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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Global Medical and Health Communication EMITTER International Journal of Engineering Technology MNJ (Malang Neurology Journal) Molecular and Cellular Biomedical Sciences (MCBS) Knowledge Engineering and Data Science Journal Of Vocational Health Studies Jurnal Pengabdian Pada Masyarakat JUXTA: Jurnal Ilmiah Mahasiswa Kedokteran Universitas Airlangga Jurnal Pengabdian Masyarakat dalam Kesehatan Indian Journal of Forensic Medicine & Toxicology Poltekita: Jurnal Pengabdian Masyarakat Jurnal Radiografer Indonesia AKSONA International Journal of Radiology and Imaging
Sensusiati, Anggraini Dwi
Department Of Radiology, Faculty Of Medicine, Universitas Airlangga/Universitas Airlangga Hospital, Surabaya, Indonesia.
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Education Engineering Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Nursing Public Health Other

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NEUROLOGIC COMPLICATION IN LUNG ADENOCARCINOMA EFGR MUTATION WITH A CONSOLIDATION-TO-TUMOR-RATIO (CTR) >75% Prasetyo, Firman Adi; Sensusiati, Anggraini Dwi
International Journal of Radiology and Imaging Vol. 2 No. 02 (2023): International Journal of Radiology and Imaging
Publisher : Department of Radiology, Medical Faculty, University of Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776//ub.ijri.2023.002.02.4

Abstract

Lung adenocarcinoma (LAC) accounts for a large proportion of lung cancer subtypes and causes various neurologic complications. This calls for extensive use of CT scans for detecting lung cancer which contains ground glass opacity (GGO). A Consolidation-to-tumor-ratio (CTR) >75% has a worse prognosis in LAC. A male 50-years-old came with paraplegia, complaining suddenly that his legs could not be moved. The patient performed a spine MRI with the result indicating a spinal metastatic process. Furthermore, the Chest X-ray only showed consolidation in the right paracardial area but the chest CT confirmed as lung mass followed by histopathology examination result of LAC with EFGR mutation. After three months, the patient also had multiple cerebral infarcts. We reported one case of LAC EFGR mutation with a CTR of 83%. higher CTR has more invasive adenocarcinomas and also correlated with immunosuppressive conditions compared with a low CTR. The patient was diagnosed lately after a complication of spinal compression. The other neurological complication is multiple cerebral infarcts. The pathogenesis of cancer-associated stroke has not been fully clarified. The pathophysiological mechanisms of these cerebrovascular complications are multifactorial. Other biological markers may also be of interest, including high levels of C-reactive protein (CRP), high levels of fibrinogen, decreased hemoglobin, and hypoalbuminemia. Retrospective studies on acute stroke detected significantly higher levels of fibrinogen and CRP in patients with cryptogenic stroke and occult malignancy. LAC with a CTR >75% is more invasive due to neurologic complications such as spinal metastases and stroke infarction. Keywords: Lung adenocarcinoma, CTR, Stroke, Metastase
Lite-FBCN: Lightweight Fast Bilinear Convolutional Network for Brain Disease Classification from MRI Image Rumala, Dewinda Julianensi; Rachmadi, Reza Fuad; Sensusiati, Anggraini Dwi; Purnama, I Ketut Eddy
EMITTER International Journal of Engineering Technology Vol 12 No 2 (2024)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24003/emitter.v12i2.853

Abstract

Achieving high accuracy with computational efficiency in brain disease classification from Magnetic Resonance Imaging (MRI) scans is challenging, particularly when both coarse and fine-grained distinctions are crucial. Current deep learning methods often struggle to balance accuracy with computational demands. We propose Lite-FBCN, a novel Lightweight Fast Bilinear Convolutional Network designed to address this issue. Unlike traditional dual-network bilinear models, Lite-FBCN utilizes a single-network architecture, significantly reducing computational load. Lite-FBCN leverages lightweight, pre-trained CNNs fine-tuned to extract relevant features and incorporates a channel reducer layer before bilinear pooling, minimizing feature map dimensionality and resulting in a compact bilinear vector. Extensive evaluations on cross-validation and hold-out data demonstrate that Lite-FBCN not only surpasses baseline CNNs but also outperforms existing bilinear models. Lite-FBCN with MobileNetV1 attains 98.10% accuracy in cross-validation and 69.37% on hold-out data (a 3% improvement over the baseline). UMAP visualizations further confirm its effectiveness in distinguishing closely related brain disease classes. Moreover, its optimal trade-off between performance and computational efficiency positions Lite-FBCN as a promising solution for enhancing diagnostic capabilities in resource-constrained and or real-time clinical environments.
Role of Chest CT Scan to Predict Malignancy on Mediastinal Mass Widyaningrum, Saraswati; Widyoningroem, Anita; Sensusiati, Anggraini Dwi; Kusumastuti, Etty Hary
Global Medical & Health Communication (GMHC) Vol 13, No 1 (2025)
Publisher : Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/gmhc.v13i1.14218

