AIMC Topic: Precision Medicine

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Towards a Precision Medicine Approach Based on Machine Learning for Tailoring Medical Treatment in Alkaptonuria.

International journal of molecular sciences
ApreciseKUre is a multi-purpose digital platform facilitating data collection, integration and analysis for patients affected by Alkaptonuria (AKU), an ultra-rare autosomal recessive genetic disease. It includes genetic, biochemical, histopathologica...

Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model.

Physics in medicine and biology
Digital tomosynthesis (DTS) has been proposed as a fast low-dose imaging technique for image-guided radiation therapy (IGRT). However, due to the limited scanning angle, DTS reconstructed by the conventional FDK method suffers from significant distor...

Machine Learning Techniques for Personalized Detection of Epileptic Events in Clinical Video Recordings.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan i...

Current cancer driver variant predictors learn to recognize driver genes instead of functional variants.

BMC biology
BACKGROUND: Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenes...

A new precision medicine initiative at the dawn of exascale computing.

Signal transduction and targeted therapy
Which signaling pathway and protein to select to mitigate the patient's expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current app...

Semi-supervised learning for somatic variant calling and peptide identification in personalized cancer immunotherapy.

BMC bioinformatics
BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor r...

Imaging Beyond Seeing: Early Prognosis of Cancer Treatment.

Small methods
Assessing cancer response to therapeutic interventions has been realized as an important course to early predict curative efficacy and treatment outcomes due to tumor heterogeneity. Compared to the traditional invasive tissue biopsy method, molecular...

Detection of transient neurotransmitter response using personalized neural networks.

Physics in medicine and biology
Measurement of stimulus-induced dopamine release and other types of transient neurotransmitter response (TNR) from dynamic positron emission tomography (PET) images typically suffers from limited detection sensitivity and high false positive (FP) rat...

How wide is the application of genetic big data in biomedicine.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
In the era of big data, massive genetic data, as a new industry, has quickly swept almost all industries, especially the pharmaceutical industry. As countries around the world start to build their own gene banks, scientists study the data to explore ...

Precision medicine in the era of artificial intelligence: implications in chronic disease management.

Journal of translational medicine
Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflamm...