相关实验视频

Updated: Jan 9, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

16.1K

机器学习算法和人工神经网络用于使用轨道参数预测精神分裂症.

Elif Emre1, Derya Ozturk Soylemez2, Yusuf Secgin3

  • 1Department of Anatomy, Faculty of Medicine, Firat University, Elazig, Turkey.

Scientific reports
|November 29, 2025
PubMed
概括

机器学习和人工神经网络通过分析CT扫描的轨道测量来诊断精神分裂症. 这种人工智能驱动的方法可以为早期发现这种持久性精神疾病提供新的工具.

关键词:
人工神经网络的人工神经网络计算机断层扫描 (CT) 是一种计算机断层扫描.机器学习是机器学习.轨道参数 轨道参数精神分裂症是一种精神分裂症.

更多相关视频

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.3K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.0K

相关概念视频

Biological Causes of Schizophrenia01:29

Biological Causes of Schizophrenia

Schizophrenia, a severe psychiatric disorder, arises from a complex interplay of biological factors, including genetic predisposition, structural brain abnormalities, neurotransmitter dysregulation, and developmental irregularities. These factors collectively contribute to the onset and progression of the disorder, which typically manifests in late adolescence or early adulthood.
Genetic Factors in Schizophrenia
The genetic basis of schizophrenia is strongly supported by family and twin...
467