Abstract

Mediastinal mass is becoming a global health problem due to high mortality. The heterogeneous mediastinal components make the symptoms of mediastinal mass diverse. CT scans are still the imaging modality for examining mediastinal mass before surgery or other therapies. In this study, we evaluate whether a CT scan could predict the malignancy of mediastinal mass, which is expected to help establish a pre-surgical or pre-biopsy diagnosis. Sixty-two samples were taken consecutively from mediastinal mass patients who came to Dr. Soetomo General Academic Hospital to undergo a CT scan of the thorax with contrast and histopathology examination (core biopsy or open biopsy), which was carried out in the period from December 2019 to March 2024. The results of the CT scan imaging used in this study variable include mass location, mass shape, mass size, infiltration with surrounding organs, attenuation values before contrast administration, after contrast administration, and additional attenuation before and after contrast administration. The CT scan and histopathology results were compared, and multivariate analysis was performed to obtain predictor factors. The location of the mediastinal mass (anterior, medius, posterior), the solid heterogeny component, cystic, calcification, mass shape, organ infiltration, and contrast enhancement value could significantly predict the mediastinal mass's malignancy. If obtained simultaneously, the organ infiltration and contrast enhancement value >20 HU can indicate whether a mediastinal mass is malignant with a specificity of up to 100%.
Role of Chest CT Scan to Predict Malignancy on Mediastinal Mass Widyaningrum, Saraswati; Widyoningroem, Anita; Sensusiati, Anggraini Dwi; Kusumastuti, Etty Hary
Global Medical & Health Communication (GMHC) Vol 13, No 1 (2025)
Publisher : Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/gmhc.v13i1.14137

Abstract

Mediastinal mass is becoming a global health problem due to high mortality. The heterogeneous mediastinal components make the symptoms of mediastinal mass diverse. CT scans are still the imaging modality for examining mediastinal mass before surgery or other therapies. In this study, we evaluate whether a CT scan could predict the malignancy of mediastinal mass, which is expected to help establish a pre-surgical or pre-biopsy diagnosis. Sixty-two samples were taken consecutively from mediastinal mass patients who came to Dr. Soetomo General Academic Hospital to undergo a CT scan of the thorax with contrast and histopathology examination (core biopsy or open biopsy), which was carried out in the period from December 2019 to March 2024. The results of the CT scan imaging used in this study variable include mass location, mass shape, mass size, infiltration with surrounding organs, attenuation values before contrast administration, after contrast administration, and additional attenuation before and after contrast administration. The CT scan and histopathology results were compared, and multivariate analysis was performed to obtain predictor factors. The location of the mediastinal mass (anterior, medius, posterior), the solid heterogeny component, cystic, calcification, mass shape, organ infiltration, and contrast enhancement value could significantly predict the mediastinal mass's malignancy. If obtained simultaneously, the organ infiltration and contrast enhancement value >20 HU can indicate whether a mediastinal mass is malignant with a specificity of up to 100%.
EMPOWERING COMMUNITIES IN STROKE AWARENESS AND PREVENTION THROUGH A PUBLIC HEALTH EDUCATION WEBINAR INITIATIVE Sensusiati, Anggraini Dwi; Setyowatie, Sita
Jurnal Pengabdian Masyarakat Dalam Kesehatan Vol. 7 No. 2 (2025): OCTOBER 2025
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jpmk.v7i2.76994

