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Teuku Rizky Noviandy
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INDONESIA
Indonesian Journal of Case Reports
Published by PT. Heca Sentra Analitika
ISSN : -     EISSN : 30253578     DOI : https://doi.org/10.60084/ijcr
Core Subject : Health, Science,
Health Professions Medicine & Pharmacology Neuroscience Public Health
The journal aims to present challenging and stimulating cases in an educational format, enabling readers to engage as if they are actively collaborating with caring clinician scientists in patient management. Topics of this journal includes, but not limited to Exploration of new diseases and their manifestations, Investigation of new presentations or variations of known diseases, Identification of new associations between diseases or symptoms, Examination of new diagnostic techniques for skin, hair, and nail conditions, Evaluation of new treatment methods, including adverse events and procedural techniques, Reporting of unreported or unusual side effects or adverse interactions involving medications, Analysis of unexpected or unusual disease presentations, Discussion of new associations or variations in disease processes, Presentation, diagnosis, and management of new and emerging diseases, Reporting of unexpected events in patient observation or treatment, Discovery of findings that contribute to the understanding of disease pathogenesis or adverse effects
Arjuna Subject : Kedokteran - Kedokteran (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 1 (2024): June 2024" : 5 Documents clear
Combination Treatment of Splinting with Wire Composite and Artificial Tooth Pontic for Improved Aesthetics: A Case Report Ersa, Savana; Amalia, Martina
Indonesian Journal of Case Reports Vol. 2 No. 1 (2024): June 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijcr.v2i1.142

Abstract

Advanced bone loss in patients with periodontitis often leads to increased tooth mobility, sometimes resulting in tooth loss. The mobility of teeth necessitates splinting to optimize periodontal treatment outcomes in terms of aesthetics and periodontal health. This case report presents a novel approach using an artificial tooth pontic as a periodontal splint, utilizing wire stabilization to prevent severe tooth mobility and enhance esthetics. A 37-year-old male with aggressive periodontitis (Stage III, Grade C) exhibited extensive periodontal destruction, particularly in the upper and lower anterior regions. Pathological migration was evident following the loss of teeth 31 and 41, with additional anterior teeth in the lower jaw showing mobility and trauma from occlusion, notably tooth 33. The patient underwent nonsurgical periodontal therapy, including scaling, subgingival debridement, occlusal adjustment, and splinting. Stabilization was achieved by applying a wire splint from teeth 34 to 43, incorporating an artificial tooth pontic. Subsequent evaluations revealed improvements in clinical parameters such as probing pocket depth, tooth mobility, and bleeding on probing during supportive periodontal therapy visits. The splint remained stable, and the patient expressed satisfaction with their appearance remaining unaffected. This case demonstrates that severe tooth mobility can be effectively stabilized using a composite wire splint and an artificial tooth pontic, enhancing the patient's esthetic outcomes.
Explainable Artificial Intelligence in Medical Imaging: A Case Study on Enhancing Lung Cancer Detection through CT Images Noviandy, Teuku Rizky; Maulana, Aga; Zulfikar, Teuku; Rusyana, Asep; Enitan, Seyi Samson; Idroes, Rinaldi
Indonesian Journal of Case Reports Vol. 2 No. 1 (2024): June 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijcr.v2i1.150

Abstract

This study tackles the pressing challenge of lung cancer detection, the foremost cause of cancer-related mortality worldwide, hindered by late detection and diagnostic limitations. Aiming to improve early detection rates and diagnostic reliability, we propose an approach integrating Deep Convolutional Neural Networks (DCNN) with Explainable Artificial Intelligence (XAI) techniques, specifically focusing on the Residual Network (ResNet) architecture and Gradient-weighted Class Activation Mapping (Grad-CAM). Utilizing a dataset of 1,000 CT scans, categorized into normal, non-cancerous, and three types of lung cancer images, we adapted the ResNet50 model through transfer learning and fine-tuning for enhanced specificity in lung cancer subtype detection. Our methodology demonstrated the modified ResNet50 model's effectiveness, significantly outperforming the original architecture in accuracy (91.11%), precision (91.66%), sensitivity (91.11%), specificity (96.63%), and F1-score (91.10%). The inclusion of Grad-CAM provided insightful visual explanations for the model's predictions, fostering transparency and trust in computer-assisted diagnostics. The study highlights the potential of combining DCNN with XAI to advance lung cancer detection, suggesting future research should expand dataset diversity and explore multimodal data integration for broader applicability and improved diagnostic capabilities.
Unilateral Congenital Cataracts: Best Practices and Case Studies for Effective Management Imelda, Eva; Sari, Cut Refida; Toshniwal, Navneet Shamsundar
Indonesian Journal of Case Reports Vol. 2 No. 1 (2024): June 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijcr.v2i1.175

