Oral cancer is a major global health issue accounting for 177,384 deaths in 2018 and it is most prevalent in low-and middle-income countries. Enabling automation in the identification of potentially malignant and malignant lesions in the oral cavity would potentially lead to low-cost and early diagnosis of the disease. Building a large library of well-annotated oral lesions is key. As part of the MeMoSA ® (Mobile Mouth Screening Anywhere) project, images are currently in the process of being gathered from clinical experts from across the world, who have been provided with an annotation tool to produce rich labels. A novel strategy to combine bounding box annotations from multiple clinicians is provided in this paper. Further to this, deep neural networks were used to build automated systems, in which complex patterns were derived for tackling this difficult task. Using the initial data gathered in this study, two deep learning based computer vision approaches were assessed for the automated detection and classification of oral lesions for the early detection of oral cancer, these were image classification with ResNet-101 and object detection with the Faster R-CNN. Image classification achieved an F1 score of 87.07% for identification of images that contained lesions and 78.30% for the identification of images that required referral. Object detection achieved an F1 score of 41.18% for the detection of lesions that required referral. Further performances are reported with respect to classifying according to the type of referral decision. Our initial results demonstrate deep learning has the potential to tackle this challenging task. INDEX TERMS Composite annotation, deep learning, image classification, object detection, oral cancer, oral potentially malignant disorders.

Dimulai akhir Desember 2019 terjadi wabah virus baru di dataran china terkhusus di daerah Wuhan, yang secara cepat menyebar diluar China bahkan dalam waktu 2 bulan hampir seluruh dunia terinfeksi COVID-19, sehingga WHO menyatakan Outbreak COVID-19 Global Pandemic. Pada tanggal 2 maret 2020 Indonesia mengumumkan dimulainya kejadian wabah di wilayah Jakarta, Jawa Barat, dan Bali, dalam waktu singkat kurang 1 bulan, 34 provinsi terdeteksi COVID-19. Oleh karena Presiden RI menyatakan bencana nasional non alam, maka dibentuklah Gugus Tugas Percepatan Penanganan COVID-19 yang diawali oleh BNBP dari tingkat pusat hingga wilayah provinsi. Dengan adanya beberapa korban dokter gigi yang meninggal dunia akibat COVID-19, maka Kepala BNPB dan Kementerian Kesehatan menghimbau agar dokter gigi yang berisiko tinggi tertular COVID-19 saat memberikan pelayanan kesehatan gigi dan mulut, untuk sementara menghentikan pemberian pelayanan kecuali untuk kasus-kasus emergensi. Hampir 4 bulan para dokter gigi tidak praktik, tidak memberikan pelayanan langsung ke pasien, dan tidak dapat mengamalkan ilmu dan kompetensi dalam bentuk pengabdian kepada masyarakat. Banyak permintaan dan keluhan dari masyarakat, klinik, rumah sakit dan institusi pelayanan kesehatan agar para dokter gigi segera dapat berpraktik kembali, karena masyarakat kesulitan mendapatkan perawatan. Seiring dengan wacana Pemerintah menerapkan Kehidupan Normal Baru, atau Adaptasi Kebiasaan Baru yang dikenal dengan sebutan era New Normal, PB-PDGI memberikan kesempatan kepada dokter gigi seluruh Indonesia untuk memulai praktik kembali dengan berbagai ketentuan yang harus ditaati. Ketentuan-ketentuan ini dimaksudkan untuk melindungi dokter gigi dan tenaga kesehatan pendukung agar tidak tertular COVID-19, serta menghindari adanya infeksi silang di ruang tempat praktik. Dengan diterbitkan dan diberlakukannya Buku Panduan Dokter Gigi Dalam Era New Normal, maka dimulailah para dokter gigi Indonesia untuk berpraktik kembali. Buku ini memuat panduan secara lengkap, selain ketentuan berpraktik kembali di era new normal, tetapi juga tentang manajemen pembiayaan dan upaya promotif Kesehatan Gigi dan Mulut, yang didukung oleh literatur ilmiah yang kuat, sehingga dapat menjadi referensi bagi siapapun untuk penulisan ilmiah maupun penelitian. iv Ketua umum PB-PDGI memberikan apresiasi yang setinggi-tingginya kepada tim penulis buku Panduan Dokter Gigi Di Era New Normal, dengan dedikasi yang tinggi pula dan jerih payahnya mencari literatur, siang dan malam menyusun kata demi kata yang dirangkai menjadi kalimat-kalimat hingga terwujudnya buku ini yang menjadi pedoman bagi dokter gigi se-Indonesia untuk berpraktik di era new normal. Dengan penuh harapan, agar dokter gigi Indonesia dapat menggunakan buku ini secara bijak dan tidak menjadi keterpaksaan. Semoga Allah SWT selalu melindungi kita semua dan memberikan yang terbaik.. Aamiin...Aamiin… Ya Robbal 'alamin. Demikian terima kasih.

Purpose: This study aimed to determine the association between tobacco consumption (kretek) and betel quid chewing with oral cancer risk. Materials and Methods: A total of 81 cases of oral cancers were matched with 162 controls in this hospital-based study. Information on sociodemographic characteristics and details of risk habits (duration, frequency and type of tobacco consumption and betel quid chewing) were collected. Association between smoking and betel quid chewing with oral cancer were analysed using conditional logistic regression. Results: Slightly more than half of the cases (55.6%) were smokers where 88.9% of them smoked kretek. After adjusting for confounders, smokers have two fold increased risk, while the risk for kretek consumers and those smoking for more than 10 years was increased to almost three-fold. Prevalence of betel quid chewing among cases and controls was low (7.4% and 1.9% respectively). Chewing of at least one quid per day, and quid combination of betel leaf, areca nut, lime and tobacco conferred a 5-6 fold increased risk. Conclusions: Smoking is positively associated with oral cancer risk. A similar direct association was also seen among betel quid chewers.

A matched case-control, hospital-based study of oral cancer was conducted in Jakarta population. The sample included 81 cases and 162 controls. The purpose of this study was to determine the association between dietary pattern and oral cancer in a Jakarta population using factor analysis. Dietary data were collected using food frequency questionnaire and factor analysis was performed on 15 food groups resulting in four principle factors/components being retained. The first factor "preferred" was characterized by fast food, fermented food, canned food, snacks high in fat and sugar, cooked and raw vegetables, and seafood. The second factor labeled "combination" was loaded by the intake of dairy product, red meat, white meat and fruits. The third factor labeled "chemical related was loaded by processed food and monosodium glutamate and the fourth principle component consisted of drinks and grain was labeled as "traditional". The conditional logistic regression was done using STATA 8 to obtain the odds ratio (OR) of highest tertile of each component retained from factor analysis and the ORs were then adjusted with risk habits. The consumption the highest tertile of the "preferred" pattern increased the risk of oral cancer by two-times compared to the lowest tertile of consumption [adjusted odds ratio (aOR)=2.17; 95% confidence interval (CI)=1.05-4.50]. The chemical related" pattern showed higher risk of about threefold (aOR=2.56; 95% CI=1.18-5.54), while the "traditional" pattern showed an increased of risk by twofold (aOR=2.04; 95% CI=1.01-4.41). In contrast, the "combination" pattern displayed protective effects in relation to oral cancer (aOR=0.50; 95% CI=0.24-1.00). This finding suggests that factor analysis may be useful to determine the diet pattern of a big set of food type and establish the correlation with oral cancer.