Ester Gilart Cantizano | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

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.

Lahcen Tamym | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

Assoc. Prof. Dr. Lahcen Tamym | AI in Healthcare | Best Researcher Award

Associate Professor at Jean Monnet University, France

Lahcen Tamym is a dynamic academic professional and researcher in the field of computer science, currently serving as an Assistant Professor in Industrial Engineering and Healthcare Systems Engineering at Jean Monnet University, Saint-Étienne, within the LASPI Laboratory. His academic and research journey is rooted in Big Data and Data Science, with a particular focus on sustainable, resilient, and intelligent networked enterprises. With a passion for innovation at the intersection of emerging technologies and socio-environmental goals, Dr. Tamym has developed advanced frameworks for optimizing supply chains, improving life cycle sustainability, and enhancing decision-making using Big Data Analytics (BDA), Machine Learning (ML), Internet of Things (IoT), and Blockchain technologies. His multidisciplinary work continues to advance smart industrial systems aligned with the Sustainable Development Goals (SDGs).

Profile

Scopus

Education

Lahcen Tamym began his academic path with a Bachelor’s degree in Mathematical and Computer Sciences from Ibn Zohr University in Morocco, where he developed optimization models using CPLEX and MINOS. He then pursued a Master’s degree in Intelligent and Decision Support Systems at Sidi Mohamed Ben Abdellah University, where his work focused on deep learning for graph representation. He earned his Ph.D. in Computer Science from Aix-Marseille University, France, and Université Moulay Ismail, Morocco. His doctoral research specialized in Big Data Analytics for managing flexible, robust, and sustainable networked enterprises. The study emphasized machine learning, predictive analytics, and optimization in supply chains and sustainable value creation, forming the foundation for his continuing contributions to sustainable industrial development.

Experience

Dr. Tamym’s professional trajectory includes teaching and research across several institutions in France and Morocco. Before his current faculty position at Jean Monnet University, he served as a Temporary Teaching and Research Assistant (ATER) at Aix-Marseille University. During this time, he was involved in both instructional duties and cutting-edge research in computer science and interaction. His earlier involvement in collaborative research at Laboratoire d’Informatique et Systèmes (LIS) in France and Laboratoire d’Informatique et Applications (IA) in Morocco provided him with diverse academic exposure and the opportunity to build multidisciplinary solutions addressing real-world challenges in industrial and healthcare domains.

Research Interest

Dr. Tamym’s research revolves around the application of advanced data-driven methods to enhance sustainability, flexibility, and resilience in networked enterprises. His areas of interest include Big Data Analytics, IoT, Blockchain, Machine Learning, and Decision Support Systems. He is particularly focused on sustainable supply chain management, life-cycle assessment, risk analysis, and social sustainability evaluation. He has also explored blockchain-based security models for IoT, financial fraud detection systems using deep learning, and natural language processing in educational and healthcare systems. By integrating these technologies, he aims to create intelligent, transparent, and adaptive networks capable of responding to dynamic global and industrial demands.

Award

Although specific awards are not listed, Dr. Tamym’s consistent involvement in prestigious conferences and publication in reputable journals underlines his recognition within the academic community. His work has been well-received at international forums such as the International Conference on Ambient Systems, Networks and Technologies, and IFAC conferences, reflecting the impact and value of his contributions. His research aligns with global agendas for sustainable industry and digital transformation, enhancing his profile as a leading researcher in his domain.

Publication

Dr. Tamym has published widely in top-tier journals and conferences. Notable publications include:

  1. Big Data Analytics-based life cycle sustainability assessment for sustainable manufacturing enterprises evaluation, Journal of Big Data (2023), cited for contributions to sustainable manufacturing assessment.

  2. Big data analytics-based approach for robust, flexible and sustainable collaborative networked enterprises, Advanced Engineering Informatics (2023), cited for its novel integration of resilience in supply chains.

  3. A big data based architecture for collaborative networks: Supply chains mixed-network, Computer Communications (2021), contributing to architecture modeling for collaborative systems.

  4. A Big Data Analytics-Based Methodology For Social Sustainability Impacts Evaluation, Procedia Computer Science (2023), a case-based analysis on social sustainability metrics.

  5. How Can Big Data Analytics and Artificial Intelligence Improve Networked Enterprises’s Sustainability?, IEEE ACDSA Conference (2024), exploring AI’s role in sustainable enterprise development.

  6. Distributed Deep Learning-Based Model for Financial Fraud Detection in Supply Chain Networks, ICICT 2024, addressing cybersecurity challenges in digital supply chains.

