John Bush Idoko | Cardiology | Research Excellence Award

Published on by Health Scientists

Health Scientists Awards

John Bush Idoko
Near East University, Cyprus

John Bush Idoko
Affiliation Near East University
Country Cyprus
Scopus ID 57200209705
Documents 55
Citations 481
h-index 10
Subject Area Cardiology
Event Health Scientists Awards

John Bush Idoko is a researcher affiliated with Near East University in Cyprus whose scholarly activities span medical and health sciences with notable engagement in cardiology-related research and interdisciplinary biomedical investigations. His publication portfolio demonstrates contributions to machine learning applications in health sciences, neurological signal processing, and clinical analytics. The researcher has established measurable academic visibility through indexed publications, citations, and collaborative scientific output documented in major international databases.[1]

Abstract

This academic article presents a structured overview of the scholarly profile and research contributions of John Bush Idoko of Near East University, Cyprus. The page evaluates the researcher’s publication activities, citation indicators, interdisciplinary collaborations, and contributions to health science and biomedical analytics. Particular attention is given to publications associated with neurological diagnostics, deep learning applications in medicine, and computational approaches to health-related signal analysis. The article further discusses the relevance of the researcher’s scientific portfolio within the context of the Health Scientists Awards and highlights the consistency of publication productivity and research visibility within indexed academic databases.[2]

Keywords

Cardiology, Biomedical Engineering, Machine Learning, EEG Analysis, Deep Learning, Health Sciences, Clinical Analytics, Medical Informatics, Computational Medicine, Scientific Impact

Introduction

Contemporary health sciences increasingly integrate computational technologies, biomedical analytics, and artificial intelligence methodologies to improve diagnostic accuracy and healthcare efficiency. Researchers working at the intersection of medical sciences and intelligent systems contribute significantly to the modernization of healthcare research infrastructure. John Bush Idoko’s scholarly activities align with these evolving academic trends through publications associated with neural network methodologies, biomedical signal processing, and clinical interpretation systems.[3]

The international research environment has increasingly recognized interdisciplinary scientific collaborations that combine computational modeling with clinical sciences. Academic researchers contributing to this area frequently engage in studies involving diagnostic systems, machine learning algorithms, and predictive analytics for medical applications. Publications attributed to John Bush Idoko indicate participation in these developing scientific domains with measurable scholarly visibility across indexed academic platforms.[1]

Research Profile

John Bush Idoko is affiliated with Near East University in Cyprus and has developed an academic profile characterized by interdisciplinary research contributions involving medical sciences, signal processing, and intelligent computational systems. According to indexed bibliographic records, the researcher has produced 55 documents with 481 citations and an h-index of 10, reflecting moderate and consistent scholarly engagement within internationally indexed literature.[1]

The researcher’s publication trajectory demonstrates collaborative engagement with scientists from multiple institutions and disciplinary backgrounds. Several studies involve neural networks, convolutional deep learning systems, biomedical image interpretation, and clinical decision-support methodologies. Such interdisciplinary research profiles are increasingly important in modern health science ecosystems where computational methods assist in healthcare diagnostics and patient management strategies.[4]

Research Contributions

The research contributions associated with John Bush Idoko include investigations into biomedical signal analysis, epileptic EEG identification systems, and deep learning approaches for medical pattern recognition. These contributions reflect ongoing scientific interest in leveraging computational intelligence to improve diagnostic precision and clinical interpretation methodologies.[2]

One area of scholarly contribution involves convolutional neural network applications for EEG signal classification. Research in this area supports the development of automated neurological analysis systems capable of assisting healthcare practitioners in diagnostic processes. Such studies contribute to broader efforts within biomedical engineering and clinical informatics aimed at improving healthcare efficiency and analytical reliability.[3]

Additional contributions include studies related to sign language translation using deep neural networks and interdisciplinary artificial intelligence frameworks applied to health communication technologies. These works collectively illustrate the researcher’s participation in computational approaches that support healthcare accessibility, diagnostic automation, and biomedical data interpretation.[4]

Publications

  • Abiyev, R., Arslan, M., Idoko, J. B., Sekeroglu, B., & Ilhan, A. “Identification of epileptic EEG signals using convolutional neural networks.” Applied Sciences, 2020.
    https://doi.org/10.3390/app10124089
  • Abiyev, R. H., Arslan, M., & Idoko, J. B. “Sign language translation using deep convolutional neural networks.” KSII Transactions on Internet and Information Systems, 2020.
    https://doi.org/10.3837/tiis.2020.02.018
  • Research publications involving biomedical data analytics, machine learning applications, and intelligent healthcare systems indexed within Scopus and Google Scholar databases.[1]

Research Impact

The measurable research impact associated with John Bush Idoko is reflected through citation activity, interdisciplinary collaborations, and publication visibility across recognized indexing platforms. Citation metrics indicate that the researcher’s publications have contributed to ongoing academic discussions within biomedical engineering, computational medicine, and health informatics.[1]

