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Graph Embedded Extreme Learning Machine.

IEEE transactions on cybernetics
In this paper, we propose a novel extension of the extreme learning machine (ELM) algorithm for single-hidden layer feedforward neural network training that is able to incorporate subspace learning (SL) criteria on the optimization process followed f...

Use of a robotic device for the rehabilitation of severe upper limb paresis in subacute stroke: exploration of patient/robot interactions and the motor recovery process.

BioMed research international
This pioneering observational study explored the interaction between subacute stroke inpatients and a rehabilitation robot during upper limb training. 25 stroke survivors (age 55 ± 17 years; time since stroke, 52 ± 21 days) with severe upper limb par...

Applying under-sampling techniques and cost-sensitive learning methods on risk assessment of breast cancer.

Journal of medical systems
Breast cancer is one of the most common cause of cancer mortality. Early detection through mammography screening could significantly reduce mortality from breast cancer. However, most of screening methods may consume large amount of resources. We pro...

Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also ...

Searching for a minimal set of behaviors for autism detection through feature selection-based machine learning.

Translational psychiatry
Although the prevalence of autism spectrum disorder (ASD) has risen sharply in the last few years reaching 1 in 68, the average age of diagnosis in the United States remains close to 4--well past the developmental window when early intervention has t...

Robot-assisted surgery for gastric carcinoma: Five years follow-up and beyond: A single western center experience and long-term oncological outcomes.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: Robot-assisted surgery for the treatment of gastric cancer is considered to be safe and feasible with early post-operative outcomes comparable to open and laparoscopic series. However, data regarding long-term oncological outcomes are l...

The influence of push-off timing in a robotic ankle-foot prosthesis on the energetics and mechanics of walking.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robotic ankle-foot prostheses that provide net positive push-off work can reduce the metabolic rate of walking for individuals with amputation, but benefits might be sensitive to push-off timing. Simple walking models suggest that preempt...

Design and user evaluation of a wheelchair mounted robotic assisted transfer device.

BioMed research international
PURPOSE: The aim of this study is to describe the robotic assisted transfer device (RATD) and an initial focus group evaluation by end users. The purpose of the device is to aid in the transfers of people with disabilities to and from their electric ...

Port-site metastases in patients with gynecological cancer after robot-assisted operations.

Archives of gynecology and obstetrics
INTRODUCTION: Port-site metastasis is an extremely rare event in patients with cancer treated with robotic-assisted surgery. However, as robotic procedures are increasing, the incidence of port-site metastases might also increase. The purpose of our ...

Comparison of machine classification algorithms for fibromyalgia: neuroimages versus self-report.

The journal of pain
UNLABELLED: Recent studies have posited that machine learning (ML) techniques accurately classify individuals with and without pain solely based on neuroimaging data. These studies claim that self-report is unreliable, making "objective" neuroimaging...