Optimizing Operation Room Utilization—A Prediction Model
Optimizing Operation Room Utilization—A Prediction Model Background: Operating rooms are the core of hospitals. They are a primary source of revenue and are often seen as one of the bottlenecks in the medical system. Many efforts are made to increase throughput, reduce costs, and maximize incomes, as well as optimize clinical outcomes and patient satisfaction. […]
CPLLM: Clinical prediction with large language models
CPLLM: Clinical prediction with large language models We present Clinical Prediction with Large Language Models (CPLLM), a method that involves fine-tuning a pre-trained Large Language Model (LLM) for predicting clinical disease and readmission. We utilized quantization and fine-tuned the LLM using prompts. For diagnostic predictions, we predicted whether patients would be diagnosed with a target […]
A machine learning-based prediction model for gout in hyperuricemics: a nationwide cohort study
A machine learning-based prediction model for gout in hyperuricemics: a nationwide cohort study Objective To develop a machine learning-based prediction model for identifying hyperuricemic participants at risk of developing gout. Methods A retrospective nationwide Israeli cohort study used the Clalit Health Insurance database of 473 124 individuals to identify adults 18 years or older with at least […]
DSF-GAN: DownStream Feedback Generative Adversarial Network
DSF-GAN: DownStream Feedback Generative Adversarial Network Utility and privacy are two crucial measurements of the quality of synthetic tabular data. While significant advancements have been made in privacy measures, generating synthetic samples with high utility remains challenging. To enhance the utility of synthetic samples, we propose a novel architecture called the DownStream Feedback Generative Adversarial […]