AIMC Topic:
Supervised Machine Learning

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Towards Retrieving Force Feedback in Robotic-Assisted Surgery: A Supervised Neuro-Recurrent-Vision Approach.

IEEE transactions on haptics Dec 15, 2016
Robotic-assisted minimally invasive surgeries have gained a lot of popularity over conventional procedures as they offer many benefits to both surgeons and patients. Nonetheless, they still suffer from some limitations that affect their outcome. One ...
Neural Networks, Computer Feedback Minimally Invasive Surgical Procedures Humans Image Interpretation, Computer-Assisted Mechanical Phenomena Robotic Surgical Procedures Heart Supervised Machine Learning
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Supporting One-Time Point Annotations for Gesture Recognition.

IEEE transactions on pattern analysis and machine intelligence Dec 8, 2016
This paper investigates a new annotation technique that reduces significantly the amount of time to annotate training data for gesture recognition. Conventionally, the annotations comprise the start and end times, and the corresponding labels of gest...
Humans Pattern Recognition, Automated Accelerometry Image Processing, Computer-Assisted Supervised Machine Learning Video Recording Algorithms Wearable Electronic Devices Gestures
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Computational prediction of multidisciplinary team decision-making for adjuvant breast cancer drug therapies: a machine learning approach.

BMC cancer Dec 1, 2016
BACKGROUND: Multidisciplinary team (MDT) meetings are used to optimise expert decision-making about treatment options, but such expertise is not digitally transferable between centres. To help standardise medical decision-making, we developed a machi...
Aged, 80 and over Humans Adult Combined Modality Therapy Machine Learning Breast Neoplasms Supervised Machine Learning Clinical Decision-Making Middle Aged Algorithms Female Chemotherapy, Adjuvant Models, Theoretical Computer Simulation Aged Patient Care Team Antineoplastic Combined Chemotherapy Protocols
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An Intelligible Risk Stratification Model Based on Pairwise and Size Constrained Kmeans.

IEEE journal of biomedical and health informatics Nov 29, 2016
Having a system to stratify individuals according to risk is key to clinical disease prevention. This allows individuals identified at different risk tiers to benefit from further investigation and intervention. But the same risk score estimated for ...
Models, Statistical Supervised Machine Learning Medical Informatics Risk Assessment Diabetes Mellitus, Type 2 Cluster Analysis Humans Algorithms Databases, Factual
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Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals.

IEEE transactions on bio-medical engineering Nov 22, 2016
OBJECTIVE: An autoencoder-based framework that simultaneously reconstruct and classify biomedical signals is proposed. Previous work has treated reconstruction and classification as separate problems. This is the first study that proposes a combined ...
Algorithms Electrocardiography Signal Processing, Computer-Assisted Supervised Machine Learning Information Storage and Retrieval Pattern Recognition, Automated
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Semi-supervised learning for genomic prediction of novel traits with small reference populations: an application to residual feed intake in dairy cattle.

Genetics, selection, evolution : GSE Nov 7, 2016
BACKGROUND: Genomic prediction for novel traits, which can be costly and labor-intensive to measure, is often hampered by low accuracy due to the limited size of the reference population. As an option to improve prediction accuracy, we introduced a s...
Genome Quantitative Trait, Heritable Animal Nutritional Physiological Phenomena Breeding Dairying Cattle Genomics Phenotype Models, Biological Models, Genetic Female Animal Feed Animals Supervised Machine Learning
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Targeted use of growth mixture modeling: a learning perspective.

Statistics in medicine Nov 2, 2016
From the statistical learning perspective, this paper shows a new direction for the use of growth mixture modeling (GMM), a method of identifying latent subpopulations that manifest heterogeneous outcome trajectories. In the proposed approach, we uti...
Supervised Machine Learning Patient Outcome Assessment Machine Learning Prognosis Reproducibility of Results Bipolar Disorder Longitudinal Studies Models, Statistical Humans
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Semi-supervised learning of the electronic health record for phenotype stratification.

Journal of biomedical informatics Oct 12, 2016
Patient interactions with health care providers result in entries to electronic health records (EHRs). EHRs were built for clinical and billing purposes but contain many data points about an individual. Mining these records provides opportunities to ...
Electronic Health Records Supervised Machine Learning Disease Humans Phenotype
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Semi-Supervised Active Learning for Sound Classification in Hybrid Learning Environments.

PloS one Sep 14, 2016
Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that ...
Supervised Machine Learning Classification Humans Acoustics Problem-Based Learning Sound Machine Learning Algorithms
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A Cross-Correlated Delay Shift Supervised Learning Method for Spiking Neurons with Application to Interictal Spike Detection in Epilepsy.

International journal of neural systems Sep 1, 2016
This study introduces a novel learning algorithm for spiking neurons, called CCDS, which is able to learn and reproduce arbitrary spike patterns in a supervised fashion allowing the processing of spatiotemporal information encoded in the precise timi...
Synapses Cerebral Cortex Wavelet Analysis Epilepsy Humans Neural Networks, Computer Supervised Machine Learning Neural Inhibition Time Factors Neurons Action Potentials
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