AIMC Topic: Machine Learning

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Modeling time-to-event (survival) data using classification tree analysis.

Journal of evaluation in clinical practice
RATIONALE, AIMS, AND OBJECTIVES: Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (cal...

Piecewise convexity of artificial neural networks.

Neural networks : the official journal of the International Neural Network Society
Although artificial neural networks have shown great promise in applications including computer vision and speech recognition, there remains considerable practical and theoretical difficulty in optimizing their parameters. The seemingly unreasonable ...

Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation.

PloS one
To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving...

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation.

Medical image analysis
Accurate lung nodule segmentation from computed tomography (CT) images is of great importance for image-driven lung cancer analysis. However, the heterogeneity of lung nodules and the presence of similar visual characteristics between nodules and the...

Automated robot-assisted surgical skill evaluation: Predictive analytics approach.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Surgical skill assessment has predominantly been a subjective task. Recently, technological advances such as robot-assisted surgery have created great opportunities for objective surgical evaluation. In this paper, we introduce a predicti...

Machine learning to identify multigland disease in primary hyperparathyroidism.

The Journal of surgical research
BACKGROUND: 20%-25% of patients with primary hyperparathyroidism will have multigland disease (MGD). Preoperatative imaging can be inaccurate or unnecessary in MGD. Identification of MGD could direct the need for imaging and inform operative approach...

Kernel dynamic policy programming: Applicable reinforcement learning to robot systems with high dimensional states.

Neural networks : the official journal of the International Neural Network Society
We propose a new value function approach for model-free reinforcement learning in Markov decision processes involving high dimensional states that addresses the issues of brittleness and intractable computational complexity, therefore rendering the v...

Medical image classification via multiscale representation learning.

Artificial intelligence in medicine
Multiscale structure is an essential attribute of natural images. Similarly, there exist scaling phenomena in medical images, and therefore a wide range of observation scales would be useful for medical imaging measurements. The present work proposes...

Machine learning and microsimulation techniques on the prognosis of dementia: A systematic literature review.

PloS one
BACKGROUND: Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patien...

Turn Intent Detection For Control of a Lower Limb Prosthesis.

IEEE transactions on bio-medical engineering
OBJECTIVE: An adaptable lower limb prosthesis with variable stiffness in the transverse plane requires a control method to effect changes in real time during amputee turning. This study aimed to identify classification algorithms that can accurately ...