AIMC Topic: Precision Medicine

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Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Translational psychiatry
Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and informative, the technical expertise and resources required to develop normative models may not be a...

Non-Invasive Biomarkers in the Era of Big Data and Machine Learning.

Sensors (Basel, Switzerland)
Invasive diagnostic techniques, while offering critical insights into disease pathophysiology, are often limited by high costs, procedural risks, and patient discomfort. Non-invasive biomarkers represent a transformative alternative, providing diagno...

Pharmacogenomics and response to lithium in bipolar disorder.

Pharmacogenomics
AIMS: The present review explores the existing evidence on pharmacogenomic tests for prediction of lithium response in the treatment of bipolar disorder. We focused our research article on reports describing findings from genome-wide association stud...

Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association.

Circulation. Genomic and precision medicine
Artificial intelligence is poised to transform cardio-oncology by enabling personalized care for patients with cancer, who are at a heightened risk of cardiovascular disease due to both the disease and its treatments. The rising prevalence of cancer ...

Utilizing natural language processing for precision prevention of mental health disorders among youth: A systematic review.

Computers in biology and medicine
BACKGROUND: The global mental health crisis has created barriers to youth mental healthcare, leaving many disorders unaddressed. Precision prevention, which identifies individual risks, offers the potential for tailored interventions. While natural l...

Intuitive Human-Artificial Intelligence Theranostic Complementarity.

Cancer biotherapy & radiopharmaceuticals
Deep learning artificial intelligence (AI) algorithms are poised to subsume diagnostic imaging specialists in radiology and nuclear medicine, where radiomics can consistently outperform human analysis and reporting capability, and do it faster, with ...

Elevating Research and Careers in the Development of Safer Drugs through Artificial Intelligence.

Chemical research in toxicology
The session "Elevating Research and Careers in the Development of Safer Drugs through Artificial Intelligence," held at the American Chemical Society meeting, showcased innovative methodologies that AI brings to drug development, from predictive mode...

Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges.

BMC cancer
BACKGROUND: The ability of machine learning (ML) to process and learn from large quantities of heterogeneous patient data is gaining attention in the precision oncology community. Some remarkable developments have taken place in the domain of image c...

Artificial intelligence and science of patient input: a perspective from people with multiple sclerosis.

Frontiers in immunology
Artificial intelligence (AI) can play a vital role in achieving a shift towards predictive, preventive, and personalized medicine, provided we are guided by the science with and of patient input. Patient-reported outcome measures (PROMs) represent a ...

Artificial intelligence for individualized treatment of persistent atrial fibrillation: a randomized controlled trial.

Nature medicine
Although pulmonary vein isolation (PVI) has become the cornerstone ablation procedure for atrial fibrillation (AF), the optimal ablation procedure for persistent and long-standing persistent AF remains elusive. Targeting spatio-temporal electrogram d...