相关实验视频

Updated: Jan 14, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

开发和验证临床成像机器学习和深度学习模型,以预测患者对初始抗药物的反应

Mohammad-Reza Nazem-Zadeh^1,2, Richard Shek-Kwan Chang^1,3, Sarah Barnard¹

¹Department of Neuroscience, School of Translational Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia.

|October 24, 2025

概括

使用脑MRI和临床数据的人工智能模型可以高准确度地预测发作自由度. 这些人工智能工具可能会改善患者的治疗选择.

科学领域:

神经学神经学
医疗成像医学成像
人工智能的人工智能

背景情况:

抗发作药物 (ASM) 是第一线治疗方法,但对约40%的患者是无效的.
对ASM的个体反应是不可预测的,需要更好的治疗选择策略.

研究的目的:

开发和验证人工智能 (AI) 模型,用于预测患者对前两种ASM的反应.
整合临床数据和脑磁共振成像 (MRI) 以提高预测准确度.

主要方法:

使用临床特征,ASM和多式脑MRI数据开发AI模型.
采用融合深度学习 (DL) 模型,结合3D视频ResNet,变压器编码器和双线性神经网络.
使用五倍交叉内部验证和来自人类项目外部队列的验证模型.

主要成果:

融合DL模型在内部交叉验证中获得了0.75±0.05的F1得分.
这种DL模型在外部验证队列 (p < 0.001) 上明显优于最佳机器学习 (ML) 模型.
该模型整合了多序MRI数据,ASM方案和临床特征以进行预测.

结论:

结合脑部MRI,临床和药物数据的AI模型可以预测近期发作的发作自由度.
这些人工智能工具显示出改善治疗选择和告知临床决策支持系统的潜力.
建议在更大的患者队伍中进一步验证以确认疗效.

关键词:

抗发作药物抗发作药物人工智能的人工智能是人工智能.大脑MRI脑部MRI脑部是一种.的成像成像研究机器学习是机器学习.

更多相关视频

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue

Generation and On-Demand Initiation of Acute Ictal Activity in Rodent and Human Tissue

Published on: January 19, 2019

相关概念视频

Epilepsy and Seizures: Overview

Epilepsy and Seizures: Overview

Epilepsy is a chronic neurological disease marked by recurrent, unpredictable seizures. These seizures are caused by abnormal electrical discharges in the brain, leading to behavior, sensation, or consciousness alterations. They can also cause transient impairment of awareness, interfering with daily activities.
Various factors can trigger epilepsy, including genetic factors, brain damage, metabolic causes, and unknown etiology. Diagnosis of epilepsy involves electroencephalography (EEG), which...

Seizures: Classification

Seizures: Classification

Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types: