Accelerating Disease Model Parameter Extraction: An LLM-Based Ranking Approach to Select Initial Studies For Literature Review Automation [0.03%]
加速疾病模型参数提取：一种基于LLM的排序方法，用于选择文献回顾自动化初期研究
Masood Sujau,Masako Wada,Emilie Vallée et al.
Masood Sujau et al.
As climate change transforms our environment and human intrusion into natural ecosystems escalates, there is a growing demand for disease spread models to forecast and plan for the next zoonotic disease outbreak. Accurate parametrization of...
Machine-Learned Codes from EHR Data Predict Hard Outcomes Better than Human-Assigned ICD Codes [0.03%]
基于电子健康记录数据的机器学习代码比人类分配的ICD代码更好地预测硬性结果
Ying Yin,Yijun Shao,Phillip Ma et al.
Ying Yin et al.
We used machine learning (ML) to characterize 894,154 medical records of outpatient visits from the Veterans Administration Central Data Warehouse (VA CDW) by the likelihood of assignment of 200 International Classification of Diseases (ICD...
CovC-ReDRNet: A Deep Learning Model for COVID-19 Classification [0.03%]
基于深度学习的COVID-19分类模型 CovC-ReDRNet
Hanruo Zhu,Ziquan Zhu,Shuihua Wang et al.
Hanruo Zhu et al.
Since the COVID-19 pandemic outbreak, over 760 million confirmed cases and over 6.8 million deaths have been reported globally, according to the World Health Organization. While the SARS-CoV-2 virus carried by COVID-19 patients can be ident...
Deep Theory of Functional Connections: A New Method for Estimating the Solutions of Partial Differential Equations [0.03%]
深层函数连接理论：求解偏微分方程的一种新方法
Carl Leake,Daniele Mortari
Carl Leake
This article presents a new methodology called Deep Theory of Functional Connections (TFC) that estimates the solutions of partial differential equations (PDEs) by combining neural networks with the TFC. The TFC is used to transform PDEs in...
Analytically Embedding Differential Equation Constraints into Least Squares Support Vector Machines Using the Theory of Functional Connections [0.03%]
基于函数连接理论的微分方程约束最小二乘支持向量机分析嵌入方法研究
Carl Leake,Hunter Johnston,Lidia Smith et al.
Carl Leake et al.
Differential equations (DEs) are used as numerical models to describe physical phenomena throughout the field of engineering and science, including heat and fluid flow, structural bending, and systems dynamics. While there are many other te...