Search
3 articles for “MIMIC-III”
-
TRACE: Tracking the Loss of Memory Provenance in LLM Agents
Abstract: AI agents that carry memory across sessions gain better personalization and decision-making, but this persistence opens a serious security gap. When an agent repeatedly condenses earlier interactions into compact “lessons,” the trail linking each lesson back to the interaction that produced it gradually fades. We term this effect Reflective Attribution Collapse (RAC): the progressive loss of provenance and forensic traceability that results from repeated memory reflection. Under RAC, a malicious …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 33–49 Read article
-
Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
-
A study on Controlling Artificial Heart
Abstract: The artificial heart has moved from a visionary concept to a clinically viable organreplacement technology, yet its longterm success hinges on the sophistication of its control architecture. This paper presents a comprehensive investigation of closedloop control strategies that enable an artificial heart to mimic the dynamic, beattobeat adaptability of its biological counterpart. We first construct a highfidelity cardiovascular model that integrates ventricular elastance, systemic and pulmonary vascular compliance, and realtime …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 14–23 Read article