Pediatric Viral and Bacterial Skin Infection Profile

Dimawan, Rully Setia Agus; Prakoeswa, Flora Ramona Sigit; Pramuningtyas, Ratih

doi:10.20473/bikk.v34.3.2022.184-188

Cited by 2 publications

(2 citation statements)

References 23 publications

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“…Berdasarkan distribusi kategori infeksi bakteri didapatkan bahwa prevalensi terbanyak yaitu penyakit impetigo krustosa dengan 15 kasus atau 26.3%. Pada studi yang dilakukan di RSU Dr. Harjono S. Ponorogo dilaporkan bahwa impetigo krustosa adalah presentasi terbanyak dari infeksi bakteri pada pasien anak usia 0 hingga <18 tahun (Dimawan et al, 2022).…”

Section: Hasil Dan Pembahasanunclassified

Profil Penyakit Kulit pada Pasien Anak yang Berobat di Poliklinik Kulit dan Kelamin RSUD Provinsi Nusa Tenggara Barat Periode Januari 2020–Juni 2023

Hendrawan,

Pratama,

Nurlalwani

et al. 2023

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Skin diseases can affect all ages, children are no exception. Skin diseases in children can cause considerable discomfort, parental anxiety, and embarrassment in children and impact on absenteeism rates in school-age children. The purpose of this study was to determine the statistical epidemiology of pediatric skin diseases so that they could provide information regarding the prevalence of the disease so that it could be a way to evaluate the causes of skin diseases to help prevent and treat skin diseases. This study using descriptive retrospective method from secondary data from medical records of children aged 0 to 18 years undergoing treatment at the Dermatology and Venereology Polyclinic at Nusa Tengara Barat Province Hospital in the period January 2020 - June 2023. Then processed with software for presentation in tabular form. During this period, there were 475 pediatric patients with 448 new patients and 27 old patients. Generally men numbered 282 (59.4%). The most common categories of skin diseases in children were infectious diseases with 288 cases (60.6%), dermato-allergo-immunology with 89 cases (18.7%) and non-infectious diseases with 59 cases (12.5%). Most skin diseases are caused by infections, mainly parasitic infestations (mostly scabies), fungal infections (mostly pityriasis versicolor) and followed by bacterial infections (mostly impetigo crustosa).

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Section: Hasil Dan Pembahasanunclassified

Profil Penyakit Kulit pada Pasien Anak yang Berobat di Poliklinik Kulit dan Kelamin RSUD Provinsi Nusa Tenggara Barat Periode Januari 2020–Juni 2023

Hendrawan,

Pratama,

Nurlalwani

et al. 2023

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“…It impacts all age groups, with approximately 15 million affected in the United States alone, of which 60% are children under 12 years-old [ 3 ]. Data from the Indonesian Pediatric Dermatology Research Group indicates that AD topped the list of pediatric dermatological diseases in 2022, with over 703,270 reported cases in Indonesia [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of atopic dermatitis severity using artificial intelligence

Maulana,

Noviandy,

Suhendra

et al. 2023

Narra J

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Atopic dermatitis is a prevalent and persistent chronic inflammatory skin disorder that poses significant challenges when it comes to accurately assessing its severity. The aim of this study was to evaluate deep learning models for automated atopic dermatitis severity scoring using a dataset of Aceh ethnicity individuals in Indonesia. The dataset of clinical images was collected from 250 patients at Dr. Zainoel Abidin Hospital, Banda Aceh, Indonesia and labeled by dermatologists as mild, moderate, severe, or none. Five pre-trained convolutional neural networks (CNN) architectures were evaluated: ResNet50, VGGNet19, MobileNetV3, MnasNet, and EfficientNetB0. The evaluation metrics, including accuracy, precision, sensitivity, specificity, and F1-score, were employed to assess the models. Among the models, ResNet50 emerged as the most proficient, demonstrating an accuracy of 89.8%, precision of 90.00%, sensitivity of 89.80%, specificity of 96.60%, and an F1-score of 89.85%. These results highlight the potential of incorporating advanced, data-driven models into the field of dermatology. These models can serve as invaluable tools to assist dermatologists in making early and precise assessments of atopic dermatitis severity and therefore improve patient care and outcomes.

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Pediatric Viral and Bacterial Skin Infection Profile

Cited by 2 publications

References 23 publications

Profil Penyakit Kulit pada Pasien Anak yang Berobat di Poliklinik Kulit dan Kelamin RSUD Provinsi Nusa Tenggara Barat Periode Januari 2020–Juni 2023

Profil Penyakit Kulit pada Pasien Anak yang Berobat di Poliklinik Kulit dan Kelamin RSUD Provinsi Nusa Tenggara Barat Periode Januari 2020–Juni 2023

Evaluation of atopic dermatitis severity using artificial intelligence

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