Edwin Nugroho Njoto

@its.ac.id

Faculty of Medicine and Health
Institut Teknologi Sepuluh Nopember

11

Scopus Publications

131

Scholar Citations

6

Scholar h-index

5

Scholar i10-index

Scopus Publications

  • Mapping the Landscape of Palliative Care in Indonesia: A Scoping Review of Availability, Accessibility, and Quality
    Rick Fuh Chun Koh, Jerico Fransiscus Pardosi, Edwin Nugroho Njoto
    Journal of Health Science and Medical Research, 2026
    Indonesia has made notable strides in palliative care services over recent decades, yet substantial challenges persist, particularly in rural and under-resourced regions. This scoping review assesses the current landscape of palliative care in Indonesia, focusing on service availability, accessibility, and quality, including the effects of the coronavirus disease 2019 (COVID-19) pandemic. Following the Joanna Briggs Institute’s methodology and the PCC (Population, Concept, Context) framework, relevant studies published between 2016 and 2024 were sourced from databases such as ScienceDirect and PubMed. Findings indicate that although some progress has been achieved, palliative care services remain limited and unevenly distributed, with stark urban–rural disparities and a heavy reliance on out-of-pocket payments or charitable support. Integration into the national healthcare system remains minimal, hindered by inadequate infrastructure, insufficient policy implementation, and a shortage of trained providers. In the absence of formal support, the burden of care largely falls on family members, who face significant financial and emotional strain. These findings underscore an urgent need for strengthened policy frameworks, dedicated funding mechanisms, and culturally appropriate care models to improve access and equity. Future efforts should prioritize embedding palliative care into Indonesia’s core health services while addressing the diverse needs of patients and families across the country.
  • Determinants of subclinical leprosy among household contacts in Indonesia: serological and socio-demographic factors
    Khariri Khariri, Sunarno Sunarno, Novaria Sari Dewi Panjaitan, Putu Yuliandari, Sarwo Handayani, Rita Marleta Dewi, Nastiti Intan Permata Sari, Fitriana Fitriana, Agriani Dini Pasiana, Ina Kusrini, Edwin Nugroho Njoto
    Peerj, 2026
    Background Leprosy remains a public health challenge in Indonesia, which ranks third globally after India and Brazil. Subclinical infection among household contacts contributes to ongoing transmission, as individuals infected with Mycobacterium leprae ( M. leprae ) without symptoms may serve as undetected reservoirs. This study investigated serological and sociodemographic determinants associated with subclinical M. leprae infection among household contacts of leprosy patients in Tangerang, Indonesia. Methods A cross-sectional study was conducted in 2020 among 320 household contacts of confirmed leprosy index cases recruited through purposive sampling. Anti-Phenolic Glycolipid-1 (PGL-1) IgM antibodies were detected using an in-house enzyme-linked immunosorbent assay (ELISA). Bivariate analysis using Chi-square and t -tests assessed preliminary associations, and multivariate logistic regression was applied to identify independent predictors of seropositivity, adjusting for potential confounders. Results Overall, 43.8% of household contacts were seropositive for anti-PGL-1 IgM antibodies. Multivariate analysis revealed that a history of Bacille Calmette-Guerin (BCG) vaccination was associated with significantly lower odds of seropositivity (adjusted OR = 0.514; 95% CI [0.291–0.907]; p = 0.018), while the presence of a visible BCG scar was associated with nearly twofold higher odds (adjusted OR = 1.953; 95% CI [1.117–3.415]; p = 0.024). No significant associations were found between sociodemographic factors such as age, sex, or contact duration, and seropositivity. Conclusion BCG vaccination status and visible BCG scars were key determinants of anti-PGL-1 seropositivity, suggesting complex interactions between vaccination, immune response, and exposure to M. leprae . The study highlights the protective role of BCG-induced immunity while emphasizing the need for standardized scar assessment and continuous surveillance of household contacts. Although limited by its cross-sectional and purposive design, the integration of immunological and epidemiological data represents a strength, providing evidence to support Indonesia’s Zero Leprosy 2030 control strategy.
