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Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements - a pilot study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Intensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesi...

Random forest classifiers aid in the detection of incidental osteoblastic osseous metastases in DEXA studies.

International journal of computer assisted radiology and surgery
PURPOSE: Dual-energy X-ray absorptiometry (DEXA) studies are used for screening patients for low bone mineral density (BMD). Patients with breast and prostate cancer are often treated with hormone-altering drugs that result in low BMD. These patients...

Pilot Testing a Robot for Reducing Pain in Hospitalized Preterm Infants.

OTJR : occupation, participation and health
Optimizing neurodevelopment is a key goal of neonatal occupational therapy. In preterm infants, repeated procedural pain is associated with adverse effects on neurodevelopment long term. Calmer is a robot designed to reduce infant pain. The objective...

Machine learning vs addiction therapists: A pilot study predicting alcohol dependence treatment outcome from patient data in behavior therapy with adjunctive medication.

Journal of substance abuse treatment
BACKGROUND AND OBJECTIVES: Clinical staff providing addiction treatment predict patient outcome poorly. Prognoses based on linear statistics are rarely replicated. Addiction is a complex non-linear behavior. Incorporating non-linear models, Machine L...

Machine Learning Can Improve Estimation of Surgical Case Duration: A Pilot Study.

Journal of medical systems
Operating room (OR) utilization is a significant determinant of hospital profitability. One aspect of this is surgical scheduling, which depends on accurate predictions of case duration. This has been done historically by either the surgeon based on ...

Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks.

International journal of neural systems
Numerous nonepileptic paroxysmal events, such as syncope and psychogenic nonepileptic seizures, may imitate seizures and impede diagnosis. Misdiagnosis can lead to mistreatment, affecting patients' lives considerably. Electroencephalography is common...

Automatically Evaluating Balance: A Machine Learning Approach.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Compared to in-clinic balance training, in-home training is not as effective. This is, in part, due to the lack of feedback from physical therapists (PTs). In this paper, we analyze the feasibility of using trunk sway data and machine learning (ML) t...

Survival outcome prediction in cervical cancer: Cox models vs deep-learning model.

American journal of obstetrics and gynecology
BACKGROUND: Historically, the Cox proportional hazard regression model has been the mainstay for survival analyses in oncologic research. The Cox proportional hazard regression model generally is used based on an assumption of linear association. How...

Assistive robots for socialization in elderly people: results pertaining to the needs of the users.

Aging clinical and experimental research
BACKGROUND/AIM: Technological solutions can support the elderly, improve their quality of life and reduce isolation and loneliness. The Euro-Japan ACCRA (Agile Co-Creation for Robots and Aging) project has the objective of building a reference co-cre...