An overview of artificial intelligence in oncology.
Eduardo Moreno Júdice De Mattos FarinaJacqueline Justino NabhenMaria Inez DacoregioFelipe BataliniFabio Ynoe de MoraesPublished in: Future science OA (2022)
Cancer is associated with significant morbimortality globally. Advances in screening, diagnosis, management and survivorship were substantial in the last decades, however, challenges in providing personalized and data-oriented care remain. Artificial intelligence (AI), a branch of computer science used for predictions and automation, has emerged as potential solution to improve the healthcare journey and to promote precision in healthcare. AI applications in oncology include, but are not limited to, optimization of cancer research, improvement of clinical practice (eg., prediction of the association of multiple parameters and outcomes - prognosis and response) and better understanding of tumor molecular biology. In this review, we examine the current state of AI in oncology, including fundamentals, current applications, limitations and future perspectives.
Keyphrases
- artificial intelligence
- healthcare
- big data
- deep learning
- palliative care
- machine learning
- papillary thyroid
- clinical practice
- squamous cell
- childhood cancer
- public health
- lymph node metastasis
- quality improvement
- type diabetes
- risk assessment
- pain management
- affordable care act
- climate change
- chronic pain
- single molecule