https://padlet.com/manjusaje/daqxis1hzion Here are some abstract examples . Identity which is well written and why? en-us 2017-03-22 13:53:42 UTC 2025-10-30 10:45:00 UTC hello@padlet.com manjusaje https://padlet.com/manjusaje/daqxis1hzion/wish/2511558375  Artificial intelligence in medicine has made dramatic progress in recent years. However, much of this progress is seemingly scattered, lacking a cohesive structure for the discerning observer. In this article, we will provide an up-to-date review of artificial intelligence in medicine, with a specific focus on its application to radiology, pathology, ophthalmology, and dermatology. We will discuss a range of selected papers that illustrate the potential uses of artificial intelligence in a technologically advanced future.

Sagar Kulkarni, Nuran Seneviratne, Mirza Shaheer Baig, Ameer Hamid Ahmed Khan, Artificial Intelligence in Medicine: Where Are We Now?, Academic Radiology,
Volume 27, Issue 1, 2020, Pages 62-70, ISSN 1076-6332,
https://doi.org/10.1016/j.acra.2019.10.001.]]> 2023-03-10 08:52:23 UTC https://padlet.com/manjusaje/daqxis1hzion/wish/2511558375 manjusaje https://padlet.com/manjusaje/daqxis1hzion/wish/2511560184 Artificial intelligence (AI) in the healthcare sector is receiving attention from researchers and health professionals. Few previous studies have investigated this topic from a multi-disciplinary perspective, including accounting, business and management, decision sciences and health professions. The structured literature review with its reliable and replicable research protocol allowed the researchers to extract 288 peer-reviewed papers from Scopus. The authors used qualitative and quantitative variables to analyse authors, journals, keywords, and collaboration networks among researchers. Additionally, the paper benefited from the Bibliometrix R software package. The investigation showed that the literature in this field is emerging. It focuses on health services management, predictive medicine, patient data and diagnostics, and clinical decision-making. The United States, China, and the United Kingdom contributed the highest number of studies. Keyword analysis revealed that AI can support physicians in making a diagnosis, predicting the spread of diseases and customising treatment paths. The literature reveals several AI applications for health services and a stream of research that has not fully been covered. For instance, AI projects require skills and data quality awareness for data-intensive analysis and knowledge-based management. Insights can help researchers and health professionals understand and address future research on AI in the healthcare field.

Secinaro, S., Calandra, D., Secinaro, A. et al. The role of artificial intelligence in healthcare: a structured literature review. BMC Med Inform Decis Mak 21, 125 (2021). https://doi.org/10.1186/s12911-021-01488-9]]> 2023-03-10 08:54:18 UTC https://padlet.com/manjusaje/daqxis1hzion/wish/2511560184 manjusaje https://padlet.com/manjusaje/daqxis1hzion/wish/2514705804 Having passed the primitive phases and starting to revolutionize many different fields in some way, artificial intelligence is on its way to becoming a disruptive technology. It is also foreseen to totally change human-centred traditional engineering design approaches. Although still in the early phases, AI-powered engineering applications enable them to work with ambiguous design parameters and solve complex engineering problems, not otherwise possible with traditional design methods. This work attempts to shine a light on current progress and future research trends in AI applications in design/engineering design concepts, covering the last 15 years which is the ramp-up period for AI. Methods such as machine learning, genetic algorithm, and fuzzy logic have been carefully examined from an engineering design perspective. AI-powered design studies have been categorized and critically reviewed for various design stages such as inspiration, idea and concept generation, evaluation, optimization, decision-making, and modelling. As an overview result of this review, we can confidently say that the interest in data-based design methods and Explainable Artificial Intelligence (XAI) has increased in recent years. Furthermore, the use of AI methods in engineering design applications helps to obtain efficient, fast, accurate, and comprehensive results. Especially with deep learning methods and combinations, situations where human capacity is insufficient can be addressed efficiently. However, choosing the right AI method for a design problem under consideration is significantly important for such successful results. Hence, we have given an outline perspective on choosing the right AI method based on the literature outcomes for design problems.

Yue Pan, Limao Zhang, Roles of artificial intelligence in construction engineering and management: A critical review and future trends, Automation in Construction, Volume 122, 2021, 103517, ISSN 0926-5805, https://doi.org/10.1016/j.autcon.2020.103517.]]> 2023-03-13 16:20:45 UTC https://padlet.com/manjusaje/daqxis1hzion/wish/2514705804