Publications by authors named "Kai Nichols"
Joint Multi-Modal Longitudinal Regression and Classification for Alzheimer's Disease Prediction.
IEEE Trans Med Imaging
June 2020
Alzheimer's disease (AD) is a serious neurodegenerative condition that affects millions of individuals across the world. As the average age of individuals in the United States and the world increases, the prevalence of AD will continue to grow. To address this public health problem, the research community has developed computational approaches to sift through various aspects of clinical data and uncover their insights, among which one of the most challenging problem is to determine the biological mechanisms that cause AD to develop.
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- Alzheimer's disease (AD) is a major neurodegenerative condition impacting millions globally, and machine learning is now being applied to predict its progression.
- A new algorithm introduced in this study utilizes multi-block alternating direction methods to optimize a unique objective that integrates various types of longitudinal clinical data, aiming to predict cognitive scores and diagnoses for AD patients.
- This innovative approach outperforms traditional machine learning methods by incorporating the structural complexities of clinical data and helps validate existing brain and genetic biomarkers associated with Alzheimer's in prior research.