AIMC Topic:
Databases, Factual
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Machine learning in population health: Opportunities and threats.
PLoS medicine
Nov 27, 2018
Abraham D. Flaxman and Theo Vos of the Institute for Health Metrics and Evaluation, University of Washington, discuss near-term applications for ML in population health and name their priorities for ongoing ML development.
eDRAM: Effective early disease risk assessment with matrix factorization on a large-scale medical database: A case study on rheumatoid arthritis.
PloS one
Nov 26, 2018
Recently, a number of analytical approaches for probing medical databases have been developed to assist in disease risk assessment and to determine the association of a clinical condition with others, so that better and intelligent healthcare can be ...
Artificial intelligence for aging and longevity research: Recent advances and perspectives.
Ageing research reviews
Nov 22, 2018
The applications of modern artificial intelligence (AI) algorithms within the field of aging research offer tremendous opportunities. Aging is an almost universal unifying feature possessed by all living organisms, tissues, and cells. Modern deep lea...
Novel Effective Connectivity Inference Using Ultra-Group Constrained Orthogonal Forward Regression and Elastic Multilayer Perceptron Classifier for MCI Identification.
IEEE transactions on medical imaging
Nov 20, 2018
Mild cognitive impairment (MCI) detection is important, such that appropriate interventions can be imposed to delay or prevent its progression to severe stages, including Alzheimer's disease (AD). Brain connectivity network inferred from the function...
Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study.
PLoS medicine
Nov 20, 2018
BACKGROUND: Pneumothorax can precipitate a life-threatening emergency due to lung collapse and respiratory or circulatory distress. Pneumothorax is typically detected on chest X-ray; however, treatment is reliant on timely review of radiographs. Sinc...
Using machine learning to investigate self-medication purchasing in England via high street retailer loyalty card data.
PloS one
Nov 19, 2018
The availability alongside growing awareness of medicine has led to increased self-treatment of minor ailments. Self-medication is where one 'self' diagnoses and prescribes over the counter medicines for treatment. The self-care movement has importan...
Detecting abnormal electroencephalograms using deep convolutional networks.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Nov 17, 2018
OBJECTIVES: Electroencephalography (EEG) is a central part of the medical evaluation for patients with neurological disorders. Training an algorithm to label the EEG normal vs abnormal seems challenging, because of EEG heterogeneity and dependence of...
MAIA-A machine learning assisted image annotation method for environmental monitoring and exploration.
PloS one
Nov 16, 2018
Digital imaging has become one of the most important techniques in environmental monitoring and exploration. In the case of the marine environment, mobile platforms such as autonomous underwater vehicles (AUVs) are now equipped with high-resolution c...
Development of an artificial intelligence system to classify pathology and clinical features on retinal fundus images.
Clinical & experimental ophthalmology
Nov 15, 2018
IMPORTANCE: Artificial intelligence (AI) algorithms are under development for use in diabetic retinopathy photo screening pathways. To be clinically acceptable, such systems must also be able to classify other fundus abnormalities and clinical featur...
Synthesizing Chest X-Ray Pathology for Training Deep Convolutional Neural Networks.
IEEE transactions on medical imaging
Nov 14, 2018
Medical datasets are often highly imbalanced with over-representation of prevalent conditions and poor representation of rare medical conditions. Due to privacy concerns, it is challenging to aggregate large datasets between health care institutions....
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