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 […]
Volume-Outcome Relationship of Resternotomy Coronary Artery Bypass Grafting
Volume-Outcome Relationship of Resternotomy Coronary Artery Bypass Grafting We assessed volume-outcome relationships of resternotomy coronary artery bypass grafting (CABG). We studied over 1M first-time CABG and about 100K resternotomy CABG patients between 2010 and 2019. Primary outcomes were in-hospital mortality and mortality and morbidity (M&M) rates calculated per hospital and per surgeon. Outcomes were compared […]
Multi-Dimensional Laboratory Test Score as a Proxy for Health
Multi-Dimensional Laboratory Test Score as a Proxy for Health The standard of care for a physician to review laboratory tests results is to weigh each individual laboratory test result and compare it to against a standard reference range. Such a method of scanning can lead to missing high-level information. Different methods have tried to overcome […]
Improving Prediction Models’ Propriety in Intensive-Care Unit, by Enforcing an Advance Notice Period
Improving Prediction Models’ Propriety in Intensive-Care Unit, by Enforcing an Advance Notice Period Intensive-Care-Units (ICUs) are time-critical, and sufficient reaction time is crucial. Previous studies of systems for alerting life-threatening events in the ICU, suffer from “immediate” events bias. In this research, we present a new approach for outcome prediction in ICU admissions, which takes […]
Comparison of Classification with Reject Option Approaches on MIMIC-IV Dataset
Comparison of Classification with Reject Option Approaches on MIMIC-IV Dataset This work compares two machine learning approaches that use the reject option method, i.e., the possibility to abstain from outputting a prediction in case the model is not confident about it, thus rejecting the sample. We demonstrated the usability of such a model for predicting […]
ProteinBERT: a universal deep-learning model of protein sequence and function
ProteinBERT: a universal deep-learning model of protein sequence and function Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optimized for text analysis. We introduce ProteinBERT, a deep language model specifically designed for proteins. Our […]
Optimizing Operation Room Utilization—A Prediction Model
Optimizing Operation Room Utilization—A Prediction Model 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. We […]