Research

Publications & Ongoing Work

My research spans clinical AI evaluation, calibration theory, IoT in healthcare, and LLM behaviour. Below are papers I have authored or contributed to.

PublishedSpringer Nature · CCIS

Intravenous Bag Monitoring and Alert System — A Prototype

Real-time IV fluid monitoring using microcontroller-based non-contact capacitive sensors, integrated with an IoT platform for centralised alerting. Presented at ICBEST 2025.

Aman Chandra H et al. · 2025

Under ReviewBMC Medical Informatics · Springer Nature

Severity-Aware Evaluation of ICU Mortality Prediction Using Risk-Weighted Error Metrics (RWEM)

Introduces RWEM — a metric that penalises missed deaths by patient severity. Evaluated across 5 models and 3 critical care databases.

Aman Chandra H, K.C. Narendra · 2025

Under ReviewIEEE Access

Severity-Weighted Calibration Error (SWCE)

Aggregate calibration scores mask failures in high-acuity subgroups. Per-band isotonic recalibration consistently fixed this; global recalibration did not.

Aman Chandra H, K.C. Narendra · 2025

Under ReviewICAIHC 2026

Clinical Risk-Weighted Evaluation of ICU Mortality Prediction Models (CRWS)

A cost-sensitive evaluation framework for ICU mortality, penalising missed deaths over false alarms. Evaluated across 5 model classes on 3 independent critical care databases.

Aman Chandra H, Abhijna Shivaprakash et al. · 2025

Under ReviewICETCI 2026

NOMOS: RAG Framework for Jurisdiction-Specific Indian Legal QA

Privacy-preserving legal QA over 2.32M characters of Indian statutory text using local LLM inference, ChromaDB, and React + Firebase. Outperformed GPT-4 on citation accuracy.

Sameer Kulkarni, Aman Chandra H et al. · 2025

Submitted2026

Prevalence Shift and ICU Mortality Miscalibration Across Institutions

Zero-label Bayesian correction for prevalence shift achieving 56–65% calibration error reduction across 185 hospitals without model retraining.

Aman Chandra H, Stuti Shivhare, Suyash Sahu, Sameer Kulkarni et al. · 2026

SubmittedCONNIT 2026, Hubbali

Language as a Hidden Variable: Measuring Behavioral Divergence in Multilingual Large Language Models

A controlled multilingual study introducing BDS and showing cross-language behavioral divergence up to 2.5x within-language variation.

Aman Chandra H, Sameer Kulkarni, S Nithin, Khushboo Pandey · 2026

Research Areas

Clinical AI EvaluationICU Mortality PredictionCalibration TheoryIoT in HealthcareLLM BehaviourLegal AISignal ProcessingNeuroscience & AI