Article Per Year (5 Year)
p-Index From 2020 - 2025
0.61
P-Index
This Author published in this journals
All Journal Sriwijaya Journal of Obstetrics and Gynecology Sriwijaya Journal of Neurology Sriwijaya Journal of Otorhinolaryngology
Louisa Istarini
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Dentistry Health Professions Medicine & Pharmacology Neuroscience Nursing Public Health

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Artificial Intelligence for Early Detection of Motor Neuron Disease Using Gait Analysis and Speech Patterns in Pekanbaru, Indonesia Sari Sulistyoningsih; Louisa Istarini; Dedi Sucipto; Serena Jackson; Agnes Mariska; Linda Purnama; Imanuel Simbolon
Sriwijaya Journal of Neurology Vol. 1 No. 2 (2023): Sriwijaya Journal of Neurology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjn.v1i1.28

Abstract

Introduction: Motor neuron disease (MND) is a devastating neurodegenerative disorder characterized by progressive muscle weakness, atrophy, and ultimately, paralysis. This study investigated the potential of artificial intelligence (AI) to detect MND in its early stages using gait analysis and speech pattern recognition in a population in Pekanbaru, Indonesia. Methods: A cross-sectional study was conducted at the Neurology Department of a tertiary referral hospital in Pekanbaru, Indonesia. A total of 150 participants aged 40-75 years were recruited and categorized into three groups. Gait analysis was performed using wearable sensors to collect data on stride length, cadence, swing time, stance time, and gait variability. Machine learning algorithms, including support vector machines (SVM), random forest (RF), and deep learning models like convolutional neural networks (CNN), were trained on the combined gait and speech data to classify participants into the three groups. Results: Significant differences were observed in gait parameters between the MND group and the other two groups. Individuals with MND exhibited shorter stride length (p<0.001), slower cadence (p<0.001), increased swing time variability (p=0.002), and reduced stance time (p=0.003). Speech analysis revealed distinct patterns in the MND group, including reduced speech rate (p<0.001), increased pause duration (p=0.004), and decreased vocal intensity (p=0.001). The AI models, particularly the CNN model, demonstrated high accuracy in differentiating individuals with MND from healthy controls and those with other neurological conditions. The CNN model achieved an accuracy of 94.7%, sensitivity of 92%, specificity of 96%, and an area under the receiver operating characteristic curve (AUC) of 0.98. Conclusion: AI-powered gait analysis and speech pattern recognition show promise as a non-invasive and cost-effective tool for the early detection of MND in Pekanbaru, Indonesia. This technology has the potential to improve diagnostic accuracy and facilitate timely intervention, ultimately enhancing the quality of life for individuals with MND.
The Impact of Gastroesophageal Reflux Disease (GERD) on Pharyngeal Mucosal Changes: A Case-Control Study in Indonesia Dedi Sucipto; Nurul Hanifah; Vidhya Sathyakirti; Louisa Istarini; Syaifudin Syaifudin
Sriwijaya Journal of Otorhinolaryngology Vol. 2 No. 1 (2024): Sriwijaya Journal of Otorhinolaryngology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjorl.v1i2.94

Abstract

Introduction: Gastroesophageal reflux disease (GERD) is a prevalent digestive disorder with potential extra-esophageal manifestations, including laryngopharyngeal reflux (LPR). LPR can lead to various pharyngeal mucosal changes, impacting voice quality and overall well-being. This study aimed to investigate the association between GERD and pharyngeal mucosal changes in a population in Indonesia. Methods: A case-control study was conducted at a tertiary hospital in Indonesia, involving 100 participants diagnosed with GERD (cases) and 100 participants without GERD (controls). All participants underwent a comprehensive ear, nose, and throat (ENT) examination, including flexible nasopharyngoscopy, to assess pharyngeal mucosal changes. The Reflux Symptom Index (RSI) questionnaire was used to evaluate the severity of reflux symptoms. Data were analyzed using SPSS software, employing chi-square and logistic regression analyses to determine the association between GERD and pharyngeal mucosal changes. Results: The study found a significantly higher prevalence of pharyngeal mucosal changes in the GERD group compared to the control group (78% vs. 22%, p<0.001). Erythema, edema, and posterior pharyngeal wall cobblestoning were the most common findings in GERD patients. The severity of reflux symptoms, as measured by the RSI, was positively correlated with the presence and severity of pharyngeal mucosal changes. Conclusion: GERD is significantly associated with pharyngeal mucosal changes in the Indonesian population studied. These findings underscore the importance of recognizing and managing LPR in patients with GERD to prevent potential complications and improve quality of life.
The Impact of the COVID-19 Pandemic on Maternal Mortality Rates in Indonesia: A Retrospective Cohort Study Imanuel Simbolon; Louisa Istarini; Desiree Montesinos; Habiburrahman Said; Yi-Fen Huang
Sriwijaya Journal of Obstetrics and Gynecology Vol. 1 No. 2 (2023): Sriwijaya Journal of Obstetrics and Gynecology
Publisher : Phlox Institute: Indonesian Medical Research Organization

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59345/sjog.v1i1.21

Abstract

Introduction: The COVID-19 pandemic has presented unprecedented challenges to healthcare systems worldwide. Early reports have indicated an increase in maternal mortality rates (MMR) in various settings. This study aims to investigate the impact of the COVID-19 pandemic on MMR in Indonesia, a populous country in Southeast Asia with a high MMR. Methods: A retrospective cohort study was conducted using data from the Indonesian Ministry of Health's Maternal Mortality Surveillance System (MMSS). The study population included all pregnant women who delivered in Indonesia between January 1st, 2018, and December 31st, 2022. Women were categorized into two groups: those who delivered before the pandemic (January 1st, 2018, to February 29th, 2020) and those who delivered during the pandemic (March 1st, 2020, to December 31st 2022). The primary outcome was maternal death. Multivariable logistic regression was used to assess the association between the pandemic period and maternal mortality, adjusting for potential confounders. Results: A total of 1,250,480 deliveries were included in the study. The MMR during the pandemic period was 155 per 100,000 live births, compared to 118 per 100,000 live births pre-pandemic. After adjusting for confounders such as maternal age, socioeconomic status, and access to healthcare, the pandemic period was independently associated with an increased risk of maternal mortality (adjusted odds ratio [aOR] = 1.32; 95% confidence interval [CI], 1.25-1.39). Conclusion: The COVID-19 pandemic was associated with a significant increase in MMR in Indonesia. This highlights the need for continued efforts to strengthen maternal healthcare systems and ensure access to quality care, especially during public health emergencies.
Co-Authors Agnes Mariska Dedi Sucipto Desiree Montesinos Habiburrahman Said Imanuel Simbolon Linda Purnama Nurul Hanifah Sari Sulistyoningsih Serena Jackson Syaifudin Vidhya Sathyakirti Yi-Fen Huang