  • Risk Factors of Nonsteroidal Anti-inflammatory Drug-exacerbated Respiratory Disease: A Systematic Review and Meta-analysis of Observational Studies
    Edwin Nugroho Njoto, Moon Fai Chan, Anak Agung Bagus Wirayuda, Gumilar Fardhani Ami Putra, Desiana Widityaning Sari, Endah Indriastuti, Rizka Nurul Hidayah, Yuri Pamungkas, Edith Maria Djaputra
    Oman Medical Journal, 2025
    Objectives: This meta-analysis aimed to identify the risk factors associated with nonsteroidal anti-inflammatory drug -exacerbated respiratory disease (NERD), a chronic eosinophilic, inflammatory respiratory disorder characterized by hypersensitivity to aspirin or nonsteroidal anti-inflammatory drugs in patients with asthma and chronic rhinosinusitis with nasal polyps. Methods: We systematically reviewed 19 eligible studies and assessed their quality using the Joanna Briggs Institute Qualitative Assessment and Review Instrument. Descriptive statistics and meta-analyses were conducted to estimate the pooled odds ratio and identify the risk factors associated with NERD. The analysis considered factors such as age, gender, body mass index, family history, smoking, and atopy. Results: Being female, having atopy, a history of smoking, and a family history of asthma were significant risk factors for NERD. Female gender was associated with hormonal differences and the effects of progesterone and estrogen on inflammation and bronchial hyperresponsiveness. Atopy increased the risk through heightened airway sensitivity, persistent inflammation, and increased mast cell activation. Smoking contributes to NERD by causing chronic airway inflammation, excess mucus production, airway remodeling, and decreased lung function. A family history of asthma indicated a genetic predisposition to bronchial hyperresponsiveness. Conclusions: The meta-analysis identified several risk factors associated with NERD, including being female, having atopy, a history of smoking, and a family history of asthma. These factors contribute to increased susceptibility and inflammation in patients with NERD.
  • Low subcutaneous fat as a risk factor for sarcopenia among elderly women in Bali, Indonesia a community-based age-matched case-control study
    Malta Medical Journal, 2024
  • Determining Positive-Negative Emotions in Male and Female Based on EEG Signals using Machine Learning Algorithms
    Yuri Pamungkas, Edwin Nugroho Njoto
    International Conference on Electrical Engineering Computer Science and Informatics Eecsi, 2024
    Emotionsare vital in everyday human life as a controller of behavior, decision-making and as a means to determine product marketing strategy/ market research. All of these things are very dependent on human emotional conditions. In addition, in the development of the computational affective field, brain signal-based emotion recognition (EEG) has become a trending topic of current research. Therefore, we attempted to compare positive-negative emotions in men and women based on EEG using a Machine Learning algorithm in this study. A total of 20 male and 20 female participants recorded their EEG signals in the frontopolar and frontal areas of the brain. Then the EEG data is processed by filtering, removing artifact, and decomposing it into three sub-bands (alpha, beta, and gamma). The extracted signal features are Mean Absolute Deviation and Power Spectral Density. Based on the signal feature analysis results, it is known that the signal feature values (MAD and PSD) for women tend to be higher than for men. Meanwhile, several algorithms are used to classify positive and negative emotions, such as Naive Bayes, K-Nearest Neighbor, Support Vector Machine, and Random Forest. Based on the results of classification, the best accuracy rate was 95.8% (on positive emotions for male & female gender), 92.2% (on negative emotions for male & female gender), and 79.8% (on positive-negative emotions for male & female gender) using Random Forest algorithm.
