Integrating human knowledge into artificial intelligence for complex and ill-structured problems: Informed artificial intelligence

USAGE OF ARTIFICIAL INTELLIGENCE ON SOCIAL MEDIA IN EUROPE

Artificial Intelligence (AI) is becoming more common in our daily life. One of the biggest segments of AI is used in business. Technologies are changing at a rapid pace and in unpredictable ways. The research was done by systematic literature of the most recent (2020-2022) academic articles from the database Scopus covering the usage of AI on social media. Dividing the find articles based on chosen criteria into categories such as social media platforms used for research and general AI usage on social media. The results show that the implementation of AI will become more and more inevitable for its variety of use on social media, like chatbots, detecting harmful behaviour, data analysis and strategy making.

Artificial Intelligence in Cancer Research: Trends, Challenges and Future Directions

The World Health Organization (WHO), in their 2022 report, identified cancer as one of the leading causes of death, accounting for about 16% of deaths worldwide. The Cancer-Moonshot community aims to reduce the cancer death rate by half in the next 25 years and wants to improve the lives of cancer-affected people. Cancer mortality can be reduced if detected early and treated appropriately. Cancers like breast cancer and cervical cancer have high cure probabilities when treated early in accordance with best practices. Integration of artificial intelligence (AI) into cancer research is currently addressing many of the challenges where medical experts fail to bring cancer to control and cure, and the outcomes are quite encouraging. AI offers many tools and platforms to facilitate more understanding and tackling of this life-threatening disease. AI-based systems can help pathologists in diagnosing cancer more accurately and consistently, reducing the case error rates. Predictive-AI models can estimate the likelihood for a person to get cancer by identifying the risk factors. Big data, together with AI, can enable medical experts to develop customized treatments for cancer patients. The side effects from this kind of customized therapy will be less severe in comparison with the generalized therapies. However, many of these AI tools will remain ineffective in fighting against cancer and saving the lives of millions of patients unless they are accessible and understandable to biologists, oncologists, and other medical cancer researchers. This paper presents the trends, challenges, and future directions of AI in cancer research. We hope that this paper will be of help to both medical experts and technical experts in getting a better understanding of the challenges and research opportunities in cancer diagnosis and treatment.