相关实验视频

Updated: Mar 11, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.2K

针对GSWH的AI辅助选:验证可解释的基于HCT的死亡率模型

Ali Mansour1, Jordan Fuhrman2, Ronald Alvarado-Dyer3

  • 1Department of Neurology, Division of Neurocritical Care, University of Chicago Medical Center, Chicago, Illinois, USA.

Journal of neurotrauma
|March 10, 2026
PubMed
概括

一个新的人工智能模型使用头部CT扫描来预测平民头部枪伤 (GSWH) 的死亡率. 这种可解释的工具提供了客观的风险估计,有助于早期预后和选穿透性脑损伤.

关键词:
机器学习模型的模型.穿透性创伤性脑损伤是什么

更多相关视频

Constructing and Visualizing Models using Mime-based Machine-learning Framework06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.9K

相关概念视频

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
681