The integration of deep learning methodologies into biomedical diagnostics represents an active area of international scientific development. Contributions related to EEG analysis and medical classification systems have relevance to modern healthcare technologies and emerging intelligent diagnostic infrastructures. Such research may contribute to future clinical applications, data interpretation systems, and computational healthcare solutions.[2]

Award Suitability

The scholarly profile of John Bush Idoko demonstrates characteristics commonly associated with academic recognition programs in health sciences, including interdisciplinary collaboration, indexed publication output, citation visibility, and engagement with emerging biomedical technologies. The integration of artificial intelligence methodologies into health science investigations aligns with evolving priorities within international healthcare research communities.[4]

The Health Scientists Awards program recognizes researchers whose academic contributions support innovation, scientific advancement, and interdisciplinary development in healthcare-related fields. Based on available bibliographic indicators and publication themes, the researcher’s profile demonstrates relevance to these academic evaluation criteria.[5]

Conclusion

John Bush Idoko’s academic profile reflects ongoing contributions to interdisciplinary health science research involving machine learning, biomedical analytics, and intelligent diagnostic systems. Indexed publications, citation metrics, and collaborative research activities collectively indicate sustained engagement with contemporary computational healthcare methodologies. The researcher’s portfolio demonstrates relevance within emerging scientific areas that integrate biomedical sciences and artificial intelligence technologies. Such contributions support broader international efforts aimed at improving healthcare diagnostics, analytical efficiency, and digital health innovation.[1]

References

  1. Elsevier. (n.d.). Scopus author details: John Bush Idoko, Author ID 57200209705. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57200209705
  2. Abiyev, R., Arslan, M., Idoko, J. B., Sekeroglu, B., & Ilhan, A. (2020). Identification of epileptic EEG signals using convolutional neural networks. Applied Sciences.
    https://doi.org/10.3390/app10124089
  3. Google Scholar. (n.d.). John Bush Idoko citation profile and indexed publications.
    https://scholar.google.com/citations?user=eVqc6HkAAAAJ&hl=en&oi=ao
  4. Sekeroglu, B., Abiyev, R., Ilhan, A., Arslan, M., & Idoko, J. B. “Systematic literature review on machine learning and student performance prediction: Critical gaps and possible remedies.” Applied Sciences, 11(22), 10907. https://doi.org/10.3390/app112210907
  5. Health Scientists Awards. (n.d.). Official award information and evaluation categories.
    https://healthscientists.org/

Suwimol Prusmetikul | Health Education | Best Researcher Award

Published on by Health Scientists

Dr. Suwimol Prusmetikul | Health Education | Best Researcher Award

Instructor | Mahidol University | Thailand

Dr. Suwimol Prusmetikul is an accomplished orthopedic surgeon and instructor at Ramathibodi Hospital, Mahidol University, whose work exemplifies the integration of advanced clinical expertise with innovative approaches to medical education. Trained in foot and ankle surgery and holding a Master’s degree in Surgical Education from Imperial College London, Dr. Prusmetikul has contributed significantly to both clinical research and surgical pedagogy. Her scholarly endeavors encompass orthopedic research focusing on improving surgical techniques, imaging precision, and postoperative outcomes, as well as exploring educational frameworks that enhance the learning experience of surgical trainees. Through peer-reviewed publications in high-impact international journals, her research has illuminated the interconnection between evidence-based orthopedic practices and transformative medical training methodologies. Her ongoing investigations delve into biomechanical assessments using advanced imaging technologies, refining diagnostic and therapeutic precision in musculoskeletal care. Dr. Prusmetikul’s academic work further extends to cross-disciplinary collaborations that examine surgical education through innovative lenses, fostering competency-based learning and reflective practice among medical professionals. Her studies, such as those linking weightbearing CT scan analysis with clinical outcomes in hallux valgus surgery and the exploration of skill development in medical learning environments, demonstrate her commitment to advancing both patient care and educational excellence. Beyond clinical research, she emphasizes mentorship, ethical medical training, and the translation of scientific findings into real-world improvements in orthopedic health services. Dr. Prusmetikul’s academic engagement and research impact reflect a deep dedication to evidence-driven innovation, global collaboration, and continuous improvement in surgical education and orthopedic care—values that underscore her distinction as a forward-thinking clinician, educator, and researcher whose contributions resonate across the international medical community. She has 22 citations from 5 documents with an h-index of 3.

Profiles: Scopus | ORCID

Featured Publications

1. Prusmetikul, S., & Tawonsawatruk, T. (2023, August). The surgical treatment of bilateral accessory extensor carpi ulnaris: Case report and literature review. Journal of Wrist Surgery.

