Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Kedokteran Meditek Malahayati International Journal of Nursing and Health Science
Momole, Ansye Grace Nancy
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Nursing Public Health

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Prediksi Gangguan Kognitif Ringan Menggunakan Pencitraan Resonansi Magnetik dan Deep Learning: Sebuah Studi Meta-Analisis Setiawan, Budi; Wariki, Windy Mariane Virenia; Warouw, Finny; Momole, Ansye Grace Nancy; Tumewah, Rizal; Pertiwi, Junita Maja
Jurnal Kedokteran Meditek Vol 31 No 2 (2025): MARCH
Publisher : Fakultas Kedokteran Universitas Kristen Krida Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36452/jkdoktmeditek.v31i2.3463

Abstract

Introduction: Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline that does not interfere with daily activities but increases the risk of progressing to Alzheimer's Dementia (AD). Early detection of MCI progression to AD is crucial for early intervention. Purpose: The purpose of this meta-analysis to evaluate the performance of Convolutional Neural Networks (CNNs), an artificial intelligence used to analyze complex data such as images, in predicting the conversion of MCI to AD using MRI data. Methods: A meta-analysis was conducted following PRISMA guidelines, utilizing articles from PubMed and Wiley Online Library. Inclusion criteria focused on studies that used CNN in conjunction with MRI to diagnose MCI. A total of 39 articles with 40 comparative studies were analyzed. Results: The CNN showed an average accuracy of 0.7910 (p < 0.0001), sensitivity of 0.7698, specificity of 0.8467, and an Area Under the Curve (AUC) of 0.8063. High heterogeneity (I² = 90.90%) indicated significant variation across studies. Sub meta-analysis revealed consistent performance despite the heterogeneity. Conclusion: CNN is potentially useful for predicting the progression of MCI to AD. Further research is needed to address heterogeneity, improve algorithms, expand datasets, and include more diverse populations.
Effectiveness of non-invasive transcranial magnetic stimulation therapy as a therapy for post-stroke visuospatial impairment: A meta-analysis Lapian, Albertus Theo; Warouw, Finny; Momole, Ansye Grace Nancy; Pertiwi, Junita Maja; Tangkudung, Gilbert
Malahayati International Journal of Nursing and Health Science Vol. 8 No. 2 (2025): Volume 8 Number 2
Publisher : Program Studi Ilmu Keperawatan-fakultas Ilmu Kesehatan Universitas Malahayati

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33024/minh.v8i2.552

Abstract

Background: Visuospatial disorders refer to deficits in attention, exploration, and interaction with the contralateral side of space that cannot be attributed to primary sensory or motor dysfunction. These disorders are usually caused by lesions in the right hemisphere due to cerebral circulation disorders, such as stroke. Transcranial Magnetic Stimulation (TMS) has emerged as a noninvasive treatment option for addressing visuospatial deficits. Purpose: To evaluate the effectiveness of TMS as a therapy for visuospatial disorders in post-stroke patients. Method: This study was conducted using randomized controlled trials (RCTs) comparing TMS with sham treatment for post-stroke visuospatial impairment identified through searches in Google Scholar, PubMed/Medline, Clinical Key, Wiley Online, Science Direct, ResearchGate, and Neurona. A meta-analysis was conducted to assess the efficacy of TMS therapy for improving visuospatial deficits in post-stroke patients. Results: A total of 189 studies on TMS were identified with four homogeneous articles finally included in the meta-analysis. The analysis combined visuospatial assessments using the Motor-Free Visual Perception Test (MVPT), ​​Star Cancellation Test (SCT), Albert Test (AT), and Line Bisection Test (LBT). The meta-analysis revealed significant findings for the MVPT, with a weighted mean difference (WMD) of 2.43 (95% CI: 1.86 to 3.01, p < 0.001). For LBT, WMD was 2.69 (95% CI: 2.04 to 3.34, p = 0.020). Conclusion: The improvements in visuospatial function observed in participants undergoing TMS suggest that TMS may serve as a potential therapeutic option for post-stroke patients with visuospatial impairment.
Co-Authors Budi Setiawan Lapian, Albertus Theo Pertiwi, Junita Maja Rizal Tumewah Tangkudung, Gilbert Wariki, Windy M. V. Warouw, Finny