  • Effectiveness of CNN Architectures and SMOTE to Overcome Imbalanced X-Ray Data in Childhood Pneumonia Detection
    Journal of Robotics and Control Jrc, 2024
  • Identification of Potential Drug-Drug Interactions Using EMR Text-Mining on Atherosclerotic Heart Disease Patients
    Mukhlish Fuadi, Adhi Dharma Wibawa, Edwin Nugroho Njoto, Ghulam Asrofi Buntoro
    Proceedings of the 2024 IEEE International Conference on Industry 4 0 Artificial Intelligence and Communications Technology Iaict 2024, 2024
    Atherosclerotic heart disease patients often exhibit comorbidities, leading to polypharmacy and a heightened risk of Drug-Drug Interaction (DDI). This study investigated the harmful potential of Drug-Drug Interactions (DDIs) in patients diagnosed with atherosclerotic heart disease using Electronic Medical Records (EMR) from a private hospital in the East Java region, Indonesia. The research employed a comprehensive methodology encompassing preprocessing, drug name extraction, mapping, and assessing concomitant medications by leveraging text-mining technology on 24,672 records. DDI identification is carried out based on the DDInter database. Based on 24,660 data that have been cleaned, 149 generic drugs were obtained, of which 117 are available in the DDInter database. The findings revealed 33 DDIs at the major risk level among 117 drugs. Among those data, the number of records containing DDI at major, moderate, and minor risk levels or their combination in EMR data was 15,514 (62.91%), and many records were found to have more than one risk level. The DDIs found were 10.45% (2,577 records) at the major risk level, 46.80% (11,542 records) at the moderate risk level, and 44.78% (11,043 records) at the minor risk level. The prominent presence of major-risk and moderate-risk interactions underscores the significance of addressing DDIs in clinical practice. Healthcare services can be reinforced through education, adopting computerized prescribing systems, and enhancing drug information dissemination to mitigate these risks. The results contribute valuable insights into the prevalence of DDIs in atherosclerotic heart disease patients, guiding efforts to improve patient safety and optimize pharmaceutical interventions.
  • Implementation of EfficientNet-B0 Architecture in Malaria Detection System Based on Patient Red Blood Cell (RBC) Images
    Yuri Pamungkas, Edwin Nugroho Njoto, Dwinka Syafira Eljatin, Intan Fitri Hardyanti, Tazkiya Umamah, Kartika Jilan Putri
    Proceeding 2024 International Conference on Information Technology Research and Innovation Icitri 2024, 2024
    Malaria is an infectious disease with the most significant number of sufferers currently. The Plasmodium parasite and diagnosis cause this disease involves observing the patient’s red blood cells (RBC) by medical personnel. However, with technological advances, RBC observation can become easier with the help of artificial intelligence algorithms. Therefore, researchers attempted to develop a malaria detection system based on RBC images using the CNN EfficientNet-B0 method in this study. The RBC dataset was obtained from the publicly accessible National Institutes of Health (NIH) repository. Data pre-processing starts with augmentation, resizing, rotation, and horizontal flip in the initial stage. Then, class weighting is carried out, and the dataset is divided into training, validation, and testing data. In the model training process, $\\mathbf{1 0}$-fold cross-validation was used with 15 epochs. The testing results showed that the EfficientNet-B0 model had accuracy, precision, specificity, sensitivity, and F-1 scores, reaching 97.37%, 98.17%, 98.17%, 96.58%, and 97.37%. In addition, at the 12 th epoch, the EfficientNet-B0 model achieved optimal accuracy in the training and validation process. These results are higher and more efficient than other CNN models used in this research, such as VGG19, MobileNet, Inception, and Xception, whose accuracies reached 96.15%, 95.74%, 95.92%, and 95.83%, respectively.
  • Predicting EGFR Mutation in Lung Adenocarcinoma: Development and Validation of the EGFR Mutation Predictive Score (EMPS) in Bali, Indonesia
