MyMedR

Samsudin R

Malays J Med Sci, 2001 Jul;8(2):7-8.

Fulltext Stem cell and tissue engineering - the challenge of imitating nature

Samsudin R

Malays J Med Sci, 2003 Jul;10(2):1-3.

Fulltext Crude oil price forecasting based on hybridizing wavelet multiple linear regression model, particle swarm optimization techniques, and principal component analysis

Shabri A, Samsudin R

ScientificWorldJournal, 2014;2014:854520.

PMID: 24895666 DOI: 10.1155/2014/854520

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into several subseries with different scale. Then, the principal component analysis (PCA) is used in processing subseries data in MLR for crude oil price forecasting. The particle swarm optimization (PSO) is used to adopt the optimal parameters of the MLR model. To assess the effectiveness of this model, daily crude oil market, West Texas Intermediate (WTI), has been used as the case study. Time series prediction capability performance of the WMLR model is compared with the MLR, ARIMA, and GARCH models using various statistics measures. The experimental results show that the proposed model outperforms the individual models in forecasting of the crude oil prices series.

Effects of Twin-Block Appliance Therapy on Urinary Leukotriene E4 and Serum C-Reactive Protein Levels in Obstructive Sleep Apnea Children with Class II Malocclusion and Mandibular Retrognathia: A Prospective Longitudinal Study

Zreaqat M, Hassan R, Samsudin R, Alforaidi S

Indian J Pediatr, 2023 Jul;90(7):729.

PMID: 37261707 DOI: 10.1007/s12098-023-04601-0

Dental arch shape and size in Malay schoolchildren with Class II malocclusion

Banabilh SM, Rajion ZA, Samsudin R, Singh GD

Aust Orthod J, 2006 Nov;22(2):99-103.

PMID: 17203572

To quantify and localise differences in Class I and Class II dental arches in Malay schoolchildren.

In vivo optical coherence tomography-guided photodynamic therapy for skin pre-cancer and cancer

Hamdoon Z, Jerjes W, Rashed D, Kawas S, Sattar AA, Samsudin R, et al.

Photodiagnosis Photodyn Ther, 2021 Sep 05;36:102520.

PMID: 34496299 DOI: 10.1016/j.pdpdt.2021.102520

BACKGROUND: The primary aim of this prospective study is to demonstrate the technical feasibility of OCT to map real tumor margins and to monitor skin changes that occurred post- PDT. Moreover, to optimize PDT efficacy based on the relationship between measured OCT features and treatment outcome.

MATERIAL AND METHODS: A series of 12 patients with overall 18 facial skin lesions were investigated by OCT before surface illumination by PDT to determine tumor free margins. Monitoring of the healing process was undertaken at 3, 6 and 12 months post-PDT. Parameters measured by the in vivo OCT during healing phase were the organization of skin layer and the degree skin fibroses for the active center and peripheral transit zone of the treated lesion. Clinical and aesthetics assessment was carried out at 12-month post-PDT.

RESULTS: Distinct microstructural differences between normal skin, pre-cancer, cancer, and the transition zone between the two tissues were observed on OCT images. In the subsequent healing phase, OCT demonstrate marked delineation and organization of skin layer at late stage of healing. Early features showing bizarre non-homogenous disorganized layering (scab) but afterwards, OCT was able to differentiate between different histological layers. One lesion demonstrated clinical healing by fibrosis (scar) without sign of recurrence. Another lesion demonstrated skin erythema. Only one lesion did not response to treatment despite margins clearance. The CR rate was 95% at the end of the study. The cosmetic effect was "excellent" in 89% of the patients.

CONCLUSIONS: This feasibility study lays the groundwork for using OCT as a real-time, noninvasive monitoring device for PDT in patients with skin cancer.

Fulltext Graph-based extractive text summarization method for Hausa text

Bichi AA, Samsudin R, Hassan R, Hasan LRA, Ado Rogo A

PLoS One, 2023;18(5):e0285376.

PMID: 37159449 DOI: 10.1371/journal.pone.0285376

Automatic text summarization is one of the most promising solutions to the ever-growing challenges of textual data as it produces a shorter version of the original document with fewer bytes, but the same information as the original document. Despite the advancements in automatic text summarization research, research involving the development of automatic text summarization methods for documents written in Hausa, a Chadic language widely spoken in West Africa by approximately 150,000,000 people as either their first or second language, is still in early stages of development. This study proposes a novel graph-based extractive single-document summarization method for Hausa text by modifying the existing PageRank algorithm using the normalized common bigrams count between adjacent sentences as the initial vertex score. The proposed method is evaluated using a primarily collected Hausa summarization evaluation dataset comprising of 113 Hausa news articles on ROUGE evaluation toolkits. The proposed approach outperformed the standard methods using the same datasets. It outperformed the TextRank method by 2.1%, LexRank by 12.3%, centroid-based method by 19.5%, and BM25 method by 17.4%.

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