AIMC Topic: Precision Medicine

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Patient Similarity Networks for Precision Medicine.

Journal of molecular biology
Clinical research and practice in the 21st century is poised to be transformed by analysis of computable electronic medical records and population-level genome-scale patient profiles. Genomic data capture genetic and environmental state, providing in...

Sarcopenia: Beyond Muscle Atrophy and into the New Frontiers of Opportunistic Imaging, Precision Medicine, and Machine Learning.

Seminars in musculoskeletal radiology
As populations continue to age worldwide, the impact of sarcopenia on public health will continue to grow. The clinically relevant and increasingly common diagnosis of sarcopenia is at the confluence of three tectonic shifts in medicine: opportunisti...

Deep Patient Similarity Learning for Personalized Healthcare.

IEEE transactions on nanobioscience
Predicting patients' risk of developing certain diseases is an important research topic in healthcare. Accurately identifying and ranking the similarity among patients based on their historical records is a key step in personalized healthcare. The el...

Imaging, Health Record, and Artificial Intelligence: Hype or Hope?

Current cardiology reports
PURPOSE OF REVIEW: The review is focused on "digital health", which means advanced analytics based on multi-modal data. The "Health Care Internet of Things", which uses sensors, apps, and remote monitoring could provide continuous clinical informatio...

PhysOnline: An Open Source Machine Learning Pipeline for Real-Time Analysis of Streaming Physiological Waveform.

IEEE journal of biomedical and health informatics
Real-time analysis of streaming physiological data to identify earlier abnormal conditions is an important aspect of precision medicine. However, open-source systems supporting this workflow are lacking. In this paper, we present PhysOnline, a pipeli...

Evaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Electronic Health Records are electronic data generated during or as a byproduct of routine patient care. Structured, semi-structured and unstructured EHR offer researchers unprecedented phenotypic breadth and depth and have the potential to accelera...

Identification of Clinically Meaningful Plasma Transfusion Subgroups Using Unsupervised Random Forest Clustering.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Statistical techniques such as propensity score matching and instrumental variable are commonly employed to "simulate" randomization and adjust for measured confounders in comparative effectiveness research. Despite such adjustments, the results of t...

Data Analysis Strategies in Medical Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research
Radiographic imaging continues to be one of the most effective and clinically useful tools within oncology. Sophistication of artificial intelligence has allowed for detailed quantification of radiographic characteristics of tissues using predefined ...

Predicting cancer outcomes from histology and genomics using convolutional networks.

Proceedings of the National Academy of Sciences of the United States of America
Cancer histology reflects underlying molecular processes and disease progression and contains rich phenotypic information that is predictive of patient outcomes. In this study, we show a computational approach for learning patient outcomes from digit...

Using Big Data Analytics to Advance Precision Radiation Oncology.

International journal of radiation oncology, biology, physics
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...