Skip to content
View Audency's full-sized avatar
12 followers · 34 following

Block or report Audency

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
Audency/README.md

Hi, I’m Audêncio Victor, PhD

Epidemiologist • Health Data Scientist • Public Health Researcher

🔬 I work at the intersection of epidemiology, machine learning, and maternal & child health, applying advanced data science methods to improve health outcomes in low- and middle-income countries.

I hold a PhD in Public Health – Epidemiology (University of São Paulo), and I am currently a Researcher in Health Data Science at the London School of Hygiene & Tropical Medicine (LSHTM), University of London.

My work involves classical biostatistics, predictive modelling, AI, and big data applied to large multi-country health datasets, especially in maternal, fetal, and neonatal health.

👀 Research Interests

  • Epidemiology & Public Health
  • Maternal, Fetal, and Neonatal Health
  • Machine Learning & AI in Health
  • Big Data & Predictive Modelling
  • Global Health and Health Inequalities
  • Cardiovascular Disease & Nutrition Epidemiology

I’m looking to collaborate on

  • Health data science projects
  • Predictive models for public health
  • Epidemiological research using R or Python
  • Maternal and child health studies

Where to find me

Current Position

Researcher in Health Data Science – LSHTM
Working on predictive modelling for stillbirths and neonatal deaths using multi-country cohorts from Sub-Saharan Africa.

Summary

Epidemiologist and data scientist committed to applying advanced analytical methods to global health challenges, bridging quantitative science and real-world health policy.

Pinned Loading

  1. Prediction-of-Gestational-Weight-Gain-for-Pregnancy Prediction-of-Gestational-Weight-Gain-for-Pregnancy Public

    Identificação precoce de mulheres com maior risco de ganho de peso excessivo durante a gestação pode permitir intervenções precoces para prevenir complicações e promover um ganho de peso adequado

    Jupyter Notebook 1

  2. Meningitis-DiagnosisML Meningitis-DiagnosisML Public

    A machine learning initiative to improve the diagnostic processes for bacterial meningitis. Utilizing clinical and laboratory data from the SINAN database in São Paulo, this project develops predic…

    Jupyter Notebook

  3. Predict-cervical-cancer- Predict-cervical-cancer- Public

    This study uses machine learning models to predict in-hospital mortality among patients with cervical cancer in this region, aiming to identify key predictive factors that can support the implement…

    Jupyter Notebook

  4. Predictors-of-inadequate-gestational-weight-gain-according-to-IOM-recommendations-and-Intergrowth Predictors-of-inadequate-gestational-weight-gain-according-to-IOM-recommendations-and-Intergrowth Public

    To identify maternal predictors of GWG according to the 2009 Institute of Medicine (IOM) recommendations and Intergrowth-21st standards.

    R

  5. Predictors-of-Low-Birth-Weight-using-Machine-Laerning- Predictors-of-Low-Birth-Weight-using-Machine-Laerning- Public

    Predictors of Low Birth Weight using Machine Laerning

    Jupyter Notebook

  6. survival-analysis-approach-Predictors-of-nutritional-recovery-time-in-children-in-Mozambique- survival-analysis-approach-Predictors-of-nutritional-recovery-time-in-children-in-Mozambique- Public

    Predictors of nutritional recovery time in children aged 6–59 months with severe acute malnutrition in Sofala Province, Mozambique

    R