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All Journal ELKHA : Jurnal Teknik Elektro Archives of Pediatric Gastroenterology, Hepatology, and Nutrition
Amalia Setyati
Bagian Ilmu Kesehatan Anak FK UGM/RSUP Dr. Sardjito, Jl. Kesehatan No. 1 Sekip Utara Bulaksumur, Yogyakarta - 55284
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Industrial & Manufacturing Engineering Medicine & Pharmacology

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Outcome of Abdominal Tuberculosis Complicated by Portal Hypertension, Pulmonary Tuberculosis, and Severe Acute Malnutrition Pattinasarany, Liona Christy; Widowati, Titis; Setyati, Amalia
Archives of Pediatric Gastroenterology, Hepatology, and Nutrition Vol. 3 No. 2 (2024): APGHN Vol. 3 No. 2 May 2024
Publisher : The Indonesian Society of Pediatric Gastroenterology, Hepatology, and Nutrition

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58427/apghn.3.2.2024.26-34

Abstract

Background: Abdominal tuberculosis (TB) is a form of extrapulmonary TB that can present with or without involvement of the lungs. The diagnosis is difficult to establish, which may lead to diagnostic delays. Effective management of adolescent TB requires a holistic approach from various medical disciplines and interventions. This case presented a rare case 13-year-old girl diagnosed with abdominal TB Case: A 13-year-old girl presented with seven-months history of subfebrile fever, lymph node enlargement, abdominal distention, pallor, and severe weight loss. She was diagnosed with abdominal TB. The diagnosis was further complicated by portal hypertension, pulmonary TB, and severe acute malnutrition. To address these challenges, a multidisciplinary treatment plan was implemented and closely monitored for a period of 12 months Discussion: Multiple factors are significantly contributing to the successful outcome of the treatment for abdominal tuberculosis, including good adherence to the prescribed anti-tuberculous medications, absence of side effects from the drugs, the patient's positive knowledge, attitude and health behaviours, and housing and environmental health. Conclusion: This case highlights the importance of factors influencing disease outcomes of abdominal TB. Proper management of the factors would lead to significant clinical and nutritional status improvement, reduce TB transmission, and improved the overall quality of life.
Computer Aided Classification of X-ray Images from Pediatric Pneumonia Subjects Collected in Developing Countries Amrulloh, Yusuf Aziz; Prasetyo, Bayu Dwi; Khoiriyah, Ummatul; Gunarti, Hesti; Setyowireni, Dwikisworo; Triasih, Rina; Naning, Roni; Setyati, Amalia
ELKHA : Jurnal Teknik Elektro Vol. 15 No.2 October 2023
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v15i2.69981

Abstract

Pneumonia is a lower tract respiratory infection due to bacteria or viruses. It is a severe disease in the pediatric population. Pneumonia is the leading cause of mortality in children under five years worldwide. One of the problems with pneumonia is the diagnosis, as the symptoms of pneumonia may overlap with other diseases, such as asthma and bronchiolitis. In this work, we propose to develop a method for classifying pneumonia and non-pneumonia using X-ray images. We collected 60 X-ray images from Dr. Sardjito Hospital, Yogyakarta, Indonesia, and the dataset from Kaggle. We processed these images through pre-processing algorithms to enhance the image quality, segmentation, white pixel computation, and classification. The novelty of our method is using the ratio of the white pixels from edge detection using the Canny algorithm with the white pixels from segmentation for classifying pneumonia/non-pneumonia. In the Kaggle dataset, our proposed method achieved an accuracy of 86.7%, a sensitivity of 100%, and a specificity of 85%. The classification using the dataset from Dr. Sardjito Hospital yields sensitivity, specificity, and accuracy of 80%, 60%, and 66.7%, respectively. Despite the low performance in the results, we proved our novel feature, ratio of white pixels, can be used to classify pneumonia/non-pneumonia. We also identified that the local dataset is essential in the algorithm development as it has a different quality from the dataset from modern countries. Further, our simple method can be developed further to support pneumonia diagnosis in resource-limited settings where the advanced computing devices or cloud connection are not available.
Co-Authors Amrulloh, Yusuf Aziz Dwikisworo Setyowireni Gunarti, Hesti Khoiriyah, Ummatul Pattinasarany, Liona Christy Prasetyo, Bayu Dwi Rina Triasih Roni Naning Titis Widowati, Titis