The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia

The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status

The Utility of Decision Tree and Analytics Hierarchy Process in Prioritizing of Social Aid Distribution due to Covid-19 Pandemic in Indonesia

The Indonesian government provided various social assistance programs to local governments during Covid-19. One of the difficulties for the local governments in determining candidates for social aid is ensuring that the number of candidates is in balance with the available quota. Therefore, the local governments must select the most eligible candidates. This study proposes a priority model that can provide recommendations for candidates who meet the criteria for social assistance. The six parameters used in this study were: number of dependents, occupation, income, age, Covid status, and citizen status. The model operates in two stages, namely classification followed by ranking. The classification stage is conducted using a decision tree, while the ranking stage is performed conducted using the Analytical Hierarchy Process (AHP) algorithm. The decision tree separates two classes, namely, eligible and non-eligible. In addition, the classification process is also used to determine the dominant attributes and played a role in the modeling. The proposed model generates a list of the most eligible candidates based on our research. These are sorted by weight from greatest to most eligible using five dominant parameters: number of dependents, income, age, Covid status, and citizen status

Analisis Citra Dental Panoramic Radiograph (DPR) pada Tulang Mandibula untuk Deteksi Osteoporosis Menggunakan Metode GLCM – SVM Multiclass (Gray Level Co- Occurrence Matrix – Support Vector Machine Multiclass)

Salah satu pemeriksaan standar yang ditetapkan untuk deteksi osteoporosis adalah DEXA. Akan tetapi, pemeriksaan tersebut mahal dan hasilnya tidak dapat memberikan informasi tentang mikroarsitektur tulang. Oleh karena itu, pada penelitian ini dilakukan pengenalan pola dari citra DPR yang dianalisis pada tulang ramus mandibula. Tujuannya agar dapat mengklasifikasi tulang normal, osteopenia dan osteoporosis melalui tiga tahapan yaitu pre-processing dari adaptive histogram equalization, ekstraksi fitur dengan GLCM dan klasifikasi dengan SVM Multiclass dari adanya hubungan antara perubahan pola trabekula pada tulang rahang dengan fraktur tulang panggul. Jumlah data citra DPR yang digunakan sebanyak 61 data (24 data tulang normal, 24 data tulang osteopenia, dan 13 data tulang osteoporosis) yang terbagi menjadi dua bagian, yakni 75% sebagai data latih dan 25% sebagai data uji. Berdasarkan analisis citra DPR pada ROI ramus mandibula yang digunakan sebagai dasar computer-aided diagnosis sistem telah dapat digunakan sebagai deteksi osteoporosis. Ekstraksi fitur GLCM berdasarkan empat fitur statistik telah menujukkan sudut orientasi terbaik adalah 〖135〗^0 dan jarak d=1 piksel serta SVM Multiclass terbaik dibangun oleh kernel polynomial berderajat dua. Hasil akurasi data uji yang dihasilkan sebesar 81,25%, sensitivitas sebesar 75%, spesifisitas sebesar 90%, dan precision sebesar 88,89%

Characterising pattern asymmetry in pigmented skin lesions

Abstract. In clinical diagnosis of pigmented skin lesions asymmetric pigmentation is often indicative of melanoma. This paper describes a method and measures for characterizing lesion symmetry. The estimate of mirror symmetry is computed first for a number of axes at different degrees of rotation with respect to the lesion centre. The statistics of these estimates are the used to assess the overall symmetry. The method is applied to three different lesion representations showing the overall pigmentation, the pigmentation pattern, and the pattern of dermal melanin. The best measure is a 100% sensitive and 96% specific indicator of melanoma on a test set of 33 lesions, with a separate training set consisting of 66 lesions

Three dimensional study to quantify the relationship between facial hard and soft tissue movement as a result of orthognathic surgery

