Lost in translation: the valley of death across preclinical and clinical divide–identification of problems and overcoming obstacles
AA Seyhan - Translational Medicine Communications, 2019 - Springer
A rift that has opened up between basic research (bench) and clinical research and patients
(bed) who need their new treatments, diagnostics and prevention, and this rift is widening …
(bed) who need their new treatments, diagnostics and prevention, and this rift is widening …
Deep learning and the electrocardiogram: review of the current state-of-the-art
In the recent decade, deep learning, a subset of artificial intelligence and machine learning,
has been used to identify patterns in big healthcare datasets for disease phenotyping, event …
has been used to identify patterns in big healthcare datasets for disease phenotyping, event …
The 'Digital Twin'to enable the vision of precision cardiology
J Corral-Acero, F Margara, M Marciniak… - European heart …, 2020 - academic.oup.com
Providing therapies tailored to each patient is the vision of precision medicine, enabled by
the increasing ability to capture extensive data about individual patients. In this position …
the increasing ability to capture extensive data about individual patients. In this position …
Artificial intelligence in cardiology
Artificial intelligence and machine learning are poised to influence nearly every aspect of the
human condition, and cardiology is not an exception to this trend. This paper provides a …
human condition, and cardiology is not an exception to this trend. This paper provides a …
Exploiting machine learning for end-to-end drug discovery and development
A variety of machine learning methods such as naive Bayesian, support vector machines
and more recently deep neural networks are demonstrating their utility for drug discovery …
and more recently deep neural networks are demonstrating their utility for drug discovery …
Machine learning in cardiovascular medicine: are we there yet?
Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from
data, allowing computers to find hidden insights without being explicitly programmed where …
data, allowing computers to find hidden insights without being explicitly programmed where …
Deep-learning cardiac motion analysis for human survival prediction
Motion analysis is used in computer vision to understand the behaviour of moving objects in
sequences of images. Optimizing the interpretation of dynamic biological systems requires …
sequences of images. Optimizing the interpretation of dynamic biological systems requires …
Artificial intelligence: practical primer for clinical research in cardiovascular disease
Artificial intelligence (AI) has begun to permeate and reform the field of medicine and
cardiovascular medicine. Impacting about 100 million patients in the United States, the …
cardiovascular medicine. Impacting about 100 million patients in the United States, the …
2017 Roadmap for innovation—ACC health policy statement on healthcare transformation in the era of digital health, big data, and precision health: a report of the …
Healthcare transformation is the product of a shared vision between a broad range of
stakeholders to establish the future of care delivery and to develop new patient-centered …
stakeholders to establish the future of care delivery and to develop new patient-centered …
Relevance of multi-omics studies in cardiovascular diseases
P Leon-Mimila, J Wang… - Frontiers in cardiovascular …, 2019 - frontiersin.org
Cardiovascular diseases are the leading cause of death around the world. Despite the
larger number of genes and loci identified, the precise mechanisms by which these genes …
larger number of genes and loci identified, the precise mechanisms by which these genes …