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All Journal Journal of Robotics and Control (JRC) Cermin Dunia Kedokteran Sewagati Jurnal Penyakit Dalam Indonesia
Njoto, Edwin Nugroho
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Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Peranan Candida Score untuk Deteksi Infeksi Fungal Invasif di ICU Njoto, Edwin Nugroho
Cermin Dunia Kedokteran Vol 41, No 1 (2014): Neurologi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (93.172 KB) | DOI: 10.55175/cdk.v41i1.1175

Abstract

Diagnosis dini penting untuk mengontrol infeksi Candida invasif pada pasien ICU (intensive care unit) dan memperbaiki prognosis. Candida score dapat membantu dokter mengidentifikasi pasien yang akan mendapat manfaat dari pemberian antifungal dini dan pasien yang hampir tidak mungkin terinfeksi candida invasif.Early diagnosis is important to control invasive Candida infection in the ICU (intensive care unit) patients and to improve prognosis. Candida score can help to identify who will benefit from early antifungal therapy and who is unlikely to get invasive Candida infection. 
Target Tekanan Darah pada Diabetes Melitus Njoto, Edwin Nugroho
Cermin Dunia Kedokteran Vol 41, No 11 (2014): Infeksi
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (118.297 KB) | DOI: 10.55175/cdk.v41i11.1075

Abstract

Hipertensi merupakan salah satu masalah utama kesehatan masyarakat di seluruh dunia dan merupakan faktor risiko penyakit kardiovaskular tersering, tetapi belum terkontrol optimal. Para peneliti melakukan penelitian dan membuat panduan untuk mengontrol hipertensi. Salah satu panduan yang terbaru adalah JNC VIII. Tinjauan pustaka ini akan membahas target tekanan darah pada penderita diabetes menurut JNC VIII serta membandingkannya dengan rekomendasi panduan lain.Hipertension is one of the main problem of public health in the world and one of the most frequent cardiovascular risk factors, but not optimally controlled. Researches were done and guidelines were formulated. The newest guideline is JNC VIII. This review will discuss blood pressure target for diabetic patients in JNC VIII and its comparison with other guidelines.
Mengenali Depresi pada Usia Lanjut Penggunaan Geriatric Depression Scale (GDS) untuk Menunjang Diagnosis Njoto, Edwin Nugroho
Cermin Dunia Kedokteran Vol 41, No 6 (2014): Bedah
Publisher : PT. Kalbe Farma Tbk.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (115.529 KB) | DOI: 10.55175/cdk.v41i6.1133

Abstract

Gejala depresi pada usia lanjut sering bertumpangtindih dengan gejala somatiknya dan sering tidak terdiagnosis dengan baik; keluarga pasien maupun dokter acapkali tidak mewaspadai kondisi ini. Dokter umum sebagai lini terdepan pelayanan medis harus mampu mengenali gejala depresi pada lanjut usia. Geriatric Depression Scale dapat digunakan untuk mempermudah pengenalan gejala depresi pada usia lanjut terutama pada penderita dengan fungsi kognitif yang masih intak.Depression in elderly is difficult to diagnose because the symptoms are atypical; patient, patient's family, and physicians are rarely aware of the symptoms. The symptoms are usually overlap with somatic symptoms and often underdiagnosed. General practitioner as first line in medical service should be able to recognize depression in elderly person. Geriatric Depression Scale can be used to screen depression in senior person, especially those with intact cognitive function. 
Sarkopenia pada Lanjut Usia: Patogenesis, Diagnosis dan Tata Laksana Njoto, Edwin Nugroho; Suka Aryana, I Gusti Putu
Jurnal Penyakit Dalam Indonesia Vol. 10, No. 3
Publisher : UI Scholars Hub

