From the 2 of 6 linked papers with an AI index.
6 papers
CalTwin: Towards Calibrated, Shift-Robust Medical World Models via Fisher-Information Regularisation
Behraj Khan, Shabir Ahmad, Syed Ahmad Chan Bukhari +1
The paper introduces CalTwin, a lightweight regularization that combines a Fisher‑information‑based shift penalty with a confidence‑misalignment penalty to make GRU‑based medical w…
PIcsC: Partitioning-Induced Covariate Shift Correction
Behraj Khan, Behroz Mirza, Syed Ahmad Chan Bukhari +1
The paper introduces PIcsC, a Fisher information‑based regularization method that corrects covariate shift caused by data partitioning in both centralized (e.g., cross‑validation)…
Graph-Constrained Policy Learning for Extreme Clinical Code Prediction
Amritpal Singh, Sebastian Torres, Khawar Shakeel +1
Clinical code prediction maps unstructured discharge summaries to ICD-10-CM leaf codes in a large, sparse, and deeply hierarchical label space. Most systems treat the task as flat…
Early Prediction of Multi-Label Care Escalation Triggers in the Intensive Care Unit Using Electronic Health Records
Syed Ahmad Chan Bukhari, Amritpal Singh, Shifath Hossain +1
Intensive Care Unit (ICU) patients often present with complex, overlapping signs of physiological deterioration that require timely escalation of care. Traditional early warning sy…
A Machine Learning Framework for Pathway-Driven Therapeutic Target Discovery in Metabolic Disorders
Iram Wajahat, Amritpal Singh, Fazel Keshtkar +1
Metabolic disorders, particularly type 2 diabetes mellitus (T2DM), represent a significant global health burden, disproportionately impacting genetically predisposed populations su…
A Narrative-Driven Computational Framework for Clinician Burnout Surveillance
Syed Ahmad Chan Bukhari, Fazel Keshtkar, Alyssa Meczkowska
Clinician burnout poses a substantial threat to patient safety, particularly in high-acuity intensive care units (ICUs). Existing research predominantly relies on retrospective sur…