A Systematic Process for Feature Selection, Feature Dropping, and Algorithmic Self-Selection in Iterative Machine Learning Development Feature selection is the most consequential and least disciplined step in the machine
Healthcare’s AI crisis isn’t what you think. While the pandemic unleashed hundreds of COVID-19 prediction models promising diagnostic breakthroughs, zero reached successful clinical deployment. A 2020 BMJ systematic review
Overlooking the Arabian Sea from Taj Lands End, as I wrapped up a journey through Mumbai and the Maldives, a simple yet profound realization resurfaced: human connection and relationships
Artificial intelligence (AI) is often expected to outperform humans in healthcare because the stakes are high. A more rational approach is to evaluate AI against the real‑world performance of
For all the amazing innovators, leaders, founders, entrepreneurs, and students—undergrad, grad, and beyond—tasked with building AI strategy, many of you whom I’ve had the privilege of mentoring and coaching
Prompt engineering – the crafting of effective inputs for generative AI – is emerging as a critical skill in healthcare. This article provides a comprehensive overview of six key
Neo’s Legacy – Predicting Congenital Risk in Dogs with AI Neo’s Legacy – Predicting Congenital Risk in Dogs with AI Neo came into our lives as a surprise birthday
In this article, I explore the application of LangChain in building AI agents, with a specific focus on drug safety reporting. Within the field of pharmacovigilance, LangChain could play
Understanding the needs and problems emerging from quantitative data analysis is crucial for driving objective, realistic and purposeful innovations across societal, private, government, or any other setup. Over the
Growing up in a family of educators in India, I often stopped by my late father’s department between my engineering classes. His office was next to the engineering college
