OBJECTIVE: In this paper, we propose to evaluate the use of pre-trained convolutional neural networks (CNNs) as a features extractor followed by the Principal Component Analysis (PCA) to find the best discriminant features to perform classification u...
IEEE journal of biomedical and health informatics
Nov 4, 2020
Classical drug design methodologies are hugely costly and time-consuming, with approximately 85% of the new proposed molecules failing in the first three phases of the FDA drug approval process. Thus, strategies to find alternative indications for al...
IEEE journal of biomedical and health informatics
Nov 4, 2020
The paucity of physiological time-series data collected from low-resource clinical settings limits the capabilities of modern machine learning algorithms in achieving high performance. Such performance is further hindered by class imbalance; datasets...
IEEE journal of biomedical and health informatics
Nov 4, 2020
There has been increasing interest in modelling survival data using deep learning methods in medical research. Current approaches have focused on designing special cost functions to handle censored survival data. We propose a very different method wi...
International journal of chronic obstructive pulmonary disease
Nov 4, 2020
PURPOSE: Patients with chronic obstructive pulmonary disease (COPD) would have a poor prognosis if they were not continuously managed according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. We aim to develop a model...
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Nov 3, 2020
PURPOSE: The aim of this study was to develop an algorithm for automated estimation of patient height and weight during computed tomography (CT) and to evaluate its accuracy in everyday clinical practice.
BACKGROUND: This study develops machine learning (ML) algorithms that use preoperative-only features to predict discharge-to-nonhome-facility (DNHF) and length-of-stay (LOS) following complex head and neck surgeries.
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Nov 3, 2020
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboratio...
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Nov 3, 2020
The application of big data, radiomics, machine learning, and artificial intelligence (AI) algorithms in radiology requires access to large data sets containing personal health information. Because machine learning projects often require collaboratio...
European journal of pain (London, England)
Nov 3, 2020
BACKGROUND: In pain research and clinics, it is common practice to subgroup subjects according to shared pain characteristics. This is often achieved by computer-aided clustering. In response to a recent EU recommendation that computer-aided decision...
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