Ester Gilart Cantizano | AI in Healthcare | Best Researcher Award

Prof. Dr. Ester Gilart Cantizano | AI in Healthcare | Best Researcher Award

Department of Nursing and Physiotherapy, University of Cadiz, Spain

Ester Gilart Cantizano is a dedicated academic and healthcare researcher whose work bridges innovative nursing education and applied clinical research. With a strong background in nursing sciences, she has developed a robust academic profile integrating research, teaching, and international collaboration. Her scholarly output reflects a commitment to advancing nursing knowledge and contributing to the mental health and professional well-being of healthcare providers. Ester’s active participation in international congresses and scientific publications has positioned her as a significant contributor to evidence-based nursing education and practice.

Profile

Scopus

Education

Ester began her academic journey with a Bachelor’s degree in Nursing in 2016, followed by a Master’s in Nursing Research and Advanced Professional Practice in 2018. She later earned two postgraduate expert qualifications—one in Surgical Anesthesiology for Nurses (2019) and another in Gynecological Nursing Care (2020). Currently, she is completing a PhD in Health Sciences, with a dissertation focused on the post-COVID-19 emotional impacts on nursing professionals, including the development and validation of a professional traumatic grief inventory. Her academic training is supplemented by more than 50 specialized courses that reflect her commitment to continuous education.

Experience

Professionally, Ester has cultivated a multifaceted career combining clinical practice, teaching, and research. Her clinical experience in both public and private hospitals has enriched her teaching approach, allowing her to merge practical skills with theoretical instruction. At the University of Cádiz, she has taught over 600 hours across subjects such as pharmacology, community nursing, occupational health, and bioethics. Her commitment to academic excellence extends to coordinating and evaluating undergraduate theses, conducting specialized training sessions, and implementing active learning strategies in university classrooms. She also served as a mentor for practicum courses and developed evaluation rubrics to assess communication skills.

Research Interest

Ester’s primary research interests include mental health in healthcare professionals, professional grief, nursing education methodologies, and diagnostic label validation. She is a key member of the research group “Present, Past, and Future of Nursing: Innovation, Teaching, and Development” at the University of Cádiz. Her research focuses on designing psychometric instruments and exploring psychological stressors such as unemployment syndrome and grief among nurses. Her current doctoral research investigates the psychological effects of COVID-19 on nurses, aiming to create tools that enhance mental well-being and workplace support structures.

Award

Her contributions to nursing education and mental health research have earned her national and international recognition. She has presented findings at over 20 scientific congresses, including the prestigious Sociedade Espanhola de Epidemiología and Associação Portuguesa de Epidemiologia. She also undertook a notable research stay at the University of Naples in 2024, where she studied the impact of the COVID-19 pandemic on hospital staff’s mental health. This international collaboration enriched her doctoral work and expanded her methodological toolkit for assessing psychological resilience and trauma.

Publication

  1. Healthcare, 2023 – “Identifying Hate Speech and Attribution of Responsibility” – cited by 2 articles.

  2. International Journal of Environmental Research and Public Health, 2022 – “Bereavement Needs Assessment in Nurses” – cited by 5 articles.

  3. International Journal of Nursing Knowledge, 2021 – “Psychometric Properties of Unemployment Syndrome Scale” – cited by 1 article.

  4. International Journal of Environmental Research and Public Health, 2021 – “Unemployment Syndrome During COVID-19” – cited by 9 articles.

  5. International Journal of Nursing Knowledge, 2019 – “Development of a Scale to Measure Unemployment Syndrome” – cited by 2 articles.

  6. Healthcare, 2021 – “When Nurses Become Patients” – cited by 8 articles.

  7. Nursing Reports, 2024 – “Predictive Model for Resilience in Family Caregivers” – recent publication, citations pending.

Conclusion

Ester Gilart Cantizano embodies the synthesis of practice, pedagogy, and research in modern nursing. Her academic journey, rich with advanced degrees and specialized training, reflects her drive to improve healthcare delivery and professional resilience. Through validated psychometric tools and innovative teaching methods, she has significantly influenced both her students and the broader healthcare community. Her leadership in traumatic grief research and her ongoing efforts in international collaboration highlight her as a prominent figure in the evolution of nursing science.

Yuriy Gusev | AI in Healthcare | Best Use of Data in Healthcare Award

Assoc. Prof. Dr. Yuriy Gusev | AI in Healthcare | Best Use of Data in Healthcare Award

Director of Health Informatics and Data Science Program at Georgetown University, United States

Yuriy Gusev is an esteemed Associate Professor of Bioinformatics at Georgetown University Medical Center’s Innovation Center for Biomedical Informatics (ICBI) and Department of Oncology. He is recognized for his extensive expertise in computational biology, bioinformatics, and systems biology, with a particular focus on cancer research. Dr. Gusev has dedicated his career to bioinformatics, computational modeling, and the development of innovative bioinformatics tools and methodologies. He also plays a leading role in the Health Informatics and Data Science graduate program, and co-directs the Biostatistics and Bioinformatics Shared Resource at the Lombardi Cancer Center. Throughout his career, Dr. Gusev has contributed significantly to multi-institutional cancer research efforts, particularly through large-scale studies, including the Georgetown Database of Cancer (G-DOC), and various NIH-funded programs.

