AIMC Topic: Translational Research, Biomedical

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Character level and word level embedding with bidirectional LSTM - Dynamic recurrent neural network for biomedical named entity recognition from literature.

Journal of biomedical informatics
Named Entity Recognition is the process of identifying different entities in a given context. Biomedical Named Entity Recognition (BNER) is the task of extracting chemical names from biomedical texts to support biomedical and translational research. ...

Precision Medicine, AI, and the Future of Personalized Health Care.

Clinical and translational science
The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less-common responses to treatment or unique healthcare needs. AI leverages ...

Ontologies, Knowledge Representation, and Machine Learning for Translational Research: Recent Contributions.

Yearbook of medical informatics
OBJECTIVES: To select, present, and summarize the most relevant papers published in 2018 and 2019 in the field of Ontologies and Knowledge Representation, with a particular focus on the intersection between Ontologies and Machine Learning.

Gut microbiome, big data and machine learning to promote precision medicine for cancer.

Nature reviews. Gastroenterology & hepatology
The gut microbiome has been implicated in cancer in several ways, as specific microbial signatures are known to promote cancer development and influence safety, tolerability and efficacy of therapies. The 'omics' technologies used for microbiome anal...

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.

Scientific reports
Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive pi...

Translating big data to better treatment in bipolar disorder - a manifesto for coordinated action.

European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Bipolar disorder (BD) is a major healthcare and socio-economic challenge. Despite its substantial burden on society, the research activity in BD is much smaller than its economic impact appears to demand. There is a consensus that the accurate identi...

Data-driven translational prostate cancer research: from biomarker discovery to clinical decision.

Journal of translational medicine
Prostate cancer (PCa) is a common malignant tumor with increasing incidence and high heterogeneity among males worldwide. In the era of big data and artificial intelligence, the paradigm of biomarker discovery is shifting from traditional experimenta...

Big data in IBD: big progress for clinical practice.

Gut
IBD is a complex multifactorial inflammatory disease of the gut driven by extrinsic and intrinsic factors, including host genetics, the immune system, environmental factors and the gut microbiome. Technological advancements such as next-generation se...

Harnessing big 'omics' data and AI for drug discovery in hepatocellular carcinoma.

Nature reviews. Gastroenterology & hepatology
Hepatocellular carcinoma (HCC) is the most common form of primary adult liver cancer. After nearly a decade with sorafenib as the only approved treatment, multiple new agentsĀ have demonstrated efficacy in clinical trials, including the targeted thera...