5,158 research outputs found
Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset Session.
At the first annual Conference on Machine Intelligence in Medical Imaging (C-MIMI), held in September 2016, a conference session on medical image data and datasets for machine learning identified multiple issues. The common theme from attendees was that everyone participating in medical image evaluation with machine learning is data starved. There is an urgent need to find better ways to collect, annotate, and reuse medical imaging data. Unique domain issues with medical image datasets require further study, development, and dissemination of best practices and standards, and a coordinated effort among medical imaging domain experts, medical imaging informaticists, government and industry data scientists, and interested commercial, academic, and government entities. High-level attributes of reusable medical image datasets suitable to train, test, validate, verify, and regulate ML products should be better described. NIH and other government agencies should promote and, where applicable, enforce, access to medical image datasets. We should improve communication among medical imaging domain experts, medical imaging informaticists, academic clinical and basic science researchers, government and industry data scientists, and interested commercial entities
Recommended from our members
Implementing a mobile diagnostic unit to increase access to imaging and laboratory services in western Kenya.
Access to basic imaging and laboratory services remains a major challenge in rural, resource-limited settings in sub-Saharan Africa. In 2016, the Academic Model Providing Access to Healthcare programme in western Kenya implemented a mobile diagnostic unit (MDU) outfitted with a generator-powered X-ray machine and basic laboratory tests to address the lack of these services at rural, low-resource, public health facilities. The objective of this paper is to describe the design, implementation, preliminary impact and operational challenges of the MDU in western Kenya. Since implementing the MDU at seven rural health facilities serving a catchment of over half a million people, over 4500 chest radiographs have been performed, with one or more abnormalities detected in approximately 30% of radiographs. We observed favorable feedback and uptake of MDU services by healthcare workers and patients. However, various operational challenges in the design and construction of the MDU and the transmission and reporting of radiographs in remote areas were encountered. Our experience supports the feasibility of deploying an MDU to increase access to basic radiology and laboratory services in rural, resource-limited settings
Magneto-optical Kerr Effect Studies of Square Artificial Spin Ice
We report a magneto-optical Kerr effect study of the collective magnetic
response of artificial square spin ice, a lithographically-defined array of
single-domain ferromagnetic islands. We find that the anisotropic inter-island
interactions lead to a non-monotonic angular dependence of the array coercive
field. Comparisons with micromagnetic simulations indicate that the two
perpendicular sublattices exhibit distinct responses to island edge roughness,
which clearly influence the magnetization reversal process. Furthermore, such
comparisons demonstrate that disorder associated with roughness in the island
edges plays a hitherto unrecognized but essential role in the collective
behavior of these systems.Comment: Physical Review B, Rapid Communications (in press
Global Sourcing of IT Services: Necessary Evil or Blessing in Disguise?
Firms use information systems to reduce the costs of doing business and create innovative applications and products for competitive advantage. IT outsourcing, often to overseas locations, appears to have accomplished efficiency improvements. However, firms increasingly employ global sourcing of IT services for other purposes, such as to broaden the scope of provided services and for strategic considerations. Given the complexities of emergent forms of global IT sourcing - away from arm\u27s length transactions and toward highly integrated relationships - the purpose of this panel, originally presented at the 2006 International Conference on Information Systems, was to shed light on the issue of global sourcing of IT services by examining three interrelated questions: 1) Is this more about efficiency or strategic considerations? 2) What new conceptual frameworks and theory bases are appropriate for studies of global IT sourcing? and 3) What skills are required of managers and what should we be teaching our students
Algorithmic assessment of cellular senescence in experimental and clinical specimens
The development of genetic tools allowed for the validation of the pro-aging and pro-disease functions of senescent cells in vivo. These discoveries prompted the development of senotherapies—pharmaceutical interventions aimed at interfering with the detrimental effect of senescent cells—that are now entering the clinical stage. However, unequivocal identification and examination of cellular senescence remains highly difficult because of the lack of universal and specific markers. Here, to overcome the limitation of measuring individual markers, we describe a detailed two-phase algorithmic assessment to quantify various senescence-associated parameters in the same specimen. In the first phase, we combine the measurement of lysosomal and proliferative features with the expression of general senescence-associated genes to validate the presence of senescent cells. In the second phase we measure the levels of pro-inflammatory markers for specification of the type of senescence. The protocol can help graduate-level basic scientists to improve the characterization of senescence-associated phenotypes and the identification of specific senescent subtypes. Moreover, it can serve as an important tool for the clinical validation of the role of senescent cells and the effectiveness of anti-senescence therapies
Choice of antibiotics for prophylaxis of bacterial STIs among individuals currently self-sourcing.
Integrated whole transcriptome and DNA methylation analysis identifies gene networks specific to late-onset Alzheimer’s disease
Previous transcriptome studies observed disrupted cellular processes in late-onset Alzheimer\u27s disease (LOAD), yet it is unclear whether these changes are specific to LOAD, or are common to general neurodegeneration. In this study, we address this question by examining transcription in LOAD and comparing it to cognitively normal controls and a cohort of disease controls. Differential transcription was examined using RNA-seq, which allows for the examination of protein coding genes, non-coding RNAs, and splicing. Significant transcription differences specific to LOAD were observed in five genes: C10orf105, DIO2, a lincRNA, RARRES3, and WIF1. These findings were replicated in two independent publicly available microarray data sets. Network analyses, performed on 2,504 genes with moderate transcription differences in LOAD, reveal that these genes aggregate into seven networks. Two networks involved in myelination and innate immune response specifically correlated to LOAD. FRMD4B and ST18, hub genes within the myelination network, were previously implicated in LOAD. Of the five significant genes, WIF1 and RARRES3 are directly implicated in the myelination process; the other three genes are located within the network. LOAD specific changes in DNA methylation were located throughout the genome and substantial changes in methylation were identified within the myelination network. Splicing differences specific to LOAD were observed across the genome and were decreased in all seven networks. DNA methylation had reduced influence on transcription within LOAD in the myelination network when compared to both controls. These results hint at the molecular underpinnings of LOAD and indicate several key processes, genes, and networks specific to the disease
Simultaneous segmentation and pose estimation of humans using dynamic graph cuts
This paper presents a novel algorithm for performing inte-
grated segmentation and 3D pose estimation of a human body from mul-
tiple views. Unlike other state of the art methods which focus on either
segmentation or pose estimation individually, our approach tackles these
two tasks together. Our method works by optimizing a cost function
based on a Conditional Random Field (CRF). This has the advantage
that all information in the image (edges, background and foreground ap-
pearances), as well as the prior information on the shape and pose of the
subject can be combined and used in a Bayesian framework. Optimizing
such a cost function would have been computationally infeasible. How-
ever, our recent research in dynamic graph cuts allows this to be done
much more efficiently than before. We demonstrate the efficacy of our ap-
proach on challenging motion sequences. Although we target the human
pose inference problem in the paper, our method is completely generic
and can be used to segment and infer the pose of any rigid, deformable
or articulated object
- …