei Liang | Healthcare Data Analysis | Best Researcher Award

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Dr. Wei Liang | Healthcare Data Analysis | Best Researcher Award

Doctorate at East China University of Science and Technology, China

 Author Profile 👨‍🎓

Early Academic Pursuits 🎓

Dr. Wei Liang embarked on his academic journey at East China University of Science and Technology, where he earned his Bachelor’s degree in Engineering (B.E.) in 2020. His interest in Brain-Computer Interfaces (BCI) and Machine Learning became evident during his undergraduate studies, setting the stage for his continued academic success. Currently, he is pursuing his PhD at the same institution, delving deeper into the intersection of neuroscience, computer science, and biomedical engineering. His early education laid a strong foundation for his research in the emerging field of BCI technology.

Professional Endeavors 💼

As a PhD candidate, Wei Liang is already contributing to the rapidly evolving field of Brain-Computer Interfaces, particularly in motor imagery and neural signal processing. His research involves collaboration with prominent experts in the fields of computer science, neuroscience, and biomedical engineering, such as Andrzej Cichocki, Ian Daly, and Brendan Allison. Liang’s professional journey has been shaped by these collaborations, allowing him to gain insights from diverse disciplines, further honing his expertise in BCI.

Contributions and Research Focus 🧠

Wei Liang’s research focuses on advancing Brain-Computer Interface (BCI) technology, particularly in motor imagery and neural signal processing. His work has led to the development of SecNet, a second-order neural network designed to improve motor imagery decoding from electroencephalography (EEG) signals. Liang’s innovative approaches include variance-preserving spatial patterns for EEG signal processing and the use of graph convolutional networks for optimal channel selection. These contributions have enhanced the accuracy and reliability of BCI systems, making them more applicable to real-world scenarios such as stroke rehabilitation and neural engineering.

Impact and Influence 🌍

Wei Liang’s work is making significant strides in improving BCI systems, which have far-reaching applications in medicine, rehabilitation, and human-computer interaction. By optimizing EEG decoding strategies, his research could impact the development of more effective neuroprosthetics and assistive technologies for individuals with motor impairments. His collaboration with leading researchers from around the world further amplifies the global impact of his work, positioning him as a rising star in BCI research.

Academic Citations 📚

Despite being in the early stages of his career, Wei Liang has already made a notable impact on the academic community. His research has led to the publication of five papers, accumulating a total of 14 citations and an h-index of 2. Notable papers include works published in Information Processing & Management, Frontiers in Human Neuroscience, and IEEE Journal of Biomedical and Health Informatics, among others. These publications highlight his contributions to improving BCI systems and their applications.

Technical Skills 🛠️

Wei Liang possesses a strong technical skill set, particularly in the areas of machine learning, neural network architecture, and EEG signal processing. He has expertise in developing novel algorithms for motor imagery decoding, including the use of second-order neural networks and graph convolutional networks. Liang is proficient in various computational tools and programming languages necessary for his research, positioning him as an expert in his field.

Teaching Experience 🏫

Though primarily focused on research, Wei Liang’s academic journey has also included some teaching experience, collaborating with faculty and providing guidance to students. His strong academic background, coupled with his research expertise, allows him to mentor and inspire others in the field of Brain-Computer Interfaces.

Legacy and Future Contributions 🌟

Wei Liang’s research trajectory holds great promise for shaping the future of Brain-Computer Interface technology. His innovative methodologies have the potential to revolutionize how we understand and utilize EEG signals for communication and rehabilitation. In the long term, his contributions could lead to breakthroughs in neuroprosthetics, enhancing the quality of life for individuals with disabilities. With continued dedication and innovation, Liang is on track to leave a lasting legacy in the realm of neuroscience and technology.

Teaching and Mentorship 🧑‍🏫

Although Liang is primarily focused on research, his experiences collaborating with top researchers and participating in academia have enriched his teaching and mentorship skills. His ability to translate complex ideas into understandable concepts makes him an effective communicator, ready to guide the next generation of researchers in the field of BCI.

Awards and Recognition 🏆

Wei Liang has been recognized for his groundbreaking research, publishing in high-impact journals and earning accolades for his contributions to BCI technology. As a promising young researcher, he is poised to receive even greater recognition as his work continues to influence and shape the future of the field.

