Metrics Beyond Data

Predicting Human Lifespan Using Healthcare Data Analytics: Can Ayurveda Add a New Dimension? Introduction Predicting human lifespan has always been a challenging yet fascinating goal in healthcare. With the rise of data science, predictive models are now used to estimate survival probabilities based on clinical and demographic data. However, most existing models rely purely on biomedical factors and often overlook deeper individualized and environmental influences. This article explores a unique and innovative idea: integrating Ayurvedic principles such as dosha (body constitution) and desha (geographical influence) into modern predictive analytics to improve lifespan prediction. Current Approach in Healthcare Data Analytics Modern prediction of survival is primarily done using techniques from Survival Analysis. These models do not predict exact lifespan but estimate probabilities such as: Risk of mortality within a specific time (e.g., 1 year, 5 years) Su...

Why Some Treatments Don’t Work: Understanding GLP-1 Resistance Through Genetics Introduction In modern healthcare, treatments are often designed based on clinical trials and population-level outcomes. However, one important reality is becoming increasingly clear: not all treatments work equally for everyone. A recent focus in medical research is on GLP-1 therapies, widely used for managing diabetes and supporting weight loss. While these treatments have shown remarkable results for many individuals, a significant group of patients does not respond as expected. What is GLP-1 and Why is it Important? GLP-1 (Glucagon-Like Peptide-1) is a natural hormone in the body that plays a crucial role in: Regulating blood sugar levels Reducing appetite Supporting weight management Medications based on GLP-1 mechanisms have gained global attention due to their effectiveness in treating type 2 diabetes and obesity. The Problem: Not Everyone Responds the Sa...