Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently...
Predictions of patient outcomes after a given therapy are fundamental to medical practice. We employ a machine learning approach towards predicting the outcomes after stereotactic radiosurgery for cerebral arteriovenous malformations (AVMs). Using th...
Genotype-phenotype studies aim to identify causative relationships between genes and phenotypes. The International Mouse Phenotyping Consortium is a high throughput phenotyping program whose goal is to collect phenotype data for a knockout mouse stra...
BACKGROUND: Knee osteoarthritis (OA) is the most common joint disease of adults worldwide. Since the treatments for advanced radiographic knee OA are limited, clinicians face a significant challenge of identifying patients who are at high risk of OA ...
IEEE journal of biomedical and health informatics
Feb 8, 2016
Detecting short-duration events from continuous sensor signals is a significant challenge in the domain of wearable devices and health monitoring systems. Time-series segmentation refers to the challenge of subdividing a continuous stream of data int...
Haemophilia : the official journal of the World Federation of Hemophilia
Feb 8, 2016
INTRODUCTION: Execution of total knee arthroplasty (TKA) in end-stage haemophilic arthropathy is challenging because of soft tissue fibrosis, flexion contractures, poor quality of the bone, and the altered bony anatomy. Restoring the lower limb align...
This paper presents a fully automated method for the identification of bone marrow infiltration in femurs in low-dose CT of patients with multiple myeloma. We automatically find the femurs and the bone marrow within them. In the next step, we create ...
BACKGROUND: Neurological impairments can limit the implementation of conventional cardiopulmonary exercise testing (CPET) and cardiovascular training strategies. A promising approach to provoke cardiovascular stress while facilitating task-specific e...
BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took acco...
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