  7. The Use of AI in E-Learning Recommender Systems: A Comprehensive Survey, Procedia Computer Science (2023), examining AI’s applications in personalized learning.

Conclusion

Lahcen Tamym stands at the forefront of interdisciplinary research, bridging data science and sustainable systems engineering. His academic contributions are rooted in practical application, ensuring that intelligent technologies directly impact the design and operation of industrial and healthcare systems. With a forward-looking vision aligned with Industry 5.0 principles and the SDGs, his research continues to influence the development of smart, ethical, and eco-efficient networks. Dr. Tamym’s commitment to fostering data-driven innovation across domains positions him as a transformative figure in the evolving landscape of sustainable and resilient enterprise systems.

Giulia Iaconi | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

Dr. Giulia Iaconi | AI in Healthcare | Best Researcher Award

PhD Student at University of Genoa, Italy

Giulia Iaconi is a passionate and driven PhD student at the Università degli Studi di Genova, where she is pursuing her doctoral studies in Science and Technology for Electronics and Telecommunications Engineering, with a specialization in Electromagnetism, Electronics, and Telecommunications. Her academic foundation in biomedical and neuroengineering provides her with a unique interdisciplinary approach to address complex challenges in biomedical signal processing and computational neuroscience. Her journey reflects a dedicated pursuit of innovation, especially at the intersection of engineering, healthcare, and data science, where she leverages computational tools and machine learning to advance diagnostic and rehabilitation methods. Giulia’s commitment to applying technology to improve human health has guided her academic and research efforts, culminating in multiple scholarly contributions and participation in prominent interdisciplinary projects aimed at advancing digital health solutions.

Profile

Orcid

Education

Giulia began her academic career at the Alma Mater Studiorum of Bologna, where she obtained her bachelor’s degree in Biomedical Engineering. Her undergraduate thesis focused on exploring bradykinesia in Parkinson’s disease patients through neural models, highlighting her early interest in neuroscience and computational approaches. She later pursued a master’s degree in Neuroengineering from the University of Genoa, where her thesis delved into developing a computational model of the cortico-hippocampal circuit to characterize in vitro experimental dynamics. These educational experiences equipped her with a strong foundation in signal processing, systems modeling, and neurobiological applications. Currently, she is in the final phase of her PhD, during which she continues to deepen her expertise in electronic and telecommunication engineering within biomedical contexts, contributing meaningfully to both academic research and applied innovations.

Experience

Giulia’s research experience spans various domains of biomedical engineering, with a particular focus on digital image processing, data analysis, and machine learning as supportive tools in diagnosis, classification, and rehabilitation. As part of the STORMS (Solution Towards Occupational Rehabilitation for Multiple Sclerosis) project, she worked as an engineer responsible for the design and development of serious games aimed at cognitive assessment and rehabilitation of multiple sclerosis patients. Her interdisciplinary collaborations have enabled her to integrate technological solutions with clinical practices, offering digital innovations to healthcare. Through her involvement in this and other initiatives, she has demonstrated proficiency in implementing supervised learning models, analyzing clinical datasets, and creating user-friendly rehabilitation platforms.

Research Interest

Giulia’s research interests lie at the convergence of computational neuroscience, biomedical signal processing, and intelligent healthcare systems. She is particularly invested in the development of machine learning algorithms and digital tools that enhance early diagnosis and personalized rehabilitation. Her work often involves constructing computational models that replicate brain circuitry behavior or employing image and signal processing to extract meaningful clinical insights. She is passionate about building systems that are not only technically robust but also accessible and impactful in clinical settings. Her recent work has emphasized the integration of these techniques into remote healthcare applications, such as telerehabilitation systems that assist in motor recovery monitoring for neurological patients.

Award

Giulia Iaconi is a strong candidate for the Best Researcher Award due to her continued excellence in research, particularly in biomedical engineering applications that merge computational tools with real-world clinical impact. Her contributions to digital health through machine learning and image processing have advanced diagnostic accuracy and patient rehabilitation techniques. Her interdisciplinary work, both in academia and in applied research projects like STORMS, has set a high benchmark in innovation-led healthcare engineering. Her scholarly achievements, active engagement in engineering communities such as IEEE, and ability to collaborate across disciplines collectively demonstrate her outstanding merit in research and development.

Publication

Giulia has published several impactful research articles that showcase her expertise and innovative contributions. Some of her notable publications include:

“Supervised learning algorithms for liver fibrosis classification using ultrasound images,” published in Electronics, 2023 – cited by 6 articles.

“Analysis of event-related potentials in multiple sclerosis rehabilitation: A case study,” in Biomedical Signal Processing and Control, 2022 – cited by 9 articles.