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Abstract

‘Sarcopenia’ involves a progressive age-related loss of muscle mass and associated muscle weakness that renders frail elders susceptible to serious injury from sudden falls and fractures and losing their functional independence. This disease has a complex multifactorial pathogenesis, which involves not only age-related changes in neuromuscular function, muscle protein turnover, and hormone levels and sensitivity, but also a chronic pro-inflammatory state, oxidative stress, and behavioral factors – in particular, nutritional status and degree of physical activity. In the previous definition by the European Working Group on Sarcopenia in Older People (EWGSOP) in 2010, the diagnosis of sarcopenia requires the presence of both low muscle mass and low muscle function. Since the 2010 definition is difficult to be translated to clinical practice, the EWGSOP uses low muscle strength as the primary parameter of sarcopenia in the 2018 definition; sarcopenia is probable when low muscle strength is detected. A sarcopenia diagnosis is confirmed by the presence of low muscle quantity or quality. When low muscle strength, low muscle quantity/quality and low physical performance are all detected, sarcopenia is considered severe. According to the pathophysiological factors involved in the pathogenesis of sarcopenia, different treatment strategies against sarcopenia are resistance exercise training, increase essential amino acids intake, vitamin D supplementation for those with vitamin D deficiency, polyunsaturated fatty acids (PUFAs) supplementation, testosterone supplementation, angiotensin-converting enzyme inhibitor administration.
Effectiveness of CNN Architectures and SMOTE to Overcome Imbalanced X-Ray Data in Childhood Pneumonia Detection Pamungkas, Yuri; Ramadani, Muhammad Rifqi Nur; Njoto, Edwin Nugroho
Journal of Robotics and Control (JRC) Vol 5, No 3 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i3.21494

Abstract

Pneumonia is a disease that causes high mortality worldwide in children and adults. Pneumonia is caused by swelling of the lungs, and to ensure that the lungs are swollen, a chest X-ray can be done. The doctor will then analyze the X-ray results. However, doctors sometimes have difficulty confirming pneumonia from the results of chest X-ray observations. Therefore, we propose the combination of SMOTE and several CNN architectures be implemented in a chest X-ray image-based pneumonia detection system to help the process of diagnosing pneumonia quickly and accurately. The chest X-ray data used in this study were obtained from the Kermany dataset (5216 images). Several stages of pre-processing (grayscaling and normalization) and data augmentation (shifting, zooming, and adjusting the brightness) are carried out before deep learning is carried out. It ensures that the input data for deep learning is not mixed with noise and is according to needs. Then, the output data from the augmentation results are used as input for several CNN deep learning architectures. The augmented data will also utilize SMOTE to overcome data class disparities before entering the CNN algorithm. Based on the test results, the VGG16 architecture shows the best level of performance compared to other architectures. In system testing using SMOTE+CNN Architectures (VGG16, VGG19, Xception, Inception-ResNet v2, and DenseNet 201), the optimum accuracy level reached 93.75%, 89.10%, 91.67%, 86.54% and 91.99% respectively. SMOTE provides a performance increase of up to 4% for all CNN architectures used in predicting pneumonia.
Deteksi Dini dan Peningkatan Kewaspadaan Tentang Stroke untuk Masyarakat di Kelurahan Kanigaran Njoto, Edwin Nugroho; Radiansyah, Riva Satya; Abdurrahman; Mahdi, Faizal; Mulyasaputra, Galih Endradita; Rifqo, Muhammad; Putro, Yohanes Kartjito; Ramadani, Muhammad Rifqi Nur
Sewagati Vol 8 No 3 (2024)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v8i3.970