Top Noted Publications📖

Novel Channel Selection Model Based on Graph Convolutional Network for Motor Imagery
    • Authors: W Liang, J Jin, I Daly, H Sun, X Wang, A Cichocki
    • Journal: Cognitive Neurodynamics
    • Year: 2023
Variance Characteristic Preserving Common Spatial Pattern for Motor Imagery BCI
    • Authors: W Liang, J Jin, R Xu, X Wang, A Cichocki
    • Journal: Frontiers in Human Neuroscience
    • Year: 2023
SecNet: A Second Order Neural Network for MI-EEG
    • Authors: W Liang, BZ Allison, R Xu, X He, X Wang, A Cichocki, J Jin
    • Journal: Information Processing & Management
    • Year: 2025
Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces
    • Authors: J Jin, W Chen, R Xu, W Liang, X Wu, X He, X Wang, A Cichocki
    • Journal: IEEE Journal of Biomedical and Health Informatics
    • Year: 2024
Leveraging Transfer Superposition Theory for StableState Visual Evoked Potential Cross-Subject Frequency Recognition
    • Authors: X He, BZ Allison, K Qin, W Liang, X Wang, A Cichocki, J Jin
    • Journal: IEEE Transactions on Biomedical Engineering
    • Year: 2024

Shuaa S. Alharbi | Bioimage informatics | Best Researcher Award

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Dr. Shuaa S. Alharbi | Bioimage informatics | Best Researcher Award

Doctorate at Department of Information Technology, College of Computer, Qassim University, Saudi Arabia

👨‍🎓Professional Profiles

Orcid Profile

Scopus Profile

👩‍💻 Summary

Dr. Shuaa S. Alharbi is an Assistant Professor in the Department of Information Technology at the College of Computer, Qassim University, Saudi Arabia. With a strong interdisciplinary background, she specializes in machine learning and image processing, particularly their applications in biomedical fields. Her research focuses on leveraging deep learning techniques to analyze medical images and improve diagnostic accuracy. Dr. Alharbi is dedicated to advancing bioinformatics and medical image analysis using cutting-edge technology.

🎓 Education

Dr. Alharbi holds a Ph.D. in Computer Science from Durham University, UK (2020), and both an M.Sc. and B.Sc. in Computer Science from Qassim University (2007) and King Saud University (2014), respectively. Her academic journey has provided her with a solid foundation in computer science, further augmented by extensive research in machine learning and bioimaging.

💼 Professional Experience

Dr. Alharbi has accumulated years of academic experience. She started as a Teaching Assistant at Qassim University in 2008, then progressed to Lecturer in 2015. Since 2020, she has served as an Assistant Professor at the same institution. Throughout her career, she has mentored students and contributed significantly to the academic environment at Qassim University, particularly in the Information Technology Department.

📝 Academic Committees & Administrative Roles

Dr. Alharbi has been deeply involved in various administrative roles at Qassim University. She served as E-content Supervisor (2020-2022), and currently coordinates the IT Department (2020-present). She is also a Postgraduate Supervisor (2023-present) and has been a Permanent Member of the Standing Committee for Assistance in the Scientific Council since 2023, contributing to the advancement of educational practices and research policies at the university.

🔬 Research Interests

Dr. Alharbi’s research interests are at the intersection of machine learning, image processing, and bioinformatics. She focuses on the application of deep learning for medical image analysis, working to enhance disease detection and diagnostic precision. Her work includes developing novel deep learning architectures and data-driven models to solve complex problems in medical and biological imaging.

🖥️ Technical Skills

Dr. Alharbi is proficient in a range of technical skills, including machine learning and deep learning frameworks, image and signal processing, computer graphics, and bioinformatics. She is experienced with programming languages such as Python, MATLAB, C++, and Java, and is adept at using these tools to solve complex problems in medical image analysis and other interdisciplinary fields.

📚 Teaching Experience

In addition to her research, Dr. Alharbi has taught several graduate-level courses, including Data Science, Computer Graphics, and Health Information Systems. She has also supervised Master’s theses in fields like cybersecurity, blockchain, and medical image processing, contributing to the academic growth of students in the Information Technology and Cybersecurity programs.

🌍 Conferences & Seminars

Dr. Alharbi has presented her work at prestigious international conferences, such as the IEEE BIBM International Conference on Bioinformatics and Biomedicine (Spain) and the Medical Image Computing Summer School at UCL (London). These platforms have allowed her to collaborate with global experts and stay at the forefront of research in bioimaging and machine learning.

💡 Research Grants

Dr. Alharbi was awarded a Coffee Research Grant from the Saudi Ministry of Culture, under the Saudi Heritage Preservation Society, showcasing her active involvement in research funding and promoting innovation in her fields of expertise.

