Identification of relevant diffusion MRI metrics impacting cognitive functions using a novel feature selection method
원문 초록
Mild Traumatic Brain Injury (mTBI) is a significant public health problem. The most troubling symptoms after mTBI are cognitive complaints. Studies show measurable differences between patients with mTBI and healthy controls with respect to tissue microstructure using diffusion MRI. However, it remains unclear which diffusion measures are the most informative with regard to cognitive functions in both the healthy state as well as after injury. In this study, we use diffusion MRI to formulate a predictive model for performance on working memory based on the most relevant MRI features. The key challenge is to identify relevant features over a large feature space with high accuracy in an efficient manner. To tackle this challenge, we propose a novel improvement of the best first search approach with crossover operators inspired by genetic algorithm. Compared against other heuristic feature selection algorithms, the proposed method achieves significantly more accurate predictions and yields clinically interpretable selected features.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Dual Deep Learning Approach for Non-invasive Renal Tumour Subtyping with VERDICT-MRI
Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature Selection
Exploring the robustness of TractOracle methods in RL-based tractography
Malware Classification Leveraging NLP & Machine Learning for Enhanced Accuracy
Simple is what you need for efficient and accurate medical image segmentation
Permutation-Free High-Order Interaction Tests
토론
이 논문과 연결된 포럼 글이 아직 없습니다.