Panoramic and periapical radiographs utilization in Disaster Victim Identification (DVI): narrative review

Objectives: The purpose of this narrative review is to discover radiographic images in panoramic and periapical radiographs that are used as identifiers and to compare the use of panoramic and periapical radiographs in identification based on DVI. Review: The databases used in this narrative review are Google Scholar, PubMed, and Science Direct. A total of 1258 search results appeared based on keywords. The search results were selected by title and abstract according to their relevance to the review topic, then results are selected again based on the inclusion and exclusion criteria. Total of 38 literatures were reviewed. This review shows radiographic identifiers used in panoramic radiographs are tooth restorations, crown, Root Canal Treatment (RCT), dental bridge, dental implants, maxillary sinus, rectilinear metal plate, orthodontic brackets, tooth anomaly, and root morphology. The radiographic identifiers used in periapical radiograph are tooth restorations, PSA, tooth anomaly, and root morphology. In this review, 53.8% of the literatures used panoramic radiograph for identification, whereas 46.2% used periapical radiograph. Conclusion: This review concluded that the most used radiographic identifier in panoramic radiograph is tooth restoration (57,1%) whereas in periapical radiograph is RCT (83,3%). Panoramic radiography were used in 53,8% of the literatures in this review, it was used more than periapical radiography.

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Beban Kerja Perawat Gawat Darurat Dimasa Pandemi Covid19 :Narrative Review

Prosiding Seminar Nasional Kesehatan ◽

10.48144/prosiding.v1i.982 ◽

2021 ◽

Vol 1 ◽

pp. 2120-2128

Author(s):

Yanu Triana Nadhifa ◽

Benny Arief Sulistyanto

Keyword(s):

Emergency Room ◽

Negative Impact ◽

Scientific Evidence ◽

Narrative Review ◽

Emergency Nurses ◽

Exclusion Criteria ◽

Search Results ◽

Main Factors ◽

New Challenges ◽

The Impact

AbstractThe workload of emergency nurses during the COVID-19 pandemic includes mental and physical stress. They must always be ready to deal with patients who come with uncertain symptoms. The workload of emergency nurses is important to study to minimize the negative impact of excessive workload. The impact include fatigue, stress, and anxiety. This study aimed to determine the workload of emergency nurses during the COVID-19 pandemic based on the available literature. This study used the Narrative review method. The databases used to search articles were PubMed, and Clinicalkey for Nursing. Articles were selected based on their suitability with the keywords “Workload” OR “Workloads” AND “Emergency Nurse” OR “Emergency room” AND “COVID-19” OR “SARS-CoV-19” and the inclusion and exclusion criteria that had been determined. The search results obtained 6 articles. The results of this study showed that the workload Emergency nurses during the COVID-19 pandemic was in the moderate category with results of 68.36 ± 15.86 obtained from 2 articles, and obtained a range of 20-43 from 1 article. There are the same findings from the 3 articles; fear of being infected with a virus, high pressure, and new challenges during the pandemic. These could be the main factors that affect the work of nurses. The findings of the workload of emergency nurses during the COVID-19 pandemic are obtained from valid scientific evidence. Therefore, this study can be used ass a reference in research. Keywords: Workload, COVID-19 Pandemic, IGD/ER/ Emergency Nurse, AbstrakBeban kerja perawat gawat darurat dimasa pandemi COVID-19 meliputi tekanan mental maupun tekanan fisik, perawat gawat darurat harus selalu siap berhadapan dengan pasien yang datang dengan gejala tidak pasti. Beban kerja perawat gawat darurat penting diteliti untuk meminimalisir dampak negatif dari beban kerja yang berlebih. Dampak beban kerja perawat gawat darurat dimasa pandemi COVID-19 meliputi kelelahan, stress dan kecemasan. Penelitian ini bertujuan untuk beban kerja pada perawat gawat darurat (emergency) dimasa pandemi COVID-19 berdasarkan literatur yang tersedia. Penelitian menggunakan metode Narrative review. Database yang digunakan untuk pencarian artikel adalah PubMed, dan Clinicalkey for Nursing. Artikel diseleksi berdasarkan kesesuaian dengan kata kunci “Workload” OR “Workloads” AND “Emergency Nurse” OR “Emergency room” AND “COVID-19” OR “SARS-CoV-19” serta kriteria inklusi dan eksklusi yang telah ditentukan. Hasil penelusuran didapatkan sebanyak 6 artikel. Hasil dari penelitian ini didapatkan beban kerja perawat gawat darurat dimasa pandemi COVID-19 ter masuk dalam kategori sedang dengan hasil 68,36 ± 15,86 yang didapatkan dari 2 artikel, dan didapatkan range 20-43 dari 1 artikel. Terdapat temuan yang sama dari ke-3 artikel ; takut terinfeksi virus, tekanan tinggi, dan tantangan baru dimasa pandemi yang dapat menjadi faktor pengaruh utama yang mempengaruhi kerja perawat. Temuan beban kerja perawat gawat darurat dimasa pandemi COVID-19 ini didapatkan dari bukti ilmiah yang valid sehingga dapat dijadikan referensi referensi dalam penelitian. Kata kunci : Beban kerja, Pandemi COVID-19, Perwat gawat darurat/IGD/UGD.