 

📖 Top Noted Publications

nader tarabeih | Healthcare Data Analysis | Best Researcher Award

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Dr. nader tarabeih | Healthcare Data Analysis | Best Researcher Award

Dr. nader tarabeih at Ariel University, Israel

👨‍🎓Professional Profile

👨‍🔬 Summary

Dr. Nader Tarabeih is a dedicated researcher and clinician with a focus on genetic epidemiology and musculoskeletal disorders. Currently a postdoctoral researcher at Ariel University, his work centers on understanding inflammation-related biomarkers and their role in spinal pain. With a solid background in nursing, Dr. Tarabeih transitioned to academic research, publishing impactful studies on low back pain, metabolic factors, and their genetic causes.

🎓 Education

Dr. Tarabeih’s educational journey reflects his deep commitment to advancing medical research. He is currently pursuing a Post-doctoral position in Morphological Studies at the Adelson School of Medicine, Ariel University (2023 – Present). Previously, he completed his PhD in Genetic Epidemiology at Tel Aviv University (2018 – 2022), focusing on how blood biochemical factors and body composition affect spinal pain in complex Arab pedigrees. His MSc (2013 – 2016) also at Tel Aviv University examined genetic, demographic, and body composition risk factors for low back pain. Additionally, he holds a BA in Nursing from Tel Aviv University (2006 – 2010).

💼 Professional Experience

Dr. Tarabeih has gained extensive clinical and leadership experience in the healthcare field. He served as Director of Quality and Safety at the Maale HaCarmel Mental Health Center in Haifa, Israel (2020 – 2023). Prior to this, he worked as a Nurse at the same institution (2013 – 2020), where he applied his clinical expertise in a variety of settings, contributing to patient care and safety.

🔧 Technical Skills

Dr. Tarabeih brings a broad set of skills to his research and clinical practice. He is proficient in Genetic Epidemiology, specializing in the analysis of complex pedigrees and genetic risk factors for musculoskeletal disorders. His expertise extends to Biomarker Discovery, where he investigates biomarkers to improve the understanding and management of spinal pain. Additionally, he is skilled in Data Analysis and Clinical Research, focusing on inflammation, metabolic health, and spinal disorders.

👩‍🏫 Teaching Experience

Dr. Tarabeih has been an active contributor to academic discussions and has presented his research at several notable conferences. In 2022, he spoke on systemic biomarkers in degenerative lumbar spinal disorders at the Post-Genome Analysis for Musculoskeletal Biology Conference in Tzfat, Israel. He also presented on low back pain and its genetic and biochemical factors at the International Conference on Spine Disorders in Dubai, UAE (2020), and contributed a poster on genetic risk factors for low back pain at the BIRAX Ageing Conference in London, UK (2018).

🔬 Research Interests

Dr. Tarabeih’s research is driven by a passion for understanding the genetic and environmental causes of musculoskeletal disorders. His primary interests lie in Genetic Epidemiology, particularly in how genetic and lifestyle factors contribute to spinal pain. He is also dedicated to identifying biomarkers for pain-related disabilities and exploring the impact of inflammation and metabolism on musculoskeletal health in diverse populations.

 

📖 Top Noted Publications

Fernando López | Healthcare Data Analysis | Excellence in Research

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Assoc Prof Dr. Fernando López | Healthcare Data Analysis | Excellence in Research

Assoc Prof Dr. Fernando López at Hospital Clinico Universitario – Universidad de Valencia, Spain

👨‍🎓  Profile

Early Academic Pursuits 🎓

Dr. Fernando López began his academic journey at the Universidad de Cádiz, where he earned his Licenciatura in Medicine and Surgery from 1987 to 1993. His dedication led him to further his education through the Official Doctoral Program in Medicine and Surgery at the Universitat de València, culminating in a doctoral degree awarded with “Sobresaliente cum laude” in 2001.

Professional Endeavors 🏥

Dr. López completed his specialized training in General Surgery and Digestive System Surgery via the MIR program at the Hospital Clínico Universitario de Valencia from 1995 to 2000. He currently serves as an Associate Professor in the Department of Surgery at the Universitat de València, where he has been actively involved since 2011.

Contributions and Research Focus 🔍

Dr. López has made significant contributions to surgical research, particularly in the context of the COVID-19 pandemic. He is a co-author of several influential articles addressing surgical risks and outcomes during this crisis, with particular emphasis on the integration of machine learning for risk prediction. His work has been published in leading journals, reflecting his commitment to advancing surgical practices.

Impact and Influence 🌍

His research has garnered considerable attention, with publications in both national and international journals totaling 35, including articles in high-impact publications such as the British Journal of Surgery. His collaborative work with the COVIDSurg Collaborative has had a meaningful impact on surgical protocols during the pandemic.

Academic Cites 📚

Dr. López’s research has resulted in a notable cumulative impact factor of 76.697 across his indexed publications, illustrating the significant reach and influence of his work in the academic community.