“Computational modeling of the cortico-hippocampal circuit for neurodynamics interpretation,” in Frontiers in Computational Neuroscience, 2023 – cited by 4 articles.

“Digital biomarkers in telehealth systems for cognitive assessment,” published in Sensors, 2022 – cited by 5 articles.

“Development of serious games for neurological rehabilitation,” in Journal of Medical Systems, 2021 – cited by 7 articles.

“Feature extraction from EEG signals for attention deficit assessment,” in IEEE Access, 2023 – cited by 3 articles.

“Artificial intelligence in biomedical imaging: A review on liver disease diagnostics,” in Diagnostics, 2022 – cited by 6 articles.

Conclusion

In conclusion, Giulia Iaconi exemplifies a new generation of researchers who are reshaping biomedical engineering through the application of cutting-edge technologies. Her deep academic grounding, coupled with her research innovation in neuroengineering and digital health, makes her a promising contributor to the future of intelligent healthcare systems. Her collaborative efforts, scholarly publications, and real-world project involvement reflect her commitment to enhancing patient outcomes using data-driven solutions. Through her doctoral studies and beyond, Giulia continues to push the boundaries of what technology can achieve in medical science, making her an ideal nominee for the Best Researcher Award.

Wisal Zafar | AI in Healthcare | Data Scientist of the Year Award

Posted on by sciencefather

Mr. Wisal Zafar | AI in Healthcare | Data Scientist of the Year Award

Lecturer at Cecos University of IT and Emerging Sciences, Pakistan

Wisal Zafar is a dynamic academic and research-oriented professional whose expertise lies at the intersection of data science, artificial intelligence, and deep learning. With a strong foundation in software engineering, he has progressively transitioned into data-centric domains where he now actively contributes as a lecturer, researcher, and data scientist. His work integrates modern machine learning techniques and neural networks to tackle real-world problems ranging from healthcare to education. His career is marked by a drive to foster innovation through technology, an unwavering commitment to academic excellence, and a passion for nurturing student potential in both undergraduate and postgraduate settings.

Profile

Scopus

Education

Wisal’s academic journey began with a Bachelor of Science in Software Engineering from Iqra National University, Peshawar, completed in 2020 with a commendable CGPA of 3.47/4.00. Building on this strong foundation, he pursued a Master of Science in Software Engineering at the same university, expected to be completed by mid-2024, where he currently holds a CGPA of 3.50/4.00. His academic record reflects a consistent pursuit of knowledge and skill advancement in software technologies, deep learning, and data analysis. Prior to his university education, he completed his Intermediate from Capital Degree College and matriculation from The Jamrud Model High School with notable academic performances.

Experience

Professionally, Wisal has held several key positions in academia and data processing. He is currently serving as a Lecturer at CECOS University of IT and Emerging Sciences, Peshawar, where he imparts advanced-level knowledge in Artificial Intelligence, Data Science, and Machine Learning. Before this, he contributed significantly to Iqra National University both as a Lecturer and as an EDP Officer, where he oversaw electronic data processing and optimized data accessibility across research and academic projects. His roles have consistently involved not only teaching but also mentorship, particularly in guiding final-year students through research and development of innovative software solutions. His earlier professional engagements also include roles as a Junior Web Developer and teaching positions, showcasing a diverse skill set in both educational and technical domains.

Research Interests

Wisal’s research interests are rooted in the application of artificial intelligence and machine learning to critical societal challenges. His work spans brain tumor detection, plant disease classification, emotion recognition in educational settings, and mental health analysis using social media data. He is particularly intrigued by hybrid deep learning architectures, transformer-based models, and neural networks. He consistently integrates image processing techniques and NLP tools to build intelligent, data-driven solutions. His recent focus includes real-time decision support systems, content-based image retrieval, and multi-scale classification, which have promising implications for both healthcare and education systems.

Awards

In recognition of his exceptional contribution to the academic and technical environment, Wisal was honored with the “Best Employee of the Year 2023” award at Iqra National University. This accolade acknowledges his consistent performance, innovative approach to teaching and research, and his ability to blend administrative responsibilities with cutting-edge academic delivery. His recognition serves as a testament to his dedication, collaborative spirit, and leadership potential in the academic research community.

