Author(s): McKay MJ; Weber KA; Wesselink EO; Smith ZA; Abbott R; Anderson DB; Ashton-James CE; Atyeo J; Beach AJ; Burns J; Clarke S; Collins NJ; Coppieters MW; Cornwall J; Crawford RJ; De Martino E; Dunn AG; Eyles JP; Feng HJ; Fortin M; Franettovic ...

Disorders affecting the neurological and musculoskeletal systems represent international health priorities. A significant impediment to progress in trials of new therapies is the absence of responsive, objective, and valid outcome measures sensitive to early disease changes. A key finding in indi ...

Article GUID: 39590726

Author(s): Islam M; Zunair H; Mohammed N;

Crafting effective deep learning models for medical image analysis is a complex task, particularly in cases where the medical image dataset lacks significant inter-class variation. This challenge is further aggravated when employing such datasets to generate synthetic images using generative adversarial networks (GANs), as the output of GANs heavily relie ...

Article GUID: 38492455

Author(s): Vaz S; Mendes M; Khattar G; Macedo M; Ronquillo C; Zarzo-Arias A; Hortal J; Silveira L;

Background: We compiled a database of firefly species records from the Atlantic Forest hotspot in Brazil and made it available at GBIF. Data were gathered from literature and from several key entomological collections, including: Coleção entomológica Prof. José Alfredo Pinheiro Dutra (DZRJ/UFRJ) and Coleção do Laboratório de Ecologia de Insetos from Unive ...

Article GUID: 38327309

Author(s): Vu HL; Ng KTW; Richter A; An C;

The use of machine learning techniques in waste management studies is increasingly popular. Recent literature suggests k-fold cross validation may reduce input dataset partition uncertainties and minimize overfitting issues. The objectives are to quantify the benefits of k-fold cross validation for municipal waste disposal prediction and to identify the r ...

Article GUID: 35287077

Author(s): Masoumi N; Belasso CJ; Ahmad MO; Benali H; Xiao Y; Rivaz H;

Purpose: Accurate multimodal registration of intraoperative ultrasound (US) and preoperative computed tomography (CT) is a challenging problem. Construction of public datasets of US and CT images can accelerate the development of such image registration techniques. This can help ensure the accuracy and safety of spinal surgeries using image-guided surgery ...

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Author(s): Amini S, Kersten-Oertel M

Healthc Technol Lett. 2019 Dec;6(6):261-265 Authors: Amini S, Kersten-Oertel M

Article GUID: 32038868