2. Prusmetikul, S., Laohajaroensombat, S., Orapin, J., Pittayasoponkij, P., Buranawongtrakoon, S., & Tawonsawatruk, T. (2022, September). Reliability improvement in hallux valgus measurement using weight-bearing CT scan. Journal of Orthopaedic Surgery.

3. Tawonsawatruk, T., Prusmetikul, S., Kanchanathepsak, T., Patathong, T., Klaewkasikum, K., Woratanarat, P., Panuwannakorn, M., & Vongpipatana, S. (2022, April). Comparison of outcome between operative treatment and constraint-induced movement therapy for forearm and wrist deformities in cerebral palsy: A randomized controlled trial. Hand Surgery and Rehabilitation.

4. Prusmetikul, S., Vongpipatana, S., Woratanarat, P., Tuntiyatorn, P., & Tawonsawatruk, T. (2018). Correlation of range of motion and functional performance of upper extremities in children with cerebral palsy. Journal of the Medical Association of Thailand.

Sipping Kemegne Marius Tresor | Pharmacology | Best Researcher Award

Published on by Health Scientists

Dr. Sipping Kemegne Marius Tresor | Pharmacology | Best Researcher Award

Research scholar | Slovak Academy of Sciences | Slovakia

Dr. Sipping Kemegne Marius Tresor is a biochemist and postdoctoral research fellow whose expertise spans immunopharmacology, cancer biology, inflammatory diseases, and phytomedicine, with a focus on natural bioactive compounds and their translational therapeutic applications. Trained at leading institutions across Africa and Europe, he has developed a strong multidisciplinary foundation integrating molecular biology, pharmacology, biotechnology, and clinical research principles to advance innovation in precision therapeutics. His research has pioneered the exploration and characterization of polysaccharide-rich bioactive fractions from medicinal fungi, particularly Ganoderma species, elucidating their antioxidant, anti-inflammatory, and anti-metastatic potentials and offering promising chemopreventive and therapeutic leads for cancer and immune-mediated disorders. His scientific contributions include peer-reviewed publications in internationally indexed journals and authorship of a scholarly book, demonstrating sustained commitment to advancing biomedical knowledge and global research excellence. Dr. Sipping’s work has been strengthened through impactful collaborations across Africa, Europe, and Asia with prominent scientists and international research groups, fostering interdisciplinary partnerships and capacity building in natural product research and immunotherapeutics. His ongoing investigations focus on isolating novel polysaccharides and developing nanotechnology-enabled drug delivery systems to enhance therapeutic efficacy against chronic inflammatory conditions, such as rheumatoid arthritis, bridging traditional bioresources with cutting-edge biomedical strategies. Beyond laboratory research, he is a certified clinical research professional committed to strengthening translational pathways from preclinical discovery to potential clinical application. His membership in distinguished scientific bodies reflects his dedication to contributing to the global research community. Driven by the vision to harness bioresources and advanced biotechnology for improved public health, Dr. Sipping aims to deliver innovative, accessible, and safe therapeutic options addressing cancer, autoimmune, and infectious diseases, thereby contributing to scientific progress and societal well-being. He has 81 citations from 9 documents with an h-index of 5.

Profiles:  Scopus | ORCID

Featured Publications

1. Sipping, M., Thakur, D., Singh, B., Njamen, D., & Mukherjee, S. (2025). Polysaccharide extract of Ganoderma resinaceum restricts breast cancer progression in vitro by intervening in epithelial–mesenchymal transition and cancer stemness. Revista Brasileira de Farmacognosia.

2. Sipping, M., Sathish Kumar, T., & Kamdem, N. (2025). Scientific investigation on antibacterial, antioxidant, cytotoxic effects and TLC bioautography of Terminalia schimperiania stem bark extracts. Journal of Complementary and Integrative Medicine.

3. Kamga Silihe, K., Defo Mbou, W., Ngo Pambe, J. C., Kenmogne, L. V., Fotso Maptouom, L., Kemegne Sipping, M. T., Zingue, S., & Njamen, D. (2023). Comparative anticancer effects of Annona muricata Linn (Annonaceae) leaves and fruits on DMBA-induced breast cancer in female rats. BMC Complementary Medicine and Therapies.

4. Nana Tchoupang, E., Yadji, V., Wangbara, J. B., Kemegne Sipping, M. T., Zingue, S., Njamen, D., & Mutalik, S. (2022). In vitro and in vivo antiproliferative actions of Solanum gilo Raddi (Solanaceae) fruit extract on breast tissues. Advances in Pharmacological and Pharmaceutical Sciences.

5. Kamga Silihe, K., Zingue, S., Kemegne Sipping, M. T., Busuioc Cazanevscaia, A., Dediu Botezatu, A. V., Njamen, D., & Dinica, R. M. (2022). The antioxidant potential of Ficus umbellata Vahl (Moraceae) that accelerates in vitro and in vivo anti-inflammatory protective effects. Applied Sciences.