collaborators

9 papers

eess.AS2026

CaReCoS: A Spectrogram based Visual Benchmark for Cardiac, Respiratory and Cough Sounds

Harshit Rajgarhia, Shuubham Ojha, Akhil Pothanapalli +4

Medical acoustic signals such as respiratory sounds, cardiac auscultations, and cough audio carry rich diagnostic information, yet no existing benchmark evaluates multimodal reason…

cs.AI2026

World Feedback for Clinical Agents: Diagnosing RL in FHIR Environments

Ananya Mantravadi, Harshit Rajgarhia, Prasanna Desikan +1

Clinical protocol-execution tasks -- checking a lab value, applying a threshold, placing a correctly structured FHIR order -- are natural candidates for RL from world feedback: onc…

eess.AS2026

BCoughBench: Benchmarking Respiratory Acoustic Foundation Models Under Body-Coupled Wearable Sensor Conditions

Mayur Sanap, Prasanna Desikan, Edgar Lobaton

Respiratory acoustic foundation models (FMs) are benchmarked exclusively on smartphone recordings, yet clinical deployment increasingly targets body-coupled (BC) wearables whose se…

cs.AI2026

LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data

Akshat Dasula, Prasanna Desikan, Jaideep Srivastava

Large language models (LLMs) are increasingly applied to structured clinical data, yet whether they can recognize the limits of their own knowledge on such tasks remains unexplored…

cs.AI2026

CareTransition-Audit: A Benchmark to Audit Discharge Summaries for Efficient Care Transitions

Akshat Dasula, Prasanna Desikan, Jaideep Srivastava +2

Incomplete or inconsistent discharge documentation drives care fragmentation and avoidable readmissions. Despite its critical role in patient safety, auditing discharge summaries r…

cs.LG2026

Beyond Classification: A Cough Regression Benchmark for Respiratory Acoustic Foundation Models

Mayur Sanap, Prasanna Desikan, Edgar Lobaton

Respiratory acoustic foundation models (FMs) excel at cough classification, yet their ability to predict continuous health quantities from cough audio remains largely unexplored, d…