Abdelbassat KETFI | Health Sciences | Research Excellence Distinction Award

Research Excellence Distinction Award

Abdelbassat KETFI
Faculty of Medicine, University of Health Sciences

Abdelbassat KETFI
Researcher Abdelbassat KETFI
Affiliation Faculty of Medicine, University of Health Sciences
Country Algeria
Subject Area Health Sciences
Event International PopularScientist Awards
ORCID 0000-0002-9994-767X

Abdelbassat KETFI is affiliated with the Faculty of Medicine, University of Health Sciences, Algeria, and is presented for consideration for the Research Excellence Distinction Award within the International PopularScientist Awards. The supplied academic record contains bibliographic information for several journal articles covering biomaterials, tissue expansion, dermatological treatment, laser-based pain management, nanomaterials, and clinical treatment procedures. Because the supplied publication records do not independently establish every bibliographic relationship to the researcher, the profile below distinguishes between information explicitly provided and information that is not available in the supplied material.

Abstract

This academic recognition profile presents Abdelbassat KETFI, Faculty of Medicine, University of Health Sciences, Algeria, in connection with the Research Excellence Distinction Award. The supplied material identifies Health Sciences as the subject area and provides an ORCID identifier associated with the profile. The accompanying bibliographic records describe research articles addressing tissue-engineering materials, dermatological interventions, laser applications, nanocrystalline materials, and clinical treatment procedures. Several records include persistent digital object identifiers (DOIs), allowing direct verification of their publication metadata. [1] [2] [3]

Keywords

Abdelbassat KETFI, Research Excellence Distinction Award, Health Sciences, medical research, clinical research, biomedical materials, tissue engineering, dermatology, laser medicine, nanomaterials, scientific publications, International PopularScientist Awards.

Introduction

Academic research in the health sciences encompasses clinical investigation, biomedical technologies, therapeutic procedures, materials science, and interdisciplinary approaches to improving healthcare. Recognition of research excellence generally considers the quality and relevance of scholarly contributions together with evidence of research dissemination and impact. The supplied records associated with this profile span multiple areas of biomedical and clinical research, indicating a broad thematic environment rather than a single narrowly defined research topic. [1] [2]

Research Profile

The supplied information places the profile within Health Sciences and identifies the Faculty of Medicine, University of Health Sciences, Algeria, as the institutional affiliation. The ORCID identifier provided for the profile is 0000-0002-9994-767X. An ORCID identifier is a persistent researcher identifier intended to distinguish researchers and connect their scholarly contributions across research systems. Quantitative indicators such as total documents, citations, and h-index were not supplied in the source material and therefore are not assigned values in this article. This approach avoids introducing unsupported bibliometric figures into the academic recognition profile.

Research Contributions

The supplied publication records represent several areas relevant to biomedical and health-science research. The article on methacrylate-based hydrogel tissue expanders concerns polymeric materials with potential relevance to stomatology and tissue expansion. Its bibliographic record identifies the Journal of Materials Science: Materials in Medicine and provides DOI 10.1007/s10856-016-5818-y. [2]

Publications

The following publications are reproduced from the supplied bibliographic information. The source material identifies the records as Scopus-derived information and attributes the displayed source to Roman Šmucler via Scopus–Elsevier. The supplied records should therefore be treated as bibliographic evidence provided for this recognition profile rather than as an independently verified complete publication list for Abdelbassat KETFI.

    1. Hydrogel tissue expanders for stomatology. Part I. Methacrylate-based polymers. Journal of Materials Science: Materials in Medicine, 2017. [2]
    2. Infantile hemangiomas. Current treatment procedures | Infantilní hemangiomas. Současné tělečné protředky. Czech-Slovak Pediatrics, 2017. Scopus EID: 2-s2.0-85027991512. The supplied contributor list includes Malis, J.; Stara, V.; Blahova, K.; Bučkova, H.; Faberova, R.; Šterba, J.; Klovrzova, S.; Kynčl, M.; Černy, M.; Hrdlička, R.; et al. [5]
    3. Direct and indirect treatment of pain with lasers – Update 2016. Disease, 2016. Scopus EID: 2-s2.0-84992323214. Contributors listed in the supplied record are Šmucler, R. and Jenčová, J. [6]
    4. Large scale preparation of up-converting YF3:YbEr nanocrystals with various sizes by solvothermal syntheses using ionic liquid bmimCl. Journal of Fluorine Chemistry, 2016.

Research Impact

Research impact can be considered through the relevance of scholarly outputs, disciplinary reach, reproducibility of bibliographic evidence, and subsequent scholarly use. The supplied records demonstrate publication activity across clinical medicine, biomaterials, laser-based treatment, dermatology, pediatric treatment, and nanomaterials. Several publications have DOI identifiers, providing persistent mechanisms for locating and verifying the corresponding journal records. [2] [3] [4]

Award Suitability

The Research Excellence Distinction Award profile is supported by the supplied evidence of an academic affiliation in Health Sciences, an identifiable ORCID record, and a set of scholarly publications spanning multiple biomedical and clinical themes. The presence of peer-reviewed journal records and DOI-linked publications provides a documented basis for considering scholarly output as part of an award assessment. [2] [3] [4]

  • The supplied profile identifies a medical and health-science institutional affiliation.
  • The supplied material contains multiple journal publication records with identifiable bibliographic metadata.
  • Several records include DOI identifiers that support persistent publication verification.
  • The supplied topics encompass clinical treatment, dermatology, laser applications, biomaterials, tissue expansion, and nanomaterials.