    Edwin Nugroho Njoto, Ida Ayu Jasminarti Dwi Kusumawardani, Ida Bagus Ngurah Rai
    Asian Pacific Journal of Cancer Prevention, 2023
    Introduction: The examination of epidermal growth factor receptor (EGFR) mutations may not be routinely available to all patients due to the limited availability and the expensive price of the examination, especially in area with limited resources such as in Indonesia. Therefore, we aimed to build a nomogram to predict the EGFR mutation in patients with lung adenocarcinoma by incorporating significant clinical and radiological parameters. Methods: We conducted an age-matched case–control study using 160 treatment-naïve patients [80 patients with EGFR-mutated (EGFRmut) and 80 with EGFR-wild-type (EGFRwt)] with pathologically confirmed lung adenocarcinomas with tumor specimens available for genetic analysis taken from 2017 through 2021 in Bali, Indonesia. Radiomics features were extracted from contrast CT images. The cut-off of the tumor diameter was defined using Receiver Operating Characteristic Curve. A conditional logistic regression model was constructed to identify significant risk factors, and a nomogram was developed for predicting the risk of EGFR mutation. A cohort was done to validate the nomogram. Result: Being female, never-smoker, having a smaller tumor diameter (<48.5mm), located in the upper lobe, have bubble-like lucency and air-bronchogram in the chest CT scan were identified as independent risk factors of EGFR mutation at the multivariate logistic regression model. The forming normogram model produced an area under the curve of 0.993 (95 % CI = 0.98−1.00) and 0.91 (95 % CI = 0.84−0.99) in development and validation group, respectively. The calibration curve showed good agreement between predicted and actual probability. At the cut-off point of the normogram score 246 shows a sensitivity of 97.5%, a specificity of 98.8%, a positive predictive value of 99.0%, and a negative predictive value of 96.8%. Conclusion: Our study indicated that the EGFR Mutation Normogram could provide a non-invasive way to predict the risk of EGFR mutation in patients with lung adenocarcinoma in clinical practice. This normogram need to be validated in other area in Indonesia.
  • Characterising routes of H5N1 and H7N9 spread in China using Bayesian phylogeographical analysis
    Chau M. Bui, Dillon C. Adam, Edwin Njoto, Matthew Scotch, C. Raina MacIntyre
    Emerging Microbes and Infections, 2018
    Avian influenza H5N1 subtype has caused a global public health concern due to its high pathogenicity in poultry and high case fatality rates in humans. The recently emerged H7N9 is a growing pandemic risk due to its sustained high rates of human infections, and recently acquired high pathogenicity in poultry. Here, we used Bayesian phylogeography on 265 H5N1 and 371 H7N9 haemagglutinin sequences isolated from humans, animals and the environment, to identify and compare migration patterns and factors predictive of H5N1 and H7N9 diffusion rates in China. H7N9 diffusion dynamics and predictor contributions differ from H5N1. Key determinants of spatial diffusion included: proximity between locations (for H5N1 and H7N9), and lower rural population densities (H5N1 only). For H7N9, additional predictors included low avian influenza vaccination rates, low percentage of nature reserves and high humidity levels. For both H5N1 and H7N9, we found viral migration rates from Guangdong to Guangxi and Guangdong to Hunan were highly supported transmission routes (Bayes Factor > 30). We show fundamental differences in wide-scale transmission dynamics between H5N1 and H7N9. Importantly, this indicates that avian influenza initiatives designed to control H5N1 may not be sufficient for controlling the H7N9 epidemic. We suggest control and prevention activities to specifically target poultry transportation networks between Central, Pan-Pearl River Delta and South-West regions.
  • Phylogeography of H5N1 avian influenza virus in Indonesia
    E. N. Njoto, M. Scotch, C. M. Bui, D. C. Adam, A. A. Chughtai, C. R. MacIntyre
    Transboundary and Emerging Diseases, 2018

