In this paper, we propose a novel neural network architecture for clinical text mining. We formulate this hybrid neural network model (HNN), composed of recurrent neural network and deep residual network, to jointly predict the presence and period as...
Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN frame...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 4, 2018
The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features ...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Mar 27, 2018
PURPOSE: Noticing the fast growing translation of artificial intelligence (AI) technologies to medical image analysis this paper emphasizes the future role of the medical physicist in this evolving field. Specific challenges are addressed when implem...
Additional value can be potentially created by applying big data tools to address pharmacometric problems. The performances of machine learning (ML) methods and the Cox regression model were evaluated based on simulated time-to-event data synthesized...
International journal of radiation oncology, biology, physics
Mar 2, 2018
Big clinical data analytics as a primary component of precision medicine is discussed, identifying where these emerging tools fit in the spectrum of genomics and radiomics research. A learning health system (LHS) is conceptualized that uses clinicall...
In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, who...
BACKGROUND: Pathological angiogenesis has been identified in many malignancies as a potential prognostic factor and target for therapy. In most cases, angiogenic analysis is based on the measurement of microvessel density (MVD) detected by immunostai...
The adaptive immune system recognizes antigens an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in...
IEEE journal of biomedical and health informatics
Feb 8, 2018
Due to the importance of nuclear structure in cancer diagnosis, several predictive models have been described for diagnosing a wide variety of cancers based on nuclear morphology. In many computer-aided diagnosis (CAD) systems, cancer detection tasks...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.