Profile

Scopus

Education

Dr. Gusev’s academic journey began with a Master of Science in Applied Mathematics from State University of St. Petersburg in Russia. He later earned his Ph.D. in Computational Biology from the Central Research Institute of Roentgenology & Radiology in St. Petersburg, Russia. Dr. Gusev further honed his expertise with a postdoctoral position at the Waksman Institute, Rutgers University, where he focused on Computational Modeling in Cancer Research. These experiences laid the foundation for his innovative approach to bioinformatics and cancer research.

Experience

Dr. Gusev’s professional journey spans over three decades, with pivotal positions at several renowned institutions. After his postdoctoral work at Rutgers, he held various roles, including faculty research associate at Johns Hopkins University, senior research scientist at Molecular Staging Inc., and assistant professor at the University of Oklahoma Health Sciences Center. In 2009, he joined Georgetown University as an Associate Professor. Alongside his academic appointments, Dr. Gusev has directed numerous research projects and collaborated extensively in multi-disciplinary research programs across cancer genomics, bioinformatics, and computational biology.

Research Interests

Dr. Gusev’s research interests lie at the intersection of computational biology, bioinformatics, and cancer research. His primary focus includes the study of tumor heterogeneity, chromosomal instability, microRNA, and long-noncoding RNA regulation in cancer. He is particularly invested in the application of computational models and bioinformatics methods to analyze large-scale genomic and transcriptomic data. Dr. Gusev is also passionate about integrating molecular, imaging, and clinical data to advance personalized medicine and precision oncology. His work involves high-throughput data analysis, machine learning techniques for biomarker discovery, and the development of cloud-based platforms to streamline cancer research workflows.

Awards

Dr. Gusev has been recognized with numerous accolades throughout his career. Notable awards include the Charles and Johanna Bush Postdoctoral Fellowship, NSF travel awards for his work in tumor heterogeneity and mathematical population dynamics, and the Executive Leadership Award from the Mid-South Computational Biology and Bioinformatics Society. His contributions to computational cancer research were further acknowledged with the 2008 Executive Leadership Award, and his research impact continues to be recognized by various scientific bodies.

Publications

Dr. Gusev has authored or co-authored numerous influential publications. His research in tumor heterogeneity, chromosomal instability, and microRNA profiling has resulted in multiple highly cited papers. Some key publications include:

Axelrod DE, Gusev Y, Kuczek T. “Persistence of cell cycle times over many generations as determined by heritability of colony sizes of ras oncogene-transformed and non-transformed cells.” Cell Proliferation, 1993, 26(3), 235-249.

Gusev Y, Kagansky V, Dooley WC. “Long-term dynamics of chromosomal instability in cancer: a transition probability model.” Mathematical and Computer Modelling, 2001, 33(12), 1253-1273.

Gusev Y, Bhuvaneshwar K, Song L, Zenklusen JC, Fine H, Madhavan S. “The REMBRANDT study, a large collection of genomic data from brain cancer patients.” Nature Scientific Data, 2018; 5:180158.

Bhuvaneshwar K, Belouali A, Singh V, et al. “G-DOC Plus – an integrative bioinformatics platform for precision medicine.” BMC Bioinformatics, 2016; 17(1):193.

Lei Song, Krithika Bhuvaneshwar, Yue Wang, et al. “CINdex: a bioconductor package for analysis of chromosome instability in DNA copy number data.” Cancer Informatics, 2017, Volume 16, PMID: 29343938.

His works have been cited extensively, contributing to advances in cancer bioinformatics, precision oncology, and the study of molecular biomarkers in cancer.

Conclusion

Dr. Yuriy Gusev has made significant contributions to the field of computational biology and bioinformatics, particularly in cancer research. His work has greatly advanced the understanding of tumor heterogeneity, chromosomal instability, and non-coding RNA regulation in cancer. As an educator, researcher, and leader, he continues to influence the development of bioinformatics tools and platforms that facilitate precision medicine. Dr. Gusev’s expertise in computational modeling, genomic data analysis, and multi-omics integration positions him as a pivotal figure in cancer research and bioinformatics. His ongoing efforts to apply innovative computational approaches to clinical oncology will undoubtedly lead to further breakthroughs in cancer treatment and personalized therapies.