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  1. Sharifah M, Nurhazla H, Suraya A, Tan S
    Biomed Imaging Interv J, 2011 Oct;7(4):e24.
    PMID: 22279501 MyJurnal DOI: 10.2349/biij.7.4.24
    This paper describes an extremely rare case of a huge aneurysmal bone cyst (ABC) in the pelvis, occurring in the patient's 5(th) decade of life. The patient presented with a history of painless huge pelvic mass for 10 years. Plain radiograph and computed tomography showed huge expansile lytic lesion arising from the right iliac bone. A biopsy was performed and histology confirmed diagnosis of aneurysmal bone cyst. Unfortunately, the patient succumbed to profuse bleeding from the tumour.
  2. Rahman RA, Hussaini HM, Rahman NA, Rahman SR, Nor GM, Ai Idrus SM, et al.
    Eur J Trauma Emerg Surg, 2007 Feb;33(1):90-5.
    PMID: 26815981 DOI: 10.1007/s00068-007-5154-5
    The objective of this study was to determine the demographic data as well as other relevant data pertaining to the management of patients with maxillofacial injury in a Malaysian government regional hospital.
  3. Sharifah MI, Zamzami NA, Rafeah TN
    Med J Malaysia, 2011 Aug;66(3):270-2.
    PMID: 22111459 MyJurnal
    Burkitt's lymphoma is a form of Non-Hodgkin's B-cell lymphoma. We report a case of Burkitt's lymphoma mimicking peritoneal carcinomatosis. We will discuss the imaging and clinical findings that differentiate between peritoneal carcinomatosis and Burkitt's lymphoma. A 26-year-old man presented with nonspecific abdominal pain, vomiting and diarrhea associated with significant amount of loss of weight. Computed tomography images showed extensive peritoneal and mesenteric mass associated generalized lymphadenopathy. Core biopsy of the mass confirmed Burkitt's lymphoma. CT scan features are helpful indicator to differentiate Burkitt's lymphoma and peritoneal carcinomatosis. Focal or diffuse nodular thickening of the bowel wall with extensive lymphadenopathy are likely to be lymphomatosis over carcinomatosis. However, final and confirmatory diagnosis is histopathology examination.
  4. Sharifah MI, Noryati M, Che Zubaidah CD, Zakaria Z
    Med J Malaysia, 2010 Jun;65(2):150-1.
    PMID: 23756803 MyJurnal
    Foetus-in-fetu is a rare condition in which a calcified mass is in the abdomen of its host, a newborn or an infant. We report a case of a newborn in whom abdominal radiograph and ultrasonography revealed a mass in which the contents favour a foetus-in-fetu. Diagnosis was confirmed by macroscopic examination that showed a soft tissue mass resembling a foetus, attached to the membranous sac. It was covered entirely with intact skin. There were two malformed lower limbs with a rudimentary digit and one malformed upper limb.
  5. Henry Basil J, Lim WH, Syed Ahmad SM, Menon Premakumar C, Mohd Tahir NA, Mhd Ali A, et al.
    Digit Health, 2024;10:20552076241286434.
    PMID: 39430694 DOI: 10.1177/20552076241286434
    OBJECTIVE: Neonates' physiological immaturity and complex dosing requirements heighten their susceptibility to medication administration errors (MAEs), with the potential for severe harm and substantial economic impact on healthcare systems. Developing an effective risk prediction model for MAEs is crucial to reduce and prevent harm.

    METHODS: This national-level, multicentre, prospective direct observational study was conducted in neonatal intensive care units (NICUs) of five public hospitals in Malaysia. Randomly selected nurses were directly observed during medication preparation and administration. Each observation was independently assessed for errors. Ten machine learning (ML) algorithms were applied with features derived from systematic reviews, incident reports, and expert consensus. Model performance, prioritising F1-score for MAEs, was evaluated using various measures. Feature importance was determined using the permutation-feature importance for robust comparison across ML algorithms.

    RESULTS: A total of 1093 doses were administered to 170 neonates, with mean age and birth weight of 33.43 (SD ± 5.13) weeks and 1.94 (SD ± 0.95) kg, respectively. F1-scores for the ten models ranged from 76.15% to 83.28%. Adaptive boosting (AdaBoost) emerged as the best-performing model (F1-score: 83.28%, accuracy: 77.63%, area under the receiver operating characteristic: 82.95%, precision: 84.72%, sensitivity: 81.88% and negative predictive value: 64.00%). The most influential features in AdaBoost were the intravenous route of administration, working hours, and nursing experience.

    CONCLUSIONS: This study developed and validated an ML-based model to predict the presence of MAEs among neonates in NICUs. AdaBoost was identified as the best-performing algorithm. Utilising the model's predictions, healthcare providers can potentially reduce MAE occurrence through timely interventions.

  6. Sharifah MI, Lee CL, Suraya A, Johan A, Syed AF, Tan SP
    Knee Surg Sports Traumatol Arthrosc, 2015 Mar;23(3):826-30.
    PMID: 24240983 DOI: 10.1007/s00167-013-2766-7
    PURPOSE: This study was conducted to evaluate the accuracy of magnetic resonance imaging (MRI) in diagnosing meniscal tears in patients with anterior cruciate ligament (ACL) tears and to determine the frequency of missed meniscal tears on MRI.

    METHODS: This prospective comparative study was conducted from 2009 to 2012. Patients with ACL injuries who underwent knee arthroscopy and MRI were included in the study. Two radiologists who were blinded to the clinical history and arthroscopic findings reviewed the pre-arthroscopic MR images. The presence and type of meniscal tears on MRI and arthroscopy were recorded. Arthroscopic findings were used as the reference standard. The accuracy, sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) of MRI in the evaluation of meniscal tears were calculated.

    RESULTS: A total of 65 patients (66 knees) were included. The sensitivity, specificity, accuracy, PPV, and NPV for the MRI diagnosis of lateral meniscal tears in our patients were 83, 97, 92, 96, and 90 %, respectively, whereas those for medial meniscus tears were 82, 92, 88, 82, and 88 %, respectively. There were five false-negative diagnoses of medial meniscus tears and four false-negative diagnoses of lateral meniscus tears. The majority of missed meniscus tears on MRI affected the peripheral posterior horns.

    CONCLUSION: The sensitivity for diagnosing a meniscal tear was significantly higher when the tear involved more than one-third of the meniscus or the anterior horn. The sensitivity was significantly lower for tears located in the posterior horn and for vertically oriented tears. Therefore, special attention should be given to the peripheral posterior horns of the meniscus, which are common sites of injury that could be easily missed on MRI. The high NPVs obtained in this study suggest that MRI is a valuable tool prior to arthroscopy.

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