Technical Skills ⚙️

As an experienced surgeon, Dr. López possesses a robust set of technical skills, particularly in advanced trauma and emergency care. He has been involved in teaching various advanced trauma life support courses and has contributed to international workshops, underscoring his proficiency and commitment to surgical education.

Teaching Experience 👨‍🏫

In addition to his clinical practice, Dr. López has extensive teaching experience, having tutored 35 residents in General Surgery and Digestive Surgery. He has organized and led numerous courses and seminars, including advanced trauma support training, reflecting his passion for educating the next generation of surgeons.

Legacy and Future Contributions 🌱

Looking ahead, Dr. López aims to continue his research in surgical safety and education, leveraging his experience and expertise to foster advancements in the field. His ongoing commitment to mentoring residents and collaborating on impactful research will undoubtedly leave a lasting legacy in the surgical community.

📖 Top Noted Publications

 

Characteristics of gastrointestinal stromal tumors associated to other tumors, 2024

Characteristics of gastrointestinal stromal tumors associated to other tumors, 2024

Glasbey, J. C., Nepogodiev, D., COVIDSurg Collaborative. (2021). Death following pulmonary complications of surgery before and during the SARS-CoV-2 pandemic. British Journal of Surgery, 6, pp. 1-19.

LUCENTUM Project Researchers. (2021). Simplified risk-prediction for benchmarking and quality improvement in emergency general surgery: Prospective, multicenter, observational cohort study. International Journal of Surgery, 97, pp. 1-35.

Glasbey, J. C., Nepogodiev, D., COVIDSurg Collaborative. (2021). Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score. British Journal of Surgery, 6, pp. 1-19.

Liu Yang | Bioinformatics | Best Researcher Award

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Prof Dr. Liu Yang | Bioinformatics | Best Researcher Award

Prof Dr. Liu Yang at Department of General Surgery, Jiangsu Cancer Hospital, China

👨‍🎓 Profile

👨‍⚕️ Current Position

Prof. Dr. Yang Liu is a Chief Physician and Associate Professor, serving as the Deputy Head of General Surgery at Jiangsu Cancer Hospital and the Head of Colorectal Surgery at Nanjing Medical University.

📜 Summary

Yang Liu is a prominent figure in colorectal surgery, also acting as a Master’s Supervisor and visiting overseas researcher at Thomas Jefferson University’s BluConner Hospital. His work has earned him multiple accolades in cancer research.

🎓 Education

Yang has completed his medical degree and advanced training in colorectal surgery, although specific institutions are not detailed here.

🏥 Professional Experience

With a focus on complex minimally invasive surgeries, he performs over 150 advanced procedures annually and actively participates in various national and provincial medical associations.

🔬 Research Interests

His research primarily explores ncRNA genomics in relation to colorectal cancer progression and metastasis, alongside developing innovative surgical techniques.

💡 Patents

Yang holds several patents, including:

  • 2024: Combination of Scutellarein for colorectal cancer treatment.
  • 2023: Multi-angle puncture holder.
  • 2020: Circ-0000423 for colorectal cancer drug development.
  • 2019: Surgical retractor for lower abdominal tumors.

🏆 Awards

He has received notable awards such as:

  • 2021: 2nd Prize for New Medical Technology in Jiangsu for epigenetic fusion in colorectal cancer.
  • 2019: 2nd Prize for his study on LINC00152 in colorectal cancer.
📖  Top Noted Publications

LUCAT1 inhibits ferroptosis in bladder cancer by regulating the mRNA stability of STAT3

  • Authors: Cao, Y., Zou, Z., Wu, X., Hu, J., Yang, L.
    Journal: Gene
    Year: 2024

Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer

  • Authors: Ye, Y.-X., Yang, L., Kang, Z., Du, M., Li, Z.-X.
    Journal: World Journal of Gastrointestinal Oncology
    Year: 2024

Emerging Role of ERBB2 in Targeted Therapy for Metastatic Colorectal Cancer: Signaling Pathways to Therapeutic Strategies

  • Authors: Wang, N., Cao, Y., Si, C., Bao, J., Yang, L.
    Journal: Cancers
    Year: 2022

FBXW7 and Its Downstream NOTCH Pathway Could be Potential Indicators of Organ-Free Metastasis in Colorectal Cancer

  • Authors: Li, D., Jiang, S., Zhou, X., Sun, Y., Yang, L.
    Journal: Frontiers in Oncology
    Year: 2022

Anal preservation on the psychology and quality of life of low rectal cancer

  • Authors: Mei, F., Yang, X., Na, L., Yang, L.
    Journal: Journal of Surgical Oncology
    Year: 2022