Abstract

Congenital cataract is a clouding of the eye lens in children, which contributes to blindness in 5% to 20% of children throughout the world. Cataracts can occur unilaterally or bilaterally and can vary in size, morphology, and degree of opacification. This report aims to comprehensively diagnose and treat unilateral cataracts and provide optical rehabilitation. A 3-month-old baby boy was brought by his family with complaints of a white spot on the right eye, which the family had known about since the patient was one month old. The patient was diagnosed with a congenital cataract and underwent surgery, which included aspiration irrigation, primary posterior capsulotomy, and anterior vitrectomy under general anesthesia. The use of glasses is chosen as optical rehabilitation. Collaborative management is also done with pediatric specialists, ENT, and pediatric cardiology. It was concluded that congenital cataract management aims to prevent amblyopia by clearing it as soon as possible (Clear Visual Axis) and optical rehabilitation (Clear Retinal Image) to improve the vision prognosis.
Clinical Insights and Diagnostic Dilemmas: Two Cases of Livedoid Vasculitis Earlia, Nanda; Budini, Sulamsih Sri; Lestari, Wahyu; Handriani, Risna; Ismida, Fitri Dewi; Pradistha, Aldilla; Dinillah, Teuku Muhammad Muizzy; Vemulen, Dara Avinda; Athira, Athira
Indonesian Journal of Case Reports Vol. 2 No. 1 (2024): June 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijcr.v2i1.183

Abstract

Livedoid Vasculitis (LV) is a thrombo-occlusive vasculopathy involving dermal vessels, especially in the lower extremities. Clinical symptoms of LV are chronic, recurrent, scarring, and painful purpuric ulcers. Diagnosing and providing therapy for LV is a challenge because there are no standard guidelines. We present clinical insights and diagnostic approaches on two cases of LV to improve early diagnosis and prevent misdiagnosis, which were confirmed based on history, dermatological examination, and skin biopsy. In the first case, it was a woman, 23 years old, who came with complaints of a blackish-red rash appearing on both legs. There were scars on several parts of the patient's legs, which felt painful, and the legs looked swollen. On histopathological examination, fibrin deposition in the vessel walls, endothelial proliferation, and intraluminal hyaline thrombin were found. In the second case, it was a man, 19 years old, who came with complaints of pain when walking accompanied by wounds on both lower legs. On histopathological examination, fibrin deposition in the vessel walls, endothelial proliferation, and intraluminal hyaline thrombin were found. The conclusion from the histopathology results was LV. After receiving therapy, both cases showed improvement: swelling in the legs was reduced, red and black rashes began to disappear, ulcers improved, pain decreased, and scars became blurred. These two cases provide examples of success in diagnosing LV. Being able to diagnose LV early and correctly is very important so that adequate therapy can be given and good outcomes can be achieved.
Interpretable Machine Learning for Chronic Kidney Disease Diagnosis: A Gaussian Processes Approach Noviandy, Teuku Rizky; Idroes, Ghifari Maulana; Syukri, Maimun; Idroes, Rinaldi
Indonesian Journal of Case Reports Vol. 2 No. 1 (2024): June 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijcr.v2i1.204

Abstract

Chronic Kidney Disease (CKD) is a global health issue impacting over 800 million people, characterized by a gradual loss of kidney function leading to severe complications. Traditional diagnostic methods, relying on laboratory tests and clinical assessments, have limitations in sensitivity and are prone to human error, particularly in the early stages of CKD. Recent advances in machine learning (ML) offer promising tools for disease diagnosis, but a lack of interpretability often hinders their adoption in clinical practice. Gaussian Processes (GP) provide a flexible ML model capable of delivering predictions and uncertainty estimates, essential for high-stakes medical applications. However, the integration of GP with interpretable methods remains underexplored. We developed an interpretable CKD classification model to address this knowledge gap by combining GP with Shapley Additive Explanations (SHAP). We assessed the model's performance using three GP kernels (Radial Basis Function, Matern, and Rational Quadratic). The results show that the Rational Quadratic kernel outperforms the other kernels, achieving an accuracy of 98.75%, precision of 100%, sensitivity of 97.87%, specificity of 100%, and an F1-score of 98.51%. SHAP values indicate that haemoglobin and specific gravity are the most influential features. The results demonstrate that the Rational Quadratic kernel enhances predictive accuracy and provides robust uncertainty estimates and interpretable explanations. This combination of accuracy and interpretability supports clinicians in making informed decisions and improving patient management and outcomes in CKD. Our study connects advanced ML techniques with practical medical applications, leading to more effective and reliable ML-driven healthcare solutions.

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