Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …
From a research point of view, impressive results have been reported using computer-aided …
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Mindboggling morphometry of human brains
Mindboggle (http://mindboggle. info) is an open source brain morphometry platform that
takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data …
takes in preprocessed T1-weighted MRI data and outputs volume, surface, and tabular data …
A multi-omic atlas of the human frontal cortex for aging and Alzheimer's disease research
We initiated the systematic profiling of the dorsolateral prefrontal cortex obtained from a
subset of autopsied individuals enrolled in the Religious Orders Study (ROS) or the Rush …
subset of autopsied individuals enrolled in the Religious Orders Study (ROS) or the Rush …
Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data
A large number of papers have introduced novel machine learning and feature extraction
methods for automatic classification of Alzheimer's disease (AD). However, while the vast …
methods for automatic classification of Alzheimer's disease (AD). However, while the vast …
A community approach to mortality prediction in sepsis via gene expression analysis
Improved risk stratification and prognosis prediction in sepsis is a critical unmet need.
Clinical severity scores and available assays such as blood lactate reflect global illness …
Clinical severity scores and available assays such as blood lactate reflect global illness …
Transfer learning for Alzheimer's disease through neuroimaging biomarkers: a systematic review
Alzheimer's disease (AD) is a remarkable challenge for healthcare in the 21st century. Since
2017, deep learning models with transfer learning approaches have been gaining …
2017, deep learning models with transfer learning approaches have been gaining …
Scientific utopia III: Crowdsourcing science
EL Uhlmann, CR Ebersole… - Perspectives on …, 2019 - journals.sagepub.com
Most scientific research is conducted by small teams of investigators who together formulate
hypotheses, collect data, conduct analyses, and report novel findings. These teams operate …
hypotheses, collect data, conduct analyses, and report novel findings. These teams operate …
A review of the literature on big data analytics in healthcare
P Galetsi, K Katsaliaki - Journal of the Operational Research …, 2020 - Taylor & Francis
Big data analytics (BDA) is of paramount importance in healthcare aspects such as patient
diagnostics, fast epidemic recognition, and improvement of patient management. The …
diagnostics, fast epidemic recognition, and improvement of patient management. The …
Crowdsourcing in medical research: concepts and applications
Crowdsourcing shifts medical research from a closed environment to an open collaboration
between the public and researchers. We define crowdsourcing as an approach to problem …
between the public and researchers. We define crowdsourcing as an approach to problem …