P
Piyanun Wangkulangkul
Researcher at Prince of Songkla University
Publications - 9
Citations - 67
Piyanun Wangkulangkul is an academic researcher from Prince of Songkla University. The author has contributed to research in topics: Medicine & Fibroin. The author has an hindex of 2, co-authored 4 publications receiving 41 citations.
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Journal ArticleDOI
Mimicked cartilage scaffolds of silk fibroin/hyaluronic acid with stem cells for osteoarthritis surgery: Morphological, mechanical, and physical clues.
TL;DR: It could be deduced that SF/HA scaffolds showed significant clues for suitability in cartilage tissue engineering and in surgery for osteoarthritis.
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Constructed silk fibroin scaffolds to mimic adipose tissue as engineered implantation materials in post-subcutaneous tumor removal
TL;DR: In this article, a Silk fibroin scaffolds (SFSs) were fabricated by the salt leaching method and were constructed by soaking in 0.25% and 0.50% (W/V) Silk Fibroin solutions before freeze-drying.
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Chondrogenesis of human umbilical cord-derived mesenchymal stem cells in silk-fibroin/hyaluronic acid scaffolds for cartilage tissue engineering
Jirayut Jaipaew,Piyanun Wangkulangkul,Chitkasem Suwanrath,Jirut Meesane,Supaporn Krivimol,Puttisak Puttawibul +5 more
Journal ArticleDOI
Prediction for Breast Cancer in BI-RADS Category 4 Lesion Categorized by Age and Breast Composition of Women in Songklanagarind Hospital.
Seechad Noonpradej,Piyanun Wangkulangkul,Piyanoot Woodtichartpreecha,Suphawat Laohawiriyakamol +3 more
TL;DR: In this paper, the authors investigated whether patient age and breast density influence the positive predictive value (PPV) of mammographic and ultrasonographic findings categorized as BI-RADS category 4 and subcategories 4a, 4b, and 4c among female patients.
Journal ArticleDOI
AI-Assisted Assessment of Wound Tissue with Automatic Color and Measurement Calibration on Images Taken with a Smartphone
Sawrawit Chairat,Sitthichok Chaichulee,Tulaya Dissaneewate,Piyanun Wangkulangkul,Laliphat Kongpanichakul +4 more
TL;DR: In this paper , the authors proposed an approach for automatic wound assessment that incorporates automatic color and measurement calibration and artificial intelligence algorithms, which enables the comparison of images taken at different times, even if they were taken under different lighting conditions, distances, lenses and camera sensors.