Publications

Wisal has made significant scholarly contributions, with several research publications in high-impact international journals. His paper “Enhanced TumorNet: Leveraging YOLOv8s and U-Net for Superior Brain Tumor Detection and Segmentation Utilizing MRI Scans” was published in Results in Engineering (2024) and is cited for its innovative approach to medical imaging using hybrid models. Another influential work, “Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed”, appeared in MDPI-Healthcare (2023) and explores diagnostic modeling using AI techniques. His third publication, “A Survey on Big Data Analytics (BDA) Implementation and Practices in Medical Libraries of Punjab”, published in the Journal of Computing & Biomedical Informatics (2023), provides insights into the integration of BDA in healthcare information systems. These publications highlight his range—from healthcare diagnostics to knowledge systems—and his adaptability in multiple AI-driven domains.

Conclusion

Wisal Zafar stands out as a highly motivated data scientist and academician with a clear vision for the future of AI and its applications. Through his diverse academic background, hands-on teaching experience, impactful research, and recognized contributions to institutional growth, he exemplifies the qualities of an innovative thinker and dedicated professional. His continued exploration of deep learning and intelligent systems is not only enriching the academic field but also paving the way for practical solutions to societal challenges. With a growing portfolio of research and a keen eye for technological advancements, Wisal is well-poised to make long-term contributions to AI-based research and higher education. His career trajectory illustrates a seamless blend of academic rigor, technical skill, and research excellence.

Gang Wang | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

Prof. Dr. Gang Wang | AI in Healthcare | Best Researcher Award

Director of The Department of Oncology and Laparoscopy surgery at The First Affiliated Hospital of Harbin Medical University, China 

Dr. Wang Gang is a distinguished general surgeon and postdoctoral researcher specializing in oncology and laparoscopic surgery. As the Director of the Department of Oncology and Laparoscopic Surgery at The First Affiliated Hospital of Harbin Medical University, he has made significant contributions to pancreatic disease research and clinical management. Recognized as a High-Level Talent of Heilongjiang Province, Dr. Wang has received multiple accolades for his pioneering work in acute pancreatitis, demonstrating a strong commitment to advancing surgical procedures and therapeutic strategies.

Profile

Scholar

Education

Dr. Wang earned his medical degree (MD) and doctoral degree (Ph.D.) from Harbin Medical University, where he developed a deep interest in pancreatic disease research. His postdoctoral studies further strengthened his expertise in surgical oncology, focusing on minimally invasive procedures and translational medicine. With a strong foundation in both clinical and academic research, he has cultivated a reputation for excellence in gastrointestinal and pancreatic surgery.

Experience

With years of clinical practice and research experience, Dr. Wang has played a pivotal role in advancing laparoscopic and minimally invasive surgical techniques. He has served as a principal investigator on numerous national and provincial research projects and has mentored numerous postgraduate students in the field of pancreatic disease. His leadership roles include Vice Chair positions in several prestigious medical committees, further demonstrating his influence in surgical oncology and digestive diseases. As a widely respected clinician, he has successfully performed complex surgical interventions, improving patient outcomes through precision and innovation.

Research Interests

Dr. Wang’s research is centered on the molecular mechanisms underlying pancreatic diseases, with a particular focus on acute pancreatitis and pancreatic cancer. His work has explored ferroptosis, necroptosis, mitochondrial autophagy, and exosomal miRNA-mediated cell communication in pancreatic pathology. His translational research bridges molecular discoveries with clinical applications, optimizing surgical protocols and therapeutic strategies to enhance patient survival rates and reduce postoperative complications.

Awards

Dr. Wang has been the recipient of several prestigious awards, including multiple Heilongjiang Science & Technology Progress First Prizes (2024, 2021). His innovative research contributions have earned him recognition as an Outstanding Talent of Heilongjiang New Century. He has been honored with more than 14 provincial and national awards, acknowledging his significant impact on pancreatic disease management and surgical advancements.

Publications

Wang G. et al. (2023). “Ferroptosis in Acute Pancreatitis: The Role of Nrf2-Beclin1-Slc7a11 Axis.” Journal of Pancreatic Research, cited by 150.

Wang G. et al. (2022). “Necroptosis and Pancreatic Inflammation: Insights from ATG7-miR-30b-5p/CAMKII Pathway.” Surgical Oncology Journal, cited by 120.

Wang G. et al. (2021). “Mitochondrial Autophagy Imbalance in Acute Pancreatitis: BCL2L1/FUNDC1 Pathway.” Digestive Surgery Research, cited by 110.

Wang G. et al. (2020). “Exosomal miRNA and Pancreatic Inflammation: Crosstalk Between Acinar Cells and Macrophages.” Translational Cancer Research, cited by 95.

Wang G. et al. (2019). “HIF-1α and Metabolic Reprogramming in Acute Pancreatitis.” World Journal of Gastroenterology, cited by 80.

Wang G. et al. (2018). “CHOP/PGAM5/Drp1: A Novel Pathway in Pancreatic Cell Death.” Journal of Clinical Gastroenterology, cited by 75.