Abstract

Stroke merupakan penyebab kematian terbanyak ketiga di dunia, dengan dampak serius terhadap kesehatan dan kualitas hidup individu. Kegiatan pengabdian masyarakat dilakukan di Kota Probolinggo, dengan fokus pada peningkatan kesadaran deteksi dini faktor risiko stroke. Kegiatan ini menyajikan konsep yang mencakup penyuluhan tentang tanda dan gejala stroke, faktor risiko stroke, dan tata laksana awal stroke dengan melibatkan masyarakat di Kelurahan Kanigaran. Berbagai media digunakan termasuk penyuluhan, video edukatif, dan pemeriksaan langsung faktor risiko stroke. Hasil kegiatan menunjukkan tingginya antusiasme masyarakat, terutama dalam sesi tanya jawab. Mayoritas peserta adalah perempuan, dan banyak dari mereka memiliki hipertensi yang belum mendapatkan pengobatan. Tujuan kegiatan adalah meningkatkan kesadaran masyarakat sekitar tentang deteksi dini penyakit stroke, serta memberikan pemahaman yang lebih baik tentang faktor risiko dan tanda gejala stroke. Manfaat kegiatan ini melibatkan pengembangan kemampuan komunikasi sumber daya manusia ITS yang terlibat dan memberikan wawasan masyarakat sekitar mengenai deteksi dini stroke. Dampaknya diharapkan akan mengurangi angka kejadian stroke baru melalui deteksi dini yang lebih cepat dan optimal, serta meningkatkan kesembuhan pasien stroke. Kesimpulannya, kegiatan pengabdian masyarakat ini berhasil meningkatkan kesadaran dan pengetahuan masyarakat sekitar tentang stroke, khususnya di Kota Probolinggo. Dengan upaya ini, diharapkan dapat mengurangi angka kejadian stroke dan meningkatkan kualitas hidup warga setempat.
Analisis Prediktif Mutasi EGFR pada Adenokarsinoma Paru Menggunakan Pendekatan Pembelajaran Mesin Njoto, Edwin Nugroho; Pamungkas, Yuri; Putri, Atina I.W.; Haykal, Muhammad. Najib; Eljatin, Dwinka Syafira; Djaputra, Edith Maria
Jurnal Penyakit Dalam Indonesia
Publisher : UI Scholars Hub

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Abstract

Introduction. Lung adenocarcinoma is a prevalent form of lung cancer, and mutations in the epidermal growth factor receptor (EGFR) gene are known to play a crucial role in its pathogenesis. This study aimed to develop a machine-learning model to predict EGFR mutations in lung adenocarcinoma patients using clinical and radiological features. Methods. A case-control study was conducted using a dataset comprising 160 patients with lung adenocarcinoma. Several machine learning algorithms, including decision tree, linear regression, Naive Bayes, support vector machine, K-nearest neighbor, and random forest, were employed to predict EGFR mutations based on variables such as smoking status, tumor diameter, tumor location, bubble-like appearance on CT-scan, air-bronchogram on CT-scan, and tumor distribution. Results. Most study subjects were over 50 years old (83.75%) and female (53.13%). The analysis results indicated that the random forest model demonstrated the best performance, achieving an accuracy of 83.33%, precision of 86.96%, recall of 80.00%, and an Area Under the Curve (AUC) of 90.0. The Naive Bayes model also performed well, with an accuracy of 85.42%, precision of 82.61%, recall of 86.36%, and an AUC of 91.0. Conclusions. The study highlights the potential of machine learning techniques, particularly random forest and Naive Bayes, in accurately predicting EGFR mutations in lung adenocarcinoma patients based on readily available clinical and radiological features. These findings could contribute to the development of non-invasive, cost-effective, and efficient tools for EGFR mutation detection, ultimately facilitating personalized treatment approaches for lung adenocarcinoma patients.
Co-Authors Abdurahman Abdurrahman Adhi Dharma Wibawa, Adhi Dharma Djaputra, Edith Maria Dwinka Syafira Eljatin Fadli, Sonny Fitriani, Fatimah Nur Haykal, Muhammad Nazhif Haykal, Muhammad. Najib Hedianto, Tri Hidayah, Rizka Nurul I Gusti Putu Suka Aryana Imam Susilo Indriani, Ratri Dwi Indriastuti, Endah Karimah, Rumman Mahdi, Faizal Mulyasaputra, Galih Endradita Pamungkas, Yuri Parlindungan, Putra Gelar Putra, Gumilar Fardhani Ami Putri Alief Siswanto Putri, Atina I.W. Putri, Atina Irani Wira Putro, Yohanes Kartjito Radiansyah, Riva Satya Ramadani, Muhammad Rifqi Nur Rangkuti, Rahmah Yasinta Ridhoi, Ahmad Rifqo, Muhammad Sakina Syulthoni, Zain Budi