RECENT SCHOLAR PUBLICATIONS

  • Edukasi SADARI dan Pendampingan SADANIS–USG untuk Meningkatkan Kesadaran Deteksi Dini Kanker Payudara pada Wanita Usia≥ 40 Tahun di Komunitas
    E Furaidah, MN Haykal, GFA Putra, IWH Wilopo, FN Fitriani, RD Indriani, ...
    Sewagati 10 (1) , 2026
    2026
  • Mapping the Landscape of Palliative Care in Indonesia: A Scoping Review of Availability, Accessibility, and Quality
    RFC Koh, JF Pardosi, EN Njoto
    Journal of Health Science and Medical Research 44 (2), 20251250 , 2026
    2026
  • Determinants of subclinical leprosy among household contacts in Indonesia: serological and socio-demographic factors
    K Khariri, S Sunarno, NSD Panjaitan, P Yuliandari, S Handayani, ...
    PeerJ 14, e20631 , 2026
    2026
    Citations: 2
  • Peningkatan Literasi Kesehatan Reproduksi Masyarakat Melalui Seminar Awam Kanker Serviks dan Prostat di Institut Teknologi Sepuluh Nopember
    A Ridhoi, MRN Ramadani, EN Njoto, D Arifianto, Y Pamungkas, ...
    Sewagati 9 (6), 1657-1668 , 2025
    2025
  • Peningkatan Literasi Kesehatan Masyarakat tentang Nyeri Punggung Bawah Melalui Edukasi Interaktif dengan Manekin Tiga Dimensi Tulang Belakang Abnormal
    G Fardhani, RD Indriani, DS Eljatin, EN Njoto, AN Fadhlina, ...
    Sewagati 9 (6), 1620-1636 , 2025
    2025
  • Application of 3D Printing Technology for Medical Purposes: A State of the Art
    Y Pamungkas, D Kuswanto, DS Eljatin, EN Njoto
    Journal of Medicine and Health Technology 2 (1) , 2025
    2025
  • Risk factors of nonsteroidal anti-inflammatory drug-exacerbated respiratory disease: A systematic review and meta-analysis of observational studies
    EN Njoto, MF Chan, AAB Wirayuda, GFA Putra, DW Sari, E Indriastuti, ...
    Oman Medical Journal 40 (2), e728 , 2025
    2025
    Citations: 2
  • Peningkatan Kewaspadaan Resistensi Antibiotik pada Kader Surabaya Hebat (KSH) di Kecamatan Sukolilo
    DS Eljatin, MN Haykal, I Susilo, AD Wibawa, S Fadli, EN Njoto, R Karimah, ...
    Sewagati 8 (6), 2379-2388 , 2024
    2024
  • A bayesian network meta-analysis of three and six-month weight-loss outcomes among endoscopic intragastric balloon
    EN Njoto, C Aryanti, E Syarifuddin
    JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY 39, 166-167 , 2024
    2024
  • Optimal positions in Thoracoscopic Esophagectomy: a network meta-analysis of intraoperative and postoperative outcomes
    C Aryanti, EN Njoto, M Mulyawan
    JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY 39, 29-29 , 2024
