AIMC Topic: Data Interpretation, Statistical
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Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study.
The Lancet. Digital health
Sep 5, 2019
BACKGROUND: Deep learning has the potential to transform health care; however, substantial expertise is required to train such models. We sought to evaluate the utility of automated deep learning software to develop medical image diagnostic classifie...
Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data.
EBioMedicine
Aug 13, 2019
BACKGROUND: Current fMRI-based classification approaches mostly use functional connectivity or spatial maps as input, instead of exploring the dynamic time courses directly, which does not leverage the full temporal information.
Machine learning in clinical practice: prospects and pitfalls.
The Medical journal of Australia
Aug 6, 2019
Machine learning with the hierarchy-of-hypotheses (HoH) approach discovers novel pattern in studies on biological invasions.
Research synthesis methods
Aug 5, 2019
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free s...
If machines can learn, who needs scientists?
Journal of magnetic resonance (San Diego, Calif. : 1997)
Jul 16, 2019
Machine learning has been used in NMR in for decades, but recent developments signal explosive growth is on the horizon. An obstacle to the application of machine learning in NMR is the relative paucity of available training data, despite the existen...
Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds.
Computer methods and programs in biomedicine
Jun 10, 2019
BACKGROUND AND OBJECTIVE: The recognition of many sleep related pathologies highly relies on an accurate classification of sleep stages. Clinically, sleep stages are usually labelled by sleep experts through visually inspecting the whole-night polyso...
A hybrid neural network for large-scale expressway network OD prediction based on toll data.
PloS one
May 23, 2019
Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collec...
Intelligent health data analytics: A convergence of artificial intelligence and big data.
Healthcare management forum
May 22, 2019
Healthcare is a living system that generates a significant volume of heterogeneous data. As healthcare systems are pivoting to value-based systems, intelligent and interactive analysis of health data is gaining significance for health system manageme...
Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing.
Epilepsia
May 21, 2019
OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers counsel patients about SUDEP. One potential solution is to electronically prompt clinicians to provi...
Neurosurgery
Drug Resistant Epilepsy
Death, Sudden
Epilepsy, Tonic-Clonic
Sudden Unexpected Death in Epilepsy
Natural Language Processing
Data Interpretation, Statistical
Epilepsy
Risk Factors
Sensitivity and Specificity
Cross-Sectional Studies
Algorithms
Retrospective Studies
Electronic Health Records
Humans
Estimating the Population Average Treatment Effect in Observational Studies with Choice-Based Sampling.
The international journal of biostatistics
Apr 16, 2019
We consider causal inference in observational studies with choice-based sampling, in which subject enrollment is stratified on treatment choice. Choice-based sampling has been considered mainly in the econometrics literature, but it can be useful for...
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