Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges

Radiomics leverages existing image datasets to provide non-visible data extraction via image post-processing, with the aim of identifying prognostic, and predictive imaging features at a sub-region of interest level. However, the application of radiomics is hampered by several challenges such as lack of image acquisition/analysis method standardization, impeding generalizability. As of yet, radiomics remains intriguing, but not clinically validated. We aimed to test the feasibility of a non-custom-constructed platform for disseminating existing large, standardized databases across institutions for promoting radiomics studies. Hence, University of Texas MD Anderson Cancer Center organized two public radiomics challenges in head and neck radiation oncology domain. This was done in conjunction with MICCAI 2016 satellite symposium using Kaggle-in-Class, a machine-learning and predictive analytics platform. We drew on clinical data matched to radiomics data derived from diagnostic contrast-enhanced computed tomography (CECT) images in a dataset of 315 patients with oropharyngeal cancer. Contestants were tasked to develop models for (i) classifying patients according to their human papillomavirus status, or (ii) predicting local tumor recurrence, following radiotherapy. Data were split into training, and test sets. Seventeen teams from various professional domains participated in one or both of the challenges. This review paper was based on the contestants' feedback; provided by 8 contestants only (47%). Six contestants (75%) incorporated extracted radiomics features into their predictive model building, either alone (n = 5; 62.5%), as was the case with the winner of the “HPV” challenge, or in conjunction with matched clinical attributes (n = 2; 25%). Only 23% of contestants, notably, including the winner of the “local recurrence” challenge, built their model relying solely on clinical data. In addition to the value of the integration of machine learning into clinical decision-making, our experience sheds light on challenges in sharing and directing existing datasets toward clinical applications of radiomics, including hyper-dimensionality of the clinical/imaging data attributes. Our experience may help guide researchers to create a framework for sharing and reuse of already published data that we believe will ultimately accelerate the pace of clinical applications of radiomics; both in challenge or clinical settings

Extracorporeal Shockwave Therapy in the Treatment of Nonunion in Long Bones: A Systematic Review and Meta-Analysis

Background: Nonunion is one of the most challenging problems in the field of orthopedics. The aim of this study was to perform a systematic review of the literature to evaluate the effectiveness of extracorporeal shockwave therapy (ESWT) in the treatment of nonunion in long bones. Methods: We conducted a search of three databases (PubMed, Scopus, and Web of Science) and found 646 total publications, of which 23 met our inclusion criteria. Results: Out of 1200 total long bone nonunions, 876 (73%) healed after being treated with ESWT. Hypertrophic cases achieved 3-fold higher healing rates when compared to oligotrophic or atrophic cases (p = 0.003). Metatarsal bones were the most receptive to ESWT, achieving a healing rate of 90%, followed by tibiae (75.54%), femurs (66.9%) and humeri (63.9%). Short periods between injury and treatment lead to higher healing rates (p < 0.02). Conversely, 6 months of follow-up after the treatment appears to be too brief to evaluate the full healing potential of the treatment; several studies showed that healing rates continued to increase at follow-ups beyond 6 months after the last ESWT treatment (p < 0.01). Conclusions: ESWT is a promising approach for treating nonunions. At present, a wide range of treatment protocols are used, and more research is needed to determine which protocols are the most effective

Extracorporeal Shockwave Therapy in the Treatment of Nonunion in Long Bones: A Systematic Review and Meta-Analysis

Background: Nonunion is one of the most challenging problems in the field of orthopedics. The aim of this study was to perform a systematic review of the literature to evaluate the effectiveness of extracorporeal shockwave therapy (ESWT) in the treatment of nonunion in long bones. Methods: We conducted a search of three databases (PubMed, Scopus, and Web of Science) and found 646 total publications, of which 23 met our inclusion criteria. Results: Out of 1200 total long bone nonunions, 876 (73%) healed after being treated with ESWT. Hypertrophic cases achieved 3-fold higher healing rates when compared to oligotrophic or atrophic cases (p = 0.003). Metatarsal bones were the most receptive to ESWT, achieving a healing rate of 90%, followed by tibiae (75.54%), femurs (66.9%) and humeri (63.9%). Short periods between injury and treatment lead to higher healing rates (p p < 0.01). Conclusions: ESWT is a promising approach for treating nonunions. At present, a wide range of treatment protocols are used, and more research is needed to determine which protocols are the most effective

The “Minimum Information about an ENvironmental Sequence” (MIENS) specification

We present the Genomic Standards Consortium’s (GSC) “Minimum Information about an ENvironmental Sequence” (MIENS) standard for describing marker genes. Adoption of MIENS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biospher

222nd ENMC International Workshop: Myotonic dystrophy, developing a European consortium for care and therapy, Naarden, The Netherlands, 1–2 July 2016

No abstract available

Off the Lip Conference - Transdisciplinary Approaches to Cognitive Innovation. Conference Proceedings

The promise of cognitive innovation as a collaborative project in the sciences, arts and humanities is that we can approach creativity as a bootstrapping cognitive process in which the energies that shape the poem are necessarily indistinguishable from those that shape the poet. For the purposes of this conference the exploration of the idea of cognitive innovation concerns an understanding of creativity that is not exclusively concerned with conscious human thought and action but also as intrinsic to our cognitive development. As a consequence, we see the possibility for cognitive innovation to provide a theoretical and practical platform from which to address disciplinary differences in ways that offer new topics and concerns for research in the sciences and the humanities.The Off the Lip conference was funded by the FP7 Marie Curie Action ITN CogNov

The future of metabolomics in ELIXIR [version 1; referees: 2 approved, 1 approved with reservations]

Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases