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Integrated Machine Learning Approaches for Predicting Ischemic Stroke and Thromboembolism in Atrial Fibrillation.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Atrial fibrillation (AF) is a common cardiac rhythm disorder, which increases the risk of ischemic stroke and other thromboembolism (TE). Accurate prediction of TE is highly valuable for early intervention to AF patients. However, the prediction perf...

Structured Pyramidal Neural Networks.

International journal of neural systems
The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory. PNNs are applied to computer vision and based on the concept of receptive fields. This paper prop...

Monitoring Hitting Load in Tennis Using Inertial Sensors and Machine Learning.

International journal of sports physiology and performance
CONTEXT: Quantifying external workload is fundamental to training prescription in sport. In tennis, global positioning data are imprecise and fail to capture hitting loads. The current gold standard (manual notation) is time intensive and often not p...

Who's Who? Detecting and Resolving Sample Anomalies in Human DNA Sequencing Studies with Peddy.

American journal of human genetics
The potential for genetic discovery in human DNA sequencing studies is greatly diminished if DNA samples from a cohort are mislabeled, swapped, or contaminated or if they include unintended individuals. Unfortunately, the potential for such errors is...

Performance analysis of a machine learning flagging system used to identify a group of individuals at a high risk for colorectal cancer.

PloS one
Individuals with colorectal cancer (CRC) have a tendency to intestinal bleeding which may result in mild to severe iron deficiency anemia, but for many colon cancer patients hematological abnormalities are subtle. The fecal occult blood test (FOBT) i...

Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
OBJECTIVES: One of the major challenges facing psychiatry is how to incorporate biological measures in the classification of mental health disorders. Many of these disorders affect brain development and its connectivity. In this study, we propose a n...

Finances and returns for robotic dairies.

Journal of dairy science
Automatic milking systems (AMS) became commercially available in the early 1990s. These systems provide flexibility and improve the lifestyle of farmers installing them. Because of the larger capital cost per kilogram of milk produced, observational ...

Autodelineation of cervical cancers using multiparametric magnetic resonance imaging and machine learning.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: Tumour delineation is a challenging, time-consuming and complex part of radiotherapy planning. In this study, an automatic method for delineating locally advanced cervical cancers was developed using a machine learning approach.

Sensory tractography and robot-quantified proprioception in hemiparetic children with perinatal stroke.

Human brain mapping
Perinatal stroke causes most hemiparetic cerebral palsy, resulting in lifelong disability. We have demonstrated the ability of robots to quantify sensory dysfunction in hemiparetic children but the relationship between such deficits and sensory tract...

Machine learning based compartment models with permeability for white matter microstructure imaging.

NeuroImage
Some microstructure parameters, such as permeability, remain elusive because mathematical models that express their relationship to the MR signal accurately are intractable. Here, we propose to use computational models learned from simulations to est...