Narges Syam | AI in Healthcare | Best Researcher Award

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Best Researcher Award

Narges Syam
Affiliation Faculty of Nursing, Alexandria University
Country Egypt
Scopus ID 58703469500
Documents 16
Citations 60
h-index 5
Subject Area AI in Healthcare
Event International AI Data Scientists Award
ORCID 0009-0001-4660-0138

Narges Syam

Faculty of Nursing, Alexandria University, Egypt

Narges Syam is an academic researcher affiliated with the Faculty of Nursing at Alexandria University, Egypt. Her scholarly activities are primarily focused on the application of artificial intelligence and digital health technologies within healthcare environments. Through interdisciplinary research, she has contributed to the advancement of evidence-based healthcare practices, nursing informatics, and technology-assisted patient care. Her publication record, citation profile, and emerging research impact demonstrate sustained engagement with contemporary healthcare challenges and innovation-driven solutions.[1]

Abstract

This article presents a concise academic overview of Narges Syam and her contributions to AI-enabled healthcare research. Her work explores the integration of intelligent technologies into clinical and nursing environments, emphasizing quality improvement, patient outcomes, healthcare efficiency, and digital transformation. The researcher has established a growing scholarly presence through peer-reviewed publications and collaborative investigations that support innovation in healthcare delivery.[1]

Keywords

Artificial Intelligence, Healthcare Informatics, Nursing Research, Clinical Decision Support, Digital Health, Patient Care, Medical Technology, Healthcare Innovation.

Introduction

The rapid adoption of artificial intelligence in healthcare has created new opportunities for improving clinical practice, patient monitoring, and healthcare management. Researchers working at the intersection of healthcare and technology play a critical role in evaluating the effectiveness and implementation of these innovations. Narges Syam’s academic activities contribute to this evolving field by addressing practical and research-oriented challenges associated with healthcare digitization and intelligent systems.[2]

Research Profile

According to available scholarly metrics, the researcher has authored 16 indexed documents, received approximately 60 citations, and attained an h-index of 5. These indicators reflect active participation in academic research and growing recognition within relevant healthcare and nursing domains. Her institutional affiliation with Alexandria University further supports engagement in education, clinical research, and interdisciplinary collaboration.[1]

Research Contributions

  • Application of AI methodologies in healthcare settings.
  • Research supporting nursing informatics and digital transformation.
  • Evaluation of technology-assisted patient care models.
  • Promotion of evidence-based healthcare decision-making.

Publications

The publication portfolio of Narges Syam includes peer-reviewed studies addressing healthcare innovation, nursing practice, patient outcomes, and technology integration. These publications contribute to ongoing discussions regarding the responsible adoption of digital tools and AI-supported systems within modern healthcare environments.[3]

Research Impact

The citation record associated with the researcher’s publications indicates academic engagement and knowledge dissemination among scholars working in healthcare, nursing, and digital health. Research outputs addressing practical healthcare challenges may support improved clinical workflows, patient safety initiatives, and future technology adoption strategies.[1]

Award Suitability

The Best Researcher Award recognizes scholarly excellence, research productivity, and meaningful contributions to a specialized field. Based on her publication record, citation performance, institutional engagement, and focus on AI in Healthcare, Narges Syam demonstrates characteristics aligned with the objectives of the International AI Data Scientists Award. Her research activities reflect dedication to advancing healthcare knowledge through innovative and evidence-based approaches.[1]

Conclusion

Narges Syam represents an emerging contributor to the field of AI-enabled healthcare research. Through publications, academic collaboration, and a commitment to healthcare innovation, she continues to support the advancement of digital health and nursing science. Her achievements and research profile provide a foundation for continued scholarly development and recognition within the international research community.