    2024
  • Determining Positive-Negative Emotions in Male and Female Based on EEG Signals using Machine Learning Algorithms
    Y Pamungkas, EN Njoto
    2024 11th International Conference on Electrical Engineering, Computer … , 2024
    2024
  • Implementation of EfficientNet-B0 architecture in malaria detection system based on patient red blood cell (RBC) images
    Y Pamungkas, EN Njoto, DS Eljatin, IF Hardyanti, T Umamah, KJ Putri
    2024 International Conference on Information Technology Research and … , 2024
    2024
    Citations: 5
  • Identification of Potential Drug-Drug Interactions Using EMR Text-Mining on Atherosclerotic Heart Disease Patients
    M Fuadi, AD Wibawa, EN Njoto, GA Buntoro
    2024 IEEE International Conference on Industry 4.0, Artificial Intelligence … , 2024
    2024
  • Effectiveness of CNN architectures and SMOTE to overcome imbalanced x-ray data in childhood pneumonia detection
    Y Pamungkas, MRN Ramadani, EN Njoto
    Journal of Robotics and Control (JRC) 5 (3), 775-785 , 2024
    2024
    Citations: 13
  • Gerakan 1000 Sertifikat Halal untuk Mendukung Kewajiban Sertifikat Halal 2024. Sewagati, 8 (3), Article 3
    NA Rakhmawati, S Gunawan, R Indraswari, I Ulfin, L Rahadiantino, ...
    2024
    Citations: 4
  • Analisis Prediktif Mutasi EGFR pada Adenokarsinoma Paru Menggunakan Pendekatan Pembelajaran Mesin
    EN Njoto, Y Pamungkas, AIW Putri, M Haykal, DS Eljatin, EM Djaputra
    Jurnal Penyakit Dalam Indonesia 11 (4), 6 , 2024
    2024
    Citations: 1
  • Risk Factors of NSAID-exacerbated Respiratory Disease: A Systematic Review and Meta-analysis of Observational Study
    EN Njoto, MF Chan, AAB Wirayuda, GFA Putra, DW Sari, E Indriastuti, ...
    OMAN MEDICAL JOURNAL , 2024
    2024
  • Low subcutaneous fat as a risk factor for sarcopenia among elderly women in Bali, Indonesia: a community-based age-matched case-control study
    EN Njoto, I Aryana, RAT Kuswadhani
    University of Malta. Medical School , 2024
    2024
  • MO7-1 A Bayesian network meta-analysis comparing biliary stent types’ outcomes in unresectable malignant biliary obstruction
    C Aryanti, EN Njoto, IM Mahayasa, IM Mulyawan
    Annals of Oncology 34, S1399 , 2023
    2023
  • P1. 22-12 Nomogram Prediction for the Detection of Epidermal Growth Factor Receptor Mutation in Lung Adenocarcinoma Patients in Indonesia
    EN Njoto, I Kusumawardani, IBN Rai
    Journal of Thoracic Oncology 18 (11), S249-S250 , 2023
    2023

