About this Research Topic
Driven by advances in computational power, innovative algorithms, and ever-increasing amount of data, the last decade has witnessed widespread applications of Artificial Intelligence (AI) in medicine and healthcare. AI is a broad concept of training machines to think and behave like humans. It consists of a wide range of statistical and machinal leaning approaches with a specific emphasis on learning from the existing data/information to predict future outcomes. The concept of AI was introduced during the 1950s, but its critical role in a broad range of applications has yet to be realized. The 21st century health science has increasingly used novel tools that generate information beyond conventional structured tabular “data”, such as imaging data. Meanwhile, newfangled AI methodologies, such as deep learning are capable of extracting complex patterns from multifaceted data streams.
This Research Topic is intended to present some of the state-of-the-art developments of artificial intelligence in precision health. In close collaboration with human intelligence, AI technologies can bring about more effective and personalized healthcare. Potential topics include, but are not limited to:
• Precision medicine / therapeutics
• Precision agriculture
• Drug discovery and development
• Clinical diagnosis and prognosis
• COVID-19
• Cancer research
• Natural language processing
• Regulatory science
• AI and data science methodology.
• Radiomics and quantitative imaging
• Innovative AI applications for patient privacy and security
Keywords: precision health, artificial intelligence, data science, machine learning, AI/ML, Genomics, Drug Discovery/Safety, Radiomics, Food safety, Clinical
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