AIMC Topic: Precision Medicine

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Radiogenomics in prostate cancer evaluation.

Current opinion in urology
PURPOSE OF REVIEW: Radiogenomics, fusion between radiomics and genomics, represents a new field of research to improve cancer comprehension and evaluation. In this review, we give an overview of radiogenomics and its most recent and relevant applicat...

Machine learning and network medicine: a novel approach for precision medicine and personalized therapy in cardiomyopathies.

Journal of cardiovascular medicine (Hagerstown, Md.)
The early identification of pathogenic mechanisms is essential to predict the incidence and progression of cardiomyopathies and to plan appropriate preventive interventions. Noninvasive cardiac imaging such as cardiac computed tomography, cardiac mag...

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Cell reports
Although clinical and laboratory data have long been used to guide medical practice, this information is rarely integrated with multi-omic data to identify endotypes. We present Merged Affinity Network Association Clustering (MANAclust), a coding-fre...

Artificial Intelligence in Cancer Research and Precision Medicine.

Cancer discovery
Artificial intelligence (AI) is rapidly reshaping cancer research and personalized clinical care. Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has...

Opportunities and challenges for the computational interpretation of rare variation in clinically important genes.

American journal of human genetics
Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic vari...

Deep learning for brain disorders: from data processing to disease treatment.

Briefings in bioinformatics
In order to reach precision medicine and improve patients' quality of life, machine learning is increasingly used in medicine. Brain disorders are often complex and heterogeneous, and several modalities such as demographic, clinical, imaging, genetic...

Deep learning in systems medicine.

Briefings in bioinformatics
Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features nee...

Importance-aware personalized learning for early risk prediction using static and dynamic health data.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Accurate risk prediction is important for evaluating early medical treatment effects and improving health care quality. Existing methods are usually designed for dynamic medical data, which require long-term observations. Meanwhile, import...

Swarming behavior and in vivo monitoring of enzymatic nanomotors within the bladder.

Science robotics
Enzyme-powered nanomotors are an exciting technology for biomedical applications due to their ability to navigate within biological environments using endogenous fuels. However, limited studies into their collective behavior and demonstrations of tra...