On the evidence provided, the profile has a reasonable documentary basis for academic recognition consideration, subject to the award committee’s independent verification of authorship, publication attribution, research contribution, and bibliometric indicators.

Conclusion

Abdelbassat KETFI is presented as a Health Sciences researcher affiliated with the Faculty of Medicine, University of Health Sciences, Algeria. The supplied academic material documents a collection of journal publications addressing clinically and technologically diverse areas of biomedical research. The publication records containing DOI identifiers offer verifiable bibliographic pathways, while the absence of supplied citation and h-index data limits quantitative assessment. [2] [3] [4]

References

  1. Hrib, J.; Sirc, J.; Lesny, P.; Hobzova, R.; Duskova-Smrckova, M.; Michalek, J.; Smucler, R. (2017). Hydrogel tissue expanders for stomatology. Part I. Methacrylate-based polymers. Journal of Materials Science: Materials in Medicine.
    10.1007/s10856-016-5818-y.
  2. Bartůněk, V.; Rak, J.; Pelánková, B.; Junková, J.; Mezlíková, M.; Král, V.; Kuchař, M.; Engstová, H.; Ježek, P.; Šmucler, R. (2016). Large scale preparation of up-converting YF3:YbEr nanocrystals with various sizes by solvothermal syntheses using ionic liquid bmimCl. Journal of Fluorine Chemistry.
    10.1016/j.jfluchem.2016.05.015.
  3. Lippert, J.; Šmucler, R.; Vlk, M. (2013). Fractional carbon dioxide laser improves nodular basal cell carcinoma treatment with photodynamic therapy with methyl 5-aminolevulinate. Dermatologic Surgery.
    10.1111/dsu.12242.
  4. International PopularScientist Awards. (n.d.). International PopularScientist Awards.
    https://popularscientist.com

Yashbir Singh | Medicine and Health Sciences | Best Researcher Award

Dr. Yashbir Singh | Medicine and Health Sciences | Best Researcher Award

Assistant Prof Mayo clinic, Rochester United States

Yashbir Singh is an Assistant Professor in Radiology with extensive experience in biomedical engineering and computational deep learning methods for medical imaging analysis. His research focuses on AI-driven approaches for early cancer detection, particularly in liver cancer, and has made substantial contributions to the integration of topological data analysis with deep learning. With a background in pharmaceutics, bioinformatics, and biomedical engineering, Yashbir brings a unique interdisciplinary perspective to medical imaging. His work is instrumental in advancing AI methodologies for clinical applications and patient-specific risk assessments in liver diseases. 🌐💡

Profile

Google Scholar

Orcid

Education

Yashbir Singh completed his Bachelor’s in Pharmaceutics and Drug Design from M.J.P. Rohilkhand University, Bareilly, India, followed by a Master’s in Bioinformatics from the Indian Institute of Information Technology, Allahabad. He then earned his PhD in Biomedical Engineering from Chung Yuan Christian University, Taiwan. After completing his postdoctoral work in AI Radiology at Mayo Clinic, he continued his research at the same institution as a Postdoctoral Fellow in AI Radiology. 🎓🔬

Experience

Yashbir Singh has held various prestigious positions, including visiting faculty at Harvard Medical School and a medical scientist at WVU Medicine, West Virginia. He has also been a junior research fellow at IIT Mandi, India, and a teaching assistant at IIIT Allahabad, India, and Chung Yuan Christian University, Taiwan. His diverse experiences across academia and clinical environments have significantly shaped his research in medical imaging and AI. 🌍👨‍⚕️

Research Interest

Dr. Singh’s research interests lie in the intersection of artificial intelligence, medical imaging, and oncology. He has pioneered the use of algebraic topology-based machine learning for predicting clinical outcomes, specifically in liver diseases like primary sclerosing cholangitis. His current work focuses on developing deep learning frameworks for early cancer detection, integrating machine learning with topological data analysis, and improving patient-specific diagnostic tools. 🔍💻🧬

Award

Yashbir Singh has received several prestigious awards, including the 2024 Research Award from RSNA and Best Paper Presenter at IEEE CCWC 2022. His work has been recognized for its innovation in AI-driven medical imaging and clinical applications. In addition, he has received Best Reviewer Awards from ICSPIS and the 2020 Medical Imaging Best Paper Award from SPIE. These accolades highlight his leadership in the field of AI-based medical research. 🏆📜

Publication Top Notes:

Yashbir Singh has contributed to over 20 high-impact publications. Some notable works include:

Decoding ChatGPT: a taxonomy of existing research, current challenges, and possible future directions

Mitigating bias in radiology machine learning: 1. Data handling

Mitigating bias in radiology machine learning: 2. Model development

The future of gpt: A taxonomy of existing chatgpt research, current challenges, and possible future directions

A low-cost texture-based pipeline for predicting myocardial tissue remodeling and fibrosis using cardiac ultrasound

Identification of Novel Abiotic Stress Proteins in Triticum aestivum Through Functional Annotation of Hypothetical Proteins

Algebraic topology-based machine learning using MRI predicts outcomes in primary sclerosing cholangitis

His work is highly cited, demonstrating a significant impact on the field of AI and medical imaging, especially in the context of liver disease. 📖📈