AI Medical Compendium Topic:
Biomedical Research

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Future Vision 2020 and Beyond-5 Critical Trends in Eye Research.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
Ophthalmology has been at the forefront of many innovations in basic science and clinical research. The randomized prospective multicenter clinical trial, comparative clinical trials, the bench to beside development of diagnostic and therapeutic devi...

Structured reviews for data and knowledge-driven research.

Database : the journal of biological databases and curation
UNLABELLED: Hypothesis generation is a critical step in research and a cornerstone in the rare disease field. Research is most efficient when those hypotheses are based on the entirety of knowledge known to date. Systematic review articles are common...

Bio-AnswerFinder: a system to find answers to questions from biomedical texts.

Database : the journal of biological databases and curation
The ever accelerating pace of biomedical research results in corresponding acceleration in the volume of biomedical literature created. Since new research builds upon existing knowledge, the rate of increase in the available knowledge encoded in biom...

[Actively promoting the research and development of artificial intelligence diagnosis and treatment of orbital disease].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Medical artificial intelligence (AI) promotes technological revolution and industrial transformation in the medical field, and the medical level of orbital disease will also be improved with the in-depth development of AI diagnosis and treatment. The...

Characterizing the Scope of Exposome Research Through Topic Modeling and Ontology Analysis.

Studies in health technology and informatics
Exposomics is a field of research which is receiving growing attention. In this work, we characterize the exposome research landscape and update our previous study of formal knowledge representation approaches to this field. We applied a deductive an...

An Adversorial Approach to Enable Re-Use of Machine Learning Models and Collaborative Research Efforts Using Synthetic Unstructured Free-Text Medical Data.

Studies in health technology and informatics
We leverage Generative Adversarial Networks (GAN) to produce synthetic free-text medical data with low re-identification risk, and apply these to replicate machine learning solutions. We trained GAN models to generate free-text cancer pathology repor...