Abstract

Introduction: Stroke remains a major public health issue in Indonesia, with increasing prevalence and significant impacts on morbidity and mortality. This health education intervention, implemented through an interactive public health education webinar on stroke awareness and prevention, aimed to empower the community by improving their knowledge and awareness of stroke symptoms, risk factors, and prevention strategies through an interactive online health education webinar. Methods: This activity was conducted as a public webinar on June 13, 2025 via Zoom. A total of 98 participants who completed both the pre-test and post-test included in the analysis.  The participants consisted of community members, health caders, and university students from various regions in Indonesia. The educational materials included multimedia content such as short videos focused on stroke prevention, health promotion, and rehabilitation with sessions led by specialist in radiology and neurology.  Quantitative data were analyzed using descriptive statistics to summarize demographic and knowledge-level distributions, and a paired sample t-test to examine differences in mean knowledge scores between pre-test and post-test. Results: A total of 98 participants, the majority female (74.49%) and aged 19–29 years (60.30%), completed both assessments and were included in the analysis. Mean knowledge scores increased from 84.15 ± 6.43 (pre-test) to 95.16 ± 4.03 (post-test), with a paired t-test showing a significant improvement (t(97) = –25.211, p < 0.001). Before the webinar, 14.29% had poor knowledge and 74.49% had good knowledge; post-webinar, poor knowledge dropped to 2.04% while good knowledge rose to 88.78%. Conclusion: Digital educational platforms can serve as scalable and sustainable models for community health promotion, particularly in regions with limited access to in-person education. Future initiatives are encouraged to include follow-up community engagement and ongoing digital outreach to maintain knowledge retention and promote long-term behavioral change.
Segmentasi Citra X-Ray Dada Menggunakan Metode Modifikasi Deeplabv3+ Wahyuningrum, Rima Tri; Jannah, Maughfirotul; Satoto, Budi Dwi; Sari, Amillia Kartika; Sensusiati, Anggraini Dwi
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 3: Juni 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106754

Abstract

COVID-19 is a disease that affects the human respiratory system. The latest developments in September 2022 the number of confirmed cases of COVID-19 worldwide reached 608,328,548 with 6,501,469 patients who died. While in Indonesia confirmed COVID-19 reached 6,408,806 with 157,892 patients who died. Reserve Transcription Polymerase Chain Reaction (RT-PCR) is the most widely used tool. However, the latest RT-PCR test report shows that the RT-PCR test is inadequate. As an alternative, radiographic images such as chest x-rays and CT scans can help detect this. Radiographic images, especially x-rays, need processing to be able to make a diagnosis. Computer Aided Diagnosis (CAD) is a computer assisted diagnosis system that can be used as supporting information in making a diagnosis. To make it easier to make a diagnosis, we need a deep learning model that can help with this. DeepLabV3+ is a method that can carry out the segmentation process. DeepLabV3+ which is an extension of DeepLabV3 with the aim of improving the segmentation results. DeepLabV3+ uses a modified Xception as the backbone. In this study, 1,500 chest x-ray image data were used which were then divided into 80% for training data and 20% for testing data. There are 4 test scenarios in this study, namely with a learning rate of 0.01 without CLAHE, a learning rate of 0,01 and using CLAHE, a learning rate of 0,0001 without CLAHE, and a learning rate of 0,0001 using CLAHE. Of the 4 scenarios the learning rate scenario is 0,01 and using CLAHE gets the highest evaluation results using the Dice Similarity Coefficient (DSC) of 96.91%. 
Co-Authors Ahmad Suryawan Ali Mustofa Amillia Kartika Sari Anwar Ma&#039;aruf Arina Dery Puspitasari Asmaul Fauziyah Asra Al Fauzi Budi Dwi Satoto Budi Suprapti Cyuzuzo Callixte Dinda Chandra Yuliantari Dusabimana Jean Damascene Eka Nora Vitaloka Aprilia Putri Winthoko Eko Mulyanto Yuniarno Gijsbertus Jacob Verkerke Hanik Badriyah Hidayati,* Mohammad Hasan Machfoed,* Kuntoro,** Soetojo,*** Budi Santoso,**** Suroto,***** Budi Utomo****** I Ketut Eddy Purnama Imami, Nabilah Hasna Izzatul Fitriyah Jannah, Maughfirotul KUSUMASTUTI, ETTY HARY Machin, Abdulloh Maduma, Anggi Tiur Marcha Debby Saraswati Mardliyyah, Aisyatun Melisa Melisa Muhaimin Muhaimin Muhammad Amin Muhammad Faizi Muhammad Hamdan Muhammad Hamdan Muqmiroh, Lailatul Myrtati Dyah Artaria Nabilah Hasna Imami Ndayisaba Daniel Pramono Praptono, Soegardo Indra Prasetyo, Firman Adi Putra, Wahyu Zainur Putu Hendra Suputra Rachmadi, Reza Fuad Rima Tri Wahyuningrum Risalatul Latifah Rosyid, Alfian Nur Rumala, Dewinda Julianensi Rusmanto, Rusmanto Sari, Amilia Kartika Sita Setyowatie Soegardo Indra P Sri Andreani Utomo, Sri Andreani Tamara Nur Budiarti Tyas, Rana Ayuning Widyaningrum, Saraswati Widyoningroem, Anita Witjaksono, Budi Priyo Yoes Prijatna Dachlan