Contextual Care Protocol using Neural Networks and Decision Trees
A contextual care protocol is used by a medical practitioner for patient healthcare, given the context or situation that the specified patient is in. This paper proposes a method to build an automated self-adapting protocol which can help make relevant, early decisions for effective healthcare delivery. The hybrid model leverages neural networks and decision trees. The neural network estimates the chances of each disease and each tree in the decision trees represents care protocol for a disease. These trees are subject to change in case of aberrations found by the diagnosticians. These corrections or prediction errors are clustered into similar groups for scalability and review by the experts. The corrections as suggested by the experts are incorporated into the model.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units
The management of invasive mechanical ventilation, and the regulation of sedation and analgesia during ventilation, constitutes a major part of the care of patients admitted to intensive care units. Both prolonged depend…
Managementreinforcement-learningReinforcement LearningReinforcement Learning (RL)A Practical Method for Solving Contextual Bandit Problems Using Decision Trees
Many efficient algorithms with strong theoretical guarantees have been proposed for the contextual multi-armed bandit problem. However, applying these algorithms in practice can be difficult because they require domain e…
Thompson SamplingMCP-AI: Protocol-Driven Intelligence Framework for Autonomous Reasoning in Healthcare
Healthcare AI systems have historically faced challenges in merging contextual reasoning, long-term state management, and human-verifiable workflows into a cohesive framework. This paper introduces a completely innovativ…
Contextually Private Mechanisms
We introduce a framework for comparing the privacy of different mechanisms. A mechanism designer employs a dynamic protocol to elicit agents' private information. Protocols produce a set of contextual privacy violations …
Improving Stability in Decision Tree Models
Owing to their inherently interpretable structure, decision trees are commonly used in applications where interpretability is essential. Recent work has focused on improving various aspects of decision trees, including t…