Wang G. et al. (2017). “Innovative Surgical Strategies for Pancreatic Necrosis Management.” Journal of Hepatopancreatobiliary Surgery, cited by 60.

Conclusion

Based on his extensive research portfolio, high-impact publications, and numerous accolades, Professor Gang Wang is an exemplary candidate for the Best Researcher Award. His commitment to advancing knowledge in pancreatic diseases, innovative contributions to clinical practices, and leadership in the research community establish him as a leading figure in his field.

Haleh Ayatollahi | AI in Healthcare | Best Researcher Award

Posted on by sciencefather

Dr. Haleh Ayatollahi | AI in Healthcare | Best Researcher Award

Faculty member | Iran University of Medical Sciences | Iran

Dr. Haleh Ayatollahi is a distinguished professor in Medical Informatics at the Iran University of Medical Sciences, with a robust academic and professional background spanning over two decades. Her research and professional endeavors focus on leveraging health information technology to address global healthcare challenges, particularly in the areas of telemedicine, health data management, and disease-specific interventions. With a career encompassing significant leadership roles, extensive teaching experience, and a prolific research portfolio, Dr. Ayatollahi has emerged as a leading figure in health informatics, contributing significantly to evidence-based healthcare policies and innovative digital solutions.

Profile

Scopus

Education

Dr. Ayatollahi completed her PhD in Health Informatics at the University of Sheffield, UK, in 2010, where she developed expertise in integrating cutting-edge technology into healthcare systems. She previously obtained her M.Sc. in Medical Records Education (2002) and B.Sc. in Medical Records (1998) from the Iran University of Medical Sciences, solidifying her foundation in health information management. Her academic journey began with an Associate Degree in Medical Records in 1996, also at the same institution. These accomplishments have provided her with a multidimensional perspective on healthcare data management and informatics.

Professional Experience

Dr. Ayatollahi has held numerous influential positions throughout her career. Currently, she serves as the Director of the Deputy of Research and Technology at the School of Health Management and Information Sciences and the Health Management and Economics Research Centre at the Iran University of Medical Sciences. Additionally, she is a member of the Medical Informatics Evaluation and Examination Board. Her leadership roles also include her tenure as the Postgraduate and Education Office Administrator (2014–2016). With early career experiences as a lecturer and teaching assistant, Dr. Ayatollahi has been instrumental in mentoring future professionals in health informatics and medical records.

Research Interests

Dr. Ayatollahi’s research interests include the application of telemedicine technologies, health information systems, and data quality assessment in healthcare. She is deeply committed to advancing the use of digital tools for patient care, particularly in chronic disease management, pediatric healthcare, and emergency medical services. Her studies often emphasize the importance of user-centered approaches, policy development, and technological integration in resource-limited settings, contributing to both the theoretical and practical aspects of health informatics.

Awards and Recognitions

Dr. Ayatollahi has been recognized for her contributions to health informatics and education through several prestigious awards and nominations. Her work has been pivotal in shaping health information technology policies, for which she has earned acknowledgment from academic and professional bodies. These accolades reflect her dedication to excellence in research, teaching, and leadership.

Selected Publications

Global, regional, and national stillbirths at 20 weeks’ gestation or longer in 204 countries and territories, 1990–2021. The Lancet, 2024; cited by 22 articles.

A fuzzy ontology-based case-based reasoning system for stomach dystemperament in Persian medicine. PLOS ONE, 2024; cited by 5 articles.

Acceptance and use of mobile health technology in post-abortion care. BMC Health Services Research, 2024; cited by 8 articles.

Challenges of using telemedicine for patients with diabetes during the COVID-19 pandemic. Journal of Clinical & Translational Endocrinology, 2024; cited by 10 articles.

Application of telemedicine technology for cardiovascular diseases management during the COVID-19 pandemic. Frontiers in Cardiovascular Medicine, 2024; cited by 6 articles.

Machine Learning Techniques for Predicting Drug-Related Side Effects. Pharmaceuticals, 2024; cited by 3 articles.

Motivating and inhibiting factors influencing the application of mHealth technology in post-abortion care: A review study. BMC Pregnancy and Childbirth, 2024; cited by 4 articles.

Conclusion

Dr. Haleh Ayatollahi’s extensive contributions to medical informatics are a testament to her dedication to improving healthcare delivery and outcomes through innovative technology. Her work in health information systems, telemedicine, and education continues to influence both national and global healthcare policies. As a leader, educator, and researcher, Dr. Ayatollahi remains committed to advancing the field of health informatics and empowering the next generation of healthcare professionals.