Articles and insights tagged with Healthcare.
The multi-billion dollar Direct-to-Consumer (DTC) genetic testing industry is an ethical minefield. This post breaks down the key risks—from data privacy to flawed health reports—and proposes a framework for responsible innovation using data justice and co-design principles.
A case study on using Latent Profile Analysis and Cox Proportional Hazards modeling to identify pre-diagnosis dietary patterns associated with colorectal cancer recurrence. We navigated complex, high-dimensional health data to deliver clinically relevant insights.
A case study on validating a new Food Frequency Questionnaire (FFQ) for dietary fiber intake. This post details the use of 24-hour dietary recalls as a reference method and the application of linear regression calibration to correct for measurement error, enhancing data accuracy for epidemiological research.
Leveraging machine learning on clinical data to build a robust model for early Chronic Kidney Disease (CKD) detection, improving patient outcomes and potentially reducing healthcare costs.
Building and evaluating machine learning models to predict Polycystic Ovary Syndrome (PCOS) using clinical and biochemical features, achieving high accuracy for early diagnosis.
Leveraging Python, RDFLib, and standard medical ontologies (SNOMED-CT, LOINC) to transform tabular Chronic Kidney Disease data into a structured Knowledge Graph, highlighting data integration and problem-solving.
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