Artificial Intelligence and Machine Learning in Precision Oncology
A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".
Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 16640
Special Issue Editors
Interests: cancer; clinical trials; drug development; drug discovery; artificial intelligence; machine learning
Special Issue Information
Dear Colleagues,
We live in an era where artificial intelligence (AI) is touching and radically transforming every aspect of our lives and the fabric of our society, whether it is self-driving cars, smart digital assistants, clever chatbots, metaverse, or incredible digital art created by OpenAI’s DALL·E system.
The goal of AI is to create intelligent systems capable of emulating human intellect and intelligence. Machine learning (ML), a subset of AI, is any approach that allows machines to learn patterns and gain knowledge from previously provided data without explicitly programming, as well as make predictions on new data.
AI is causing a paradigm shift in scientific research. In precision oncology, AI is reshaping the existing scenario, aiming to integrate and interpret large amounts of patients’ data with current advances in high-performance computing and groundbreaking deep-learning strategies for better treatment decisions.
This special issue of Cancers is focused on the applications of AI/ML in precision oncology and cancer research. This include, but is not limited to, new AI/ML approaches for cancer detection, screening, diagnosis, and classification, as well as the characterization of the cancer genome, the analysis of tumor microenvironment, the evaluation of biomarkers for prognostic and predictive purposes, strategies for patient follow-up, and drug designing and development. In addition, new modes of interaction between patients and doctors using AI and avatars and the application of artificial intelligence in communication skills training are also welcome.
We invite the research community to submit their latest and most significant research in the above-mentioned areas as original research articles, reviews, or short communications. Both traditional, as well as emerging ML approaches like artificial neural networks and deep learning methods, are welcome. Code availability and reproducibility of results are strongly encouraged.
Dr. Carmen Belli
Dr. Santosh Anand
Guest Editors
Manuscript Submission Information
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Keywords
- precision oncology
- cancer
- artificial intelligence
- AI
- machine learning
- deep learning
- drug discovery
- cancer screening
- biomarkers
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