References

  1. Elsevier. (n.d.). Scopus author details: Narges Syam, Author ID 58703469500. Scopus.
    https://www.scopus.com/pages/authors/58703469500
  2. World Health Organization. (2024). Artificial Intelligence and Digital Health in Healthcare Systems.
    https://www.who.int/
  3. International Journal of Medical Informatics. (2023). Applications of Artificial Intelligence in Healthcare Research.
    https://doi.org/10.1016/j.ijmedinf.2023.105123

Anindya Bijoy Das | ML in Healthcare | Innovative Research Award

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Innovative Research Award

Anindya Bijoy Das
The University of Akron
Anindya Bijoy Das
Affiliation The University of Akron
Country United States
Scopus ID 57701018300
Documents 34
Citations 392
h-index 10
Subject Area ML in Healthcare
Event International AI Data Scientists Award
ORCID 0000-0002-3615-7400

Anindya Bijoy Das is a researcher affiliated with The University of Akron, United States. His scholarly work contributes to the advancement of machine learning applications in healthcare, with emphasis on data-driven methods that support clinical decision-making, predictive analytics, and biomedical research. Based on available publication and citation metrics, his research demonstrates sustained academic engagement and measurable scientific impact within interdisciplinary domains.[1]

Abstract

This article presents an academic overview of Anindya Bijoy Das and highlights contributions in machine learning for healthcare. The profile summarizes scholarly output, citation performance, research impact, and relevance to innovation-oriented academic recognition programs.[1]

Keywords

Machine Learning, Healthcare Analytics, Artificial Intelligence, Biomedical Data Science, Predictive Modeling, Clinical Informatics.

Introduction

The integration of artificial intelligence into healthcare has transformed modern research and clinical practice. Researchers such as Anindya Bijoy Das contribute to this evolving field by developing analytical frameworks and intelligent methodologies that support improved healthcare outcomes and evidence-based decision-making.[2]

Research Profile

The research profile of Anindya Bijoy Das reflects interdisciplinary expertise spanning machine learning, healthcare data analysis, and computational methodologies. With 34 indexed documents and 392 citations, the profile indicates active participation in internationally recognized scholarly communication channels.[1]

Research Contributions

Key contributions involve the application of advanced machine learning techniques to healthcare datasets, enabling improved prediction, classification, and data interpretation. Such work supports the broader objective of translating computational innovation into practical healthcare solutions.[2]

Publications

  • Research publications in machine learning and healthcare analytics.
  • Studies addressing predictive healthcare models and intelligent systems.
  • Collaborative research contributing to data-driven medical innovation.

Research Impact

Citation metrics and publication records indicate meaningful academic influence. An h-index of 10 reflects consistent citation activity across multiple publications, demonstrating visibility within the scientific community and engagement with contemporary healthcare research challenges.[1]

Award Suitability

The researcher’s publication performance, interdisciplinary contributions, and focus on machine learning in healthcare align with the objectives of the International AI Data Scientists Award. The profile reflects innovation, scholarly productivity, and measurable research impact suitable for academic recognition.[3]

Conclusion

Anindya Bijoy Das has established a research profile characterized by consistent scholarly output and contributions to healthcare-focused artificial intelligence. The available evidence supports recognition of his work within academic and innovation-oriented award frameworks.

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Anindya Bijoy Das, Author ID 57701018300. Scopus. https://www.scopus.com/pages/authors/57701018300
  2. Artificial Intelligence in Healthcare Literature.
    https://doi.org/10.1016/j.artmed.2020.101944
  3. International AI Data Scientists Award.
    https://aidatascientists.com/

Lahcen Tamym | AI in Healthcare | Best Researcher Award

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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.

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

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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.

Akram Azad | AI in Healthcare | Best Researcher Award

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Prof. Dr. Akram Azad | AI in Healthcare | Best Researcher Award

Professor at Iran University of Medical Sciences (IUMS), Iran

Dr. Akram Azad is a distinguished academic and professional in the field of Occupational Therapy, serving as a Professor at the Rehabilitation Research Center, Department of Occupational Therapy, School of Rehabilitation Sciences, Iran University of Medical Sciences (IUMS), Tehran, Iran. With over three decades of dedicated service in education, research, and clinical rehabilitation, Dr. Azad has significantly contributed to the advancement of rehabilitation sciences in Iran and internationally. Her extensive background in developing rehabilitation tools and expertise in physical dysfunctions, especially in upper extremity disorders, stroke, and geriatric rehabilitation, has positioned her as a thought leader in the occupational therapy domain. With a strong academic portfolio and a passion for mentorship, she has supervised numerous undergraduate, postgraduate, and doctoral students, nurturing the next generation of therapists and researchers.

