Artificial Intelligence in Medicine: 16th Conference on Artificial Intelligence in Medicine, AIME 2017, Vienna, Austria, June 21-24, 2017, Proceedings
By Marium Malik, M. Tariq, Maira Kamran, M.R Naqvi. Conference on Artificial Intelligence in Medicine in Europe, 2017
1,423 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Health Informatics
View Paper: https://www.semanticscholar.org/paper/87edc94f0d3aa7e7e6fcf50916eda0737498e2d7
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Paolo Ferragina
- Richard Durbin
- Meng He
- Ben Langmead
- Chenyan Xiong
- Heng Li
- Gonzalo Navarro
- Veli Mäkinen
Citations in the corpus
- Artificial intelligence to deep learning: machine intelligence approach for drug discovery (2021, neutral): “Further, the cost of development and time consumption in developing novel therapeutic agents was another setback in the drug design and development process [2].”
- ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health (2023, background): “Our reflections highlight a growing interest in the use of LLMs in academic research, with the release of ChatGPT this interest has only increased (38).”
- A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME (2023, background): “Machine (ML) and Deep (DL) learning methods have shown great success in a variety of domains, e.g. biology [1], medicine [2], economy [3] and education [4].”
- Precision Medicine, AI, and the Future of Personalized Health Care (2020, positive): “18 The power of AI technologies to recognize sophisticated patterns and hidden structures has enabled many image-based detection and diagnostic systems in healthcare to perform as well or better than clinicians, in some cases.”
- The Internet of Things: Impact and Implications for Health Care Delivery (2020, neutral): “For example, IBM Watson uses AI to read both structured and unstructured text in the EMR, read images to highlight primary and incidental findings, and compile relevant medical literature in response to clinical queries [54].”
- Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment (2020, neutral): “This justifies how and to what extent Artificial Intelligence (AI) could be crucial in developing and upgrading health care systems on a global scale [6].”