Introduction Prediction of soft tissue changes following orthognathic surgery has been frequently attempted in the past decades. It has gradually progressed from the classic “cut and paste” of photographs to the computer assisted 2D surgical prediction planning; and finally, comprehensive 3D surgical planning was introduced to help surgeons and patients to decide on the magnitude and direction of surgical movements as well as the type of surgery to be considered for the correction of facial dysmorphology. A wealth of experience was gained and numerous published literature is available which has augmented the knowledge of facial soft tissue behaviour and helped to improve the ability to closely simulate facial changes following orthognathic surgery. This was particularly noticed following the introduction of the three dimensional imaging into the medical research and clinical applications. Several approaches have been considered to mathematically predict soft tissue changes in three dimensions, following orthognathic surgery. The most common are the Finite element model and Mass tensor Model. These were developed into software packages which are currently used in clinical practice. In general, these methods produce an acceptable level of prediction accuracy of soft tissue changes following orthognathic surgery. Studies, however, have shown a limited prediction accuracy at specific regions of the face, in particular the areas around the lips. Aims The aim of this project is to conduct a comprehensive assessment of hard and soft tissue changes following orthognathic surgery and introduce a new method for prediction of facial soft tissue changes.   Methodology The study was carried out on the pre- and post-operative CBCT images of 100 patients who received their orthognathic surgery treatment at Glasgow dental hospital and school, Glasgow, UK. Three groups of patients were included in the analysis; patients who underwent Le Fort I maxillary advancement surgery; bilateral sagittal split mandibular advancement surgery or bimaxillary advancement surgery. A generic facial mesh was used to standardise the information obtained from individual patient’s facial image and Principal component analysis (PCA) was applied to interpolate the correlations between the skeletal surgical displacement and the resultant soft tissue changes. The identified relationship between hard tissue and soft tissue was then applied on a new set of preoperative 3D facial images and the predicted results were compared to the actual surgical changes measured from their post-operative 3D facial images. A set of validation studies was conducted. To include: • Comparison between voxel based registration and surface registration to analyse changes following orthognathic surgery. The results showed there was no statistically significant difference between the two methods. Voxel based registration, however, showed more reliability as it preserved the link between the soft tissue and skeletal structures of the face during the image registration process. Accordingly, voxel based registration was the method of choice for superimposition of the pre- and post-operative images. The result of this study was published in a refereed journal. • Direct DICOM slice landmarking; a novel technique to quantify the direction and magnitude of skeletal surgical movements. This method represents a new approach to quantify maxillary and mandibular surgical displacement in three dimensions. The technique includes measuring the distance of corresponding landmarks digitized directly on DICOM image slices in relation to three dimensional reference planes. The accuracy of the measurements was assessed against a set of “gold standard” measurements extracted from simulated model surgery. The results confirmed the accuracy of the method within 0.34mm. Therefore, the method was applied in this study. The results of this validation were published in a peer refereed journal. • The use of a generic mesh to assess soft tissue changes using stereophotogrammetry. The generic facial mesh played a major role in the soft tissue dense correspondence analysis. The conformed generic mesh represented the geometrical information of the individual’s facial mesh on which it was conformed (elastically deformed). Therefore, the accuracy of generic mesh conformation is essential to guarantee an accurate replica of the individual facial characteristics. The results showed an acceptable overall mean error of the conformation of generic mesh 1 mm. The results of this study were accepted for publication in peer refereed scientific journal. Skeletal tissue analysis was performed using the validated “Direct DICOM slices landmarking method” while soft tissue analysis was performed using Dense correspondence analysis. The analysis of soft tissue was novel and produced a comprehensive description of facial changes in response to orthognathic surgery. The results were accepted for publication in a refereed scientific Journal. The main soft tissue changes associated with Le Fort I were advancement at the midface region combined with widening of the paranasal, upper lip and nostrils. Minor changes were noticed at the tip of the nose and oral commissures. The main soft tissue changes associated with mandibular advancement surgery were advancement and downward displacement of the chin and lower lip regions, limited widening of the lower lip and slight reversion of the lower lip vermilion combined with minimal backward displacement of the upper lip were recorded. Minimal changes were observed on the oral commissures. The main soft tissue changes associated with bimaxillary advancement surgery were generalized advancement of the middle and lower thirds of the face combined with widening of the paranasal, upper lip and nostrils regions. In Le Fort I cases, the correlation between the changes of the facial soft tissue and the skeletal surgical movements was assessed using PCA. A statistical method known as ’Leave one out cross validation’ was applied on the 30 cases which had Le Fort I osteotomy surgical procedure to effectively utilize the data for the prediction algorithm. The prediction accuracy of soft tissue changes showed a mean error ranging between (0.0006mm±0.582) at the nose region to (-0.0316mm±2.1996) at the various facial regions

Case series of breast fillers and how things may go wrong: radiology point of view

INTRODUCTION: Breast augmentation is a procedure opted by women to overcome sagging breast due to breastfeeding or aging as well as small breast size. Recent years have shown the emergence of a variety of injectable materials on market as breast fillers. These injectable breast fillers have swiftly gained popularity among women, considering the minimal invasiveness of the procedure, nullifying the need for terrifying surgery. Little do they know that the procedure may pose detrimental complications, while visualization of breast parenchyma infiltrated by these fillers is also deemed substandard; posing diagnostic challenges. We present a case series of three patients with prior history of hyaluronic acid and collagen breast injections. REPORT: The first patient is a 37-year-old lady who presented to casualty with worsening shortness of breath, non-productive cough, central chest pain; associated with fever and chills for 2-weeks duration. The second patient is a 34-year-old lady who complained of cough, fever and haemoptysis; associated with shortness of breath for 1-week duration. CT in these cases revealed non thrombotic wedge-shaped peripheral air-space densities. The third patient is a 37‐year‐old female with right breast pain, swelling and redness for 2- weeks duration. Previous collagen breast injection performed 1 year ago had impeded sonographic visualization of the breast parenchyma. MRI breasts showed multiple non- enhancing round and oval shaped lesions exhibiting fat intensity. CONCLUSION: Radiologists should be familiar with the potential risks and hazards as well as limitations of imaging posed by breast fillers such that MRI is required as problem-solving tool

Characterization of alar ligament on 3.0T MRI: a cross-sectional study in IIUM Medical Centre, Kuantan

INTRODUCTION: The main purpose of the study is to compare the normal anatomy of alar ligament on MRI between male and female. The specific objectives are to assess the prevalence of alar ligament visualized on MRI, to describe its characteristics in term of its course, shape and signal homogeneity and to find differences in alar ligament signal intensity between male and female. This study also aims to determine the association between the heights of respondents with alar ligament signal intensity and dimensions. MATERIALS & METHODS: 50 healthy volunteers were studied on 3.0T MR scanner Siemens Magnetom Spectra using 2-mm proton density, T2 and fat-suppression sequences. Alar ligament is depicted in 3 planes and the visualization and variability of the ligament courses, shapes and signal intensity characteristics were determined. The alar ligament dimensions were also measured. RESULTS: Alar ligament was best depicted in coronal plane, followed by sagittal and axial planes. The orientations were laterally ascending in most of the subjects (60%), predominantly oval in shaped (54%) and 67% showed inhomogenous signal. No significant difference of alar ligament signal intensity between male and female respondents. No significant association was found between the heights of the respondents with alar ligament signal intensity and dimensions. CONCLUSION: Employing a 3.0T MR scanner, the alar ligament is best portrayed on coronal plane, followed by sagittal and axial planes. However, tremendous variability of alar ligament as depicted in our data shows that caution needs to be exercised when evaluating alar ligament, especially during circumstances of injury