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Mass Disaster Victim Identification Assisted by DNA Typing

Molecular Diagnostics ◽

10.1016/b978-0-12-374537-8.00027-4 ◽

2010 ◽

pp. 407-415 ◽

Cited By ~ 1

Author(s):

Daniel Corach

Keyword(s):

Dna Typing ◽

Mass Disaster ◽

Disaster Victim Identification ◽

Victim Identification ◽

Disaster Victim

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The contribution of DNA to the disaster victim identification (DVI) effort

Forensic Science International ◽

10.1016/j.forsciint.2010.09.024 ◽

2011 ◽

Vol 205 (1-3) ◽

pp. 52-58 ◽

Cited By ~ 32

Author(s):

D. Hartman ◽

O. Drummer ◽

C. Eckhoff ◽

J.W. Scheffer ◽

P. Stringer

Keyword(s):

Disaster Victim Identification ◽

Victim Identification ◽

Disaster Victim

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Multi-Task Deep Learning Model for Classification of Dental Implant Brand and Treatment Stage Using Dental Panoramic Radiograph Images

Biomolecules ◽

10.3390/biom11060815 ◽

2021 ◽

Vol 11 (6) ◽

pp. 815

Author(s):

Shintaro Sukegawa ◽

Kazumasa Yoshii ◽

Takeshi Hara ◽

Tamamo Matsuyama ◽

Katsusuke Yamashita ◽

...

Keyword(s):

Deep Learning ◽

Dental Implant ◽

Area Under The Curve ◽

Treatment Phase ◽

Panoramic Radiograph ◽

Radiographic Images ◽

Treatment Stage ◽

Prefectural Central Hospital ◽

Dental Panoramic Radiograph

It is necessary to accurately identify dental implant brands and the stage of treatment to ensure efficient care. Thus, the purpose of this study was to use multi-task deep learning to investigate a classifier that categorizes implant brands and treatment stages from dental panoramic radiographic images. For objective labeling, 9767 dental implant images of 12 implant brands and treatment stages were obtained from the digital panoramic radiographs of patients who underwent procedures at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2020. Five deep convolutional neural network (CNN) models (ResNet18, 34, 50, 101 and 152) were evaluated. The accuracy, precision, recall, specificity, F1 score, and area under the curve score were calculated for each CNN. We also compared the multi-task and single-task accuracies of brand classification and implant treatment stage classification. Our analysis revealed that the larger the number of parameters and the deeper the network, the better the performance for both classifications. Multi-tasking significantly improved brand classification on all performance indicators, except recall, and significantly improved all metrics in treatment phase classification. Using CNNs conferred high validity in the classification of dental implant brands and treatment stages. Furthermore, multi-task learning facilitated analysis accuracy.

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