MOST CITED SCHOLAR PUBLICATIONS

  • Sarkopenia pada Lanjut Usia: Patogenesis, Diagnosis dan Tata Laksana
    EN Njoto, I Aryana
    Jurnal Penyakit Dalam Indonesia 10 (3), 164-173 , 2023
    2023
    Citations: 28
  • Mengenali Depresi pada Usia Lanjut Penggunaan Geriatric Depression Scale (GDS) untuk Menunjang Diagnosis
    EN Njoto
    Cermin Dunia Kedokteran 217 41 (6) , 2014
    2014
    Citations: 27
  • Characterising routes of H5N1 and H7N9 spread in China using Bayesian phylogeographical analysis
    CM Bui, DC Adam, E Njoto, M Scotch, CR MacIntyre
    Emerging microbes & infections 7 (1), 1-8 , 2018
    2018
    Citations: 24
  • Effectiveness of CNN architectures and SMOTE to overcome imbalanced x-ray data in childhood pneumonia detection
    Y Pamungkas, MRN Ramadani, EN Njoto
    Journal of Robotics and Control (JRC) 5 (3), 775-785 , 2024
    2024
    Citations: 13
  • Phylogeography of H5N1 avian influenza virus in Indonesia
    EN Njoto, M Scotch, C Bui, D Adam, A Chughtai, CR MacIntyre
    Transboundary and Emerging Diseases , 2018
    2018
    Citations: 11
  • Target Tekanan Darah pada Diabetes Melitus
    EN Njoto
    Cermin Dunia Kedokteran 222 41 (11) , 2014
    2014
    Citations: 7
  • Implementation of EfficientNet-B0 architecture in malaria detection system based on patient red blood cell (RBC) images
    Y Pamungkas, EN Njoto, DS Eljatin, IF Hardyanti, T Umamah, KJ Putri
    2024 International Conference on Information Technology Research and … , 2024
    2024
    Citations: 5
  • Gerakan 1000 Sertifikat Halal untuk Mendukung Kewajiban Sertifikat Halal 2024. Sewagati, 8 (3), Article 3
    NA Rakhmawati, S Gunawan, R Indraswari, I Ulfin, L Rahadiantino, ...
    2024
    Citations: 4
  • Jatim Bebas Pasung: An integrated programme to tackle the physical restraint of people with a mental health condition in East Java Province, Indonesia
    EN Njoto, JF Pardosi
    Development Bulletin , 2018
    2018
    Citations: 3
  • Determinants of subclinical leprosy among household contacts in Indonesia: serological and socio-demographic factors
    K Khariri, S Sunarno, NSD Panjaitan, P Yuliandari, S Handayani, ...
    PeerJ 14, e20631 , 2026
    2026
    Citations: 2
  • Risk factors of nonsteroidal anti-inflammatory drug-exacerbated respiratory disease: A systematic review and meta-analysis of observational studies
    EN Njoto, MF Chan, AAB Wirayuda, GFA Putra, DW Sari, E Indriastuti, ...
    Oman Medical Journal 40 (2), e728 , 2025
    2025
    Citations: 2
  • Predicting EGFR mutation in lung adenocarcinoma: development and validation of the EGFR mutation predictive score (EMPS) in Bali, Indonesia
    EN Njoto, IAJD Kusumawardani, IBN Rai
    Asian Pacific journal of cancer prevention: APJCP 24 (8), 2903 , 2023
    2023
    Citations: 2
  • Peranan Candida Score untuk Deteksi Infeksi Fungal Invasif di Ruang Intensif
    EN Njoto
    Cermin Dunia Kedokteran 212 41 (1) , 2014
    2014
    Citations: 2
  • Analisis Prediktif Mutasi EGFR pada Adenokarsinoma Paru Menggunakan Pendekatan Pembelajaran Mesin
    EN Njoto, Y Pamungkas, AIW Putri, M Haykal, DS Eljatin, EM Djaputra
    Jurnal Penyakit Dalam Indonesia 11 (4), 6 , 2024
    2024
    Citations: 1
  • Edukasi SADARI dan Pendampingan SADANIS–USG untuk Meningkatkan Kesadaran Deteksi Dini Kanker Payudara pada Wanita Usia≥ 40 Tahun di Komunitas
    E Furaidah, MN Haykal, GFA Putra, IWH Wilopo, FN Fitriani, RD Indriani, ...
    Sewagati 10 (1) , 2026
    2026
  • Mapping the Landscape of Palliative Care in Indonesia: A Scoping Review of Availability, Accessibility, and Quality
    RFC Koh, JF Pardosi, EN Njoto
    Journal of Health Science and Medical Research 44 (2), 20251250 , 2026
    2026
  • Peningkatan Literasi Kesehatan Reproduksi Masyarakat Melalui Seminar Awam Kanker Serviks dan Prostat di Institut Teknologi Sepuluh Nopember
    A Ridhoi, MRN Ramadani, EN Njoto, D Arifianto, Y Pamungkas, ...
    Sewagati 9 (6), 1657-1668 , 2025
    2025
  • Peningkatan Literasi Kesehatan Masyarakat tentang Nyeri Punggung Bawah Melalui Edukasi Interaktif dengan Manekin Tiga Dimensi Tulang Belakang Abnormal
    G Fardhani, RD Indriani, DS Eljatin, EN Njoto, AN Fadhlina, ...
    Sewagati 9 (6), 1620-1636 , 2025
    2025
  • Application of 3D Printing Technology for Medical Purposes: A State of the Art
    Y Pamungkas, D Kuswanto, DS Eljatin, EN Njoto
    Journal of Medicine and Health Technology 2 (1) , 2025
    2025
  • Peningkatan Kewaspadaan Resistensi Antibiotik pada Kader Surabaya Hebat (KSH) di Kecamatan Sukolilo
    DS Eljatin, MN Haykal, I Susilo, AD Wibawa, S Fadli, EN Njoto, R Karimah, ...
    Sewagati 8 (6), 2379-2388 , 2024
    2024