AIMC Topic: Precision Medicine

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3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients.

Nature communications
Cochlear implants restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding stimulus current spread, and how it correlates to patient-dependent factors, is hampered by the poor acc...

Using predictive machine learning models for drug response simulation by calibrating patient-specific pathway signatures.

NPJ systems biology and applications
The utility of pathway signatures lies in their capability to determine whether a specific pathway or biological process is dysregulated in a given patient. These signatures have been widely used in machine learning (ML) methods for a variety of appl...

Empowering study of breast cancer data with application of artificial intelligence technology: promises, challenges, and use cases.

Clinical & experimental metastasis
In healthcare, artificial intelligence (AI) technologies have the potential to create significant value by improving time-sensitive outcomes while lowering error rates for each patient. Diagnostic images, clinical notes, and reports are increasingly ...

Interpretable machine learning for genomics.

Human genetics
High-throughput technologies such as next-generation sequencing allow biologists to observe cell function with unprecedented resolution, but the resulting datasets are too large and complicated for humans to understand without the aid of advanced sta...

The Future Role of High-Performance Computing in Cardiovascular Medicine and Science -Impact of Multi-Dimensional Data Analysis.

Journal of atherosclerosis and thrombosis
Advances in High-performance computing (HPC) technology have reached the capacity to inform cardiovascular (CV) science in the realm of both inductive and constructive approaches. Clinical trials allow for the comparison of the effect of an intervent...

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium.

BMC medical informatics and decision making
BACKGROUND: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their im...

Deep learning in cancer diagnosis, prognosis and treatment selection.

Genome medicine
Deep learning is a subdiscipline of artificial intelligence that uses a machine learning technique called artificial neural networks to extract patterns and make predictions from large data sets. The increasing adoption of deep learning across health...

Application of Artificial Intelligence in Cardiovascular Medicine.

Comprehensive Physiology
The advent of advances in machine learning (ML)-based techniques has popularized wide applications of artificial intelligence (AI) in various fields ranging from robotics to medicine. In recent years, there has been a surge in the application of AI t...

Artificial intelligence-enhanced drug design and development: Toward a computational precision medicine.

Drug discovery today
Artificial Intelligence (AI) relies upon a convergence of technologies with further synergies with life science technologies to capture the value of massive multi-modal data in the form of predictive models supporting decision-making. AI and machine ...

Identification of clinical trait-related small RNA biomarkers with weighted gene co-expression network analysis for personalized medicine in endocervical adenocarcinoma.

Aging
Endocervical adenocarcinoma (EAC) is an aggressive type of endocervical cancer. At present, molecular research on EAC mainly focuses on the genome and mRNA transcriptome, the investigation of small RNAs in EAC has not been fully described. Here, we s...