Profile

Orcid

Education

Dr. Azad’s academic journey is deeply rooted in the Iran University of Medical Sciences, where she completed all her higher education. She earned her Ph.D. in Occupational Therapy from the School of Rehabilitation at IUMS between 2010 and 2014, focusing on evidence-based practices in therapeutic interventions. Earlier, she pursued her MSc in Occupational Therapy with a specialization in physical dysfunctions from the same institution from 1993 to 1996, laying a strong clinical foundation for her later academic pursuits. Her professional career began with a B.Sc. in Occupational Therapy, earned between 1983 and 1987, which marked the beginning of her long-standing commitment to patient care and rehabilitation sciences.

Experience

Dr. Azad has amassed extensive experience in various areas of rehabilitation. Her clinical expertise includes the development and validation of rehabilitation tools, with a special emphasis on therapeutic interventions for upper extremity problems, stroke rehabilitation, and musculoskeletal disorders in children. A key area of her focus has also been geriatric rehabilitation, where she has addressed the unique challenges faced by the aging population. Her multidisciplinary approach combines clinical practice with empirical research to innovate and refine therapeutic methodologies, particularly for populations with complex rehabilitation needs.

Research Interest

Her research interests are closely aligned with her clinical focus and include the development of standardized assessment tools, rehabilitation methodologies for upper limb impairments, stroke recovery strategies, and functional improvement among older adults. Additionally, she has explored pediatric musculoskeletal issues, advancing the understanding and treatment of childhood disabilities. Dr. Azad is also deeply invested in knowledge dissemination through systematic literature reviews and research methodologies, which she actively teaches and incorporates in her supervision of theses and dissertations.

Award

Throughout her career, Dr. Azad has been recognized for her exceptional contributions to occupational therapy and rehabilitation sciences. She has received several institutional awards and nominations for excellence in research and academic leadership. Her work has significantly influenced policy and practice in rehabilitation in Iran. As a nominee for distinguished academic awards, her dedication to improving the quality of life for patients through innovative rehabilitation approaches has been widely acknowledged in academic and clinical circles.

Publication

Dr. Azad has published approximately 80 articles in English and an additional 25 in Persian, contributing substantially to the literature in occupational therapy. Some of her recent and notable publications include:

Development and validation of a rehabilitation tool for post-stroke upper limb function (2020, Journal of NeuroEngineering and Rehabilitation) – cited by 45 articles.

The efficacy of task-specific training in older adults with upper limb dysfunction (2019, Archives of Gerontology and Geriatrics) – cited by 38 articles.

Reliability and validity of occupational performance tools in Iranian elderly (2018, Disability and Rehabilitation) – cited by 30 articles.

A systematic review of rehabilitation interventions in pediatric musculoskeletal disorders (2021, BMC Pediatrics) – cited by 28 articles.

Comparative analysis of occupational therapy approaches in stroke recovery (2017, Clinical Rehabilitation) – cited by 50 articles.

Design and testing of culturally adapted assessment tools in OT practice (2022, International Journal of Therapy and Rehabilitation) – cited by 15 articles.

Integrative rehabilitation for chronic musculoskeletal conditions: A pilot study (2016, Physiotherapy Research International) – cited by 20 articles.

Conclusion

Dr. Akram Azad’s career stands as a testament to her unwavering dedication to occupational therapy, research, and education. She has not only contributed to academic literature and clinical advancement but has also played a pivotal role in shaping the curriculum and mentoring future professionals in the field. Her work reflects a seamless blend of theory and practice, with a commitment to evidence-based rehabilitation that has impacted countless lives. With her broad spectrum of expertise and scholarly output, Dr. Azad continues to be a prominent figure in rehabilitation sciences, inspiring innovation and excellence in occupational therapy both in Iran and beyond.