FRACTAL: Fine-Grained Scoring from Aggregate Text Labels

no code implementations • 7 Apr 2024 • Yukti Makhija, Priyanka Agrawal, Rishi Saket, Aravindan Raghuveer

Large language models (LLMs) are being increasingly tuned to power complex generation tasks such as writing, fact-seeking, querying and reasoning.

Math Multiple Instance Learning +3

Learning predictive checklists from continuous medical data

no code implementations • 14 Nov 2022 • Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan

Checklists, while being only recently introduced in the medical domain, have become highly popular in daily clinical practice due to their combined effectiveness and great interpretability.

Severity and Mortality Prediction Models to Triage Indian COVID-19 Patients

no code implementations • 2 Sep 2021 • Samarth Bhatia, Yukti Makhija, Sneha Jayaswal, Shalendra Singh, Ishaan Gupta

Here, we present two interpretable machine learning models predicting the clinical outcomes, severity, and mortality, of the patients based on routine non-invasive surveillance of blood parameters from one of the largest cohorts of Indian patients at the day of admission.

Interpretable Machine Learning Mortality Prediction

Challenges in the application of a mortality prediction model for COVID-19 patients on an Indian cohort

no code implementations • 15 Jan 2021 • Yukti Makhija, Samarth Bhatia, Shalendra Singh, Sneha Kumar Jayaswal, Prabhat Singh Malik, Pallavi Gupta, Shreyas N. Samaga, Shreya Johri, Sri Krishna Venigalla, Rabi Narayan Hota, Surinder Singh Bhatia, Ishaan Gupta

Therefore, it becomes essential to triage the patients based on the severity of their disease and devote resources towards critically ill patients.

Mortality Prediction Survival Prediction