Publications by authors named "Dina N A Ningrum"

Neurological disorders pose significant challenges to healthcare systems worldwide [...

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  • The study aimed to create a deep learning model called Deep-KOA to predict the risk of knee osteoarthritis (KOA) within a year using three years' worth of electronic medical record (EMR) data.
  • Researchers analyzed data from two million patients, with 132,594 having KOA, and employed deep learning techniques, particularly CNN and ANN, to build a predictive model.
  • Deep-KOA demonstrated strong performance with an AUROC of 0.97 and highlighted significant features from various health conditions and medication use, while age and sex were less important predictors.
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  • The incidence of skin cancer, especially melanoma, is rising globally, with challenges in automated detection due to variability in skin lesions and a lack of standardized datasets.
  • Research shows deep convolutional neural networks (CNN) could aid diagnosis, but they require high computational power, which is often unavailable in low-resource healthcare settings.
  • This study developed an AI model that combines dermoscopic images with patient metadata using CNN and ANN, achieving higher accuracy (92.34%) for melanoma detection and enabling deployment on lower-end devices.
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Background: After two months of implementing a partial lockdown, the Indonesian government had announced the "New Normal" policy to prevent a further economic crash in the country. This policy received many critics, as Indonesia still experiencing a fluctuated number of infected cases. Understanding public perception through effective risk communication can assist the government in relaying an appropriate message to improve people's compliance and to avoid further disease spread.

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Because of the increasing adoption and use of technology in primary health care (PHC), public health informatics competencies (PHIC) are becoming essential for public health workers. Unfortunately, no studies have measured PHIC in resource-limited setting. This paper describes the process of developing and validating Public Health Informatics Competencies for Primary Health Care (PHIC4PHC), an instrument for measuring PHC workers' competencies in public health informatics.

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  • - The study investigates how sociodemographic factors relate to injury-related health outcomes worldwide, specifically analyzing disability-adjusted life years (DALYs) from injuries across 195 countries from 1990 to 2017.
  • - Findings show that while most injury causes display a trend of decreasing DALY rates with higher Socio-demographic Index (SDI), certain injuries like road injuries, interpersonal violence, and self-harm deviate from this trend, indicating complex underlying factors.
  • - The research highlights the importance of understanding these injury patterns to improve health strategies and intervention efforts at both national and global levels, especially since not all injuries follow the same developmental trajectory.
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Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2-to end preventable child deaths by 2030-we need consistently estimated data at the subnational level regarding child mortality rates and trends.

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  • Cancer and other noncommunicable diseases (NCDs) pose a significant threat to global development, with slow progress in addressing these issues highlighted by the recent UN meeting; key barriers include a lack of situational analyses and prioritization for effective action against NCDs.* -
  • The study aims to provide comprehensive data on cancer burden across 29 cancer types in 195 countries from 1990 to 2017, utilizing the Global Burden of Disease (GBD) methods to analyze cancer incidence, mortality, and disability metrics.* -
  • In 2017, there were 24.5 million new cancer cases globally, with significant variations based on socio-demographic factors; the majority of cancer-related disabilities stemmed
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Background And Objective: Measuring health literacy becomes more important because its association with health status and healthcare outcomes. Studies have developed at least 133 measurement tools for health literacy. HLS-EU-Q47 is a questionnaire consisting of 12 sub-dimensions and 47 questions developed by the Europe Health Literacy Consortium.

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Low adherence to leprosy treatment is the main challenge in Indonesia. This is a quasi-experimental observational study in a real setting of a leprosy control program in Indonesia. The study is aimed at evaluating an e-leprosy framework in increasing the rate of on-time attendance at primary health care and on-time completion of treatment of leprosy patients.

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Importance: Understanding causes and correlates of health loss among children and adolescents can identify areas of success, stagnation, and emerging threats and thereby facilitate effective improvement strategies.

Objective: To estimate mortality and morbidity in children and adolescents from 1990 to 2017 by age and sex in 195 countries and territories.

Design, Setting, And Participants: This study examined levels, trends, and spatiotemporal patterns of cause-specific mortality and nonfatal health outcomes using standardized approaches to data processing and statistical analysis.

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Recent years have witnessed an increased prevalence of knee osteoarthritis (KOA) among diabetes mellitus (DM) patients-conditions which might share common risk factors such as obesity and advanced aging. Therefore, we conducted dry-to-wet lab research approaches to assess the correlation of type 1 DM (T1DM) and type 2 DM (T2DM) with KOA among all age and genders of Taiwanese population. The strength of association (odds ratio: OR) was analyzed using a phenome-wide association study portal.

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Importance: Understanding global variation in firearm mortality rates could guide prevention policies and interventions.

Objective: To estimate mortality due to firearm injury deaths from 1990 to 2016 in 195 countries and territories.

Design, Setting, And Participants: This study used deidentified aggregated data including 13 812 location-years of vital registration data to generate estimates of levels and rates of death by age-sex-year-location.

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