Artificial Intelligence (AI) Revolution in Research: Transforming Data into Discovery

Authors

  • Tayyiba Wasim Services Institute of Medical Sciences, Lahore
  • Aysha Zaheer Services Institute of Medical Sciences, Lahore

DOI:

https://doi.org/10.51273/esc23.251319426

Abstract

Introduction
Artificial Intelligence (AI) has emerged as a Atransformative force in the dominion of research, reshaping the landscape across diverse
fields. AI refers to the simulation of human intelligence by a system or a machine. It implies a vast  term that encompasses machine learning and deep learning. AI is based firstly on 'intelligence' which refers to cognitive capacity of an individual to plan
learn and interpret. Secondly 'techne', a more wideranging ability to solve problems using technological objects. Although the intelligence remains the same measured by intelligence quotient (IQ) for many decades now, it is the change in techne that leads to
amplification of intelligence.

Use of AI in healthcare and biomedical sciences is based on development of algorithms. This requires a sound knowledge of programming languages, advanced mathematics and statistics. In healthcare AI cannot be used fairly if these skills are lacking.
However visual and no code programming tools  available now with free data science tools make it easy for clinicians, researchers and health journalists.

Author Biographies

Tayyiba Wasim, Services Institute of Medical Sciences, Lahore

Professor

Department of Obstetrics and Gynaecology,

Services Institute of Medical Sciences, Lahore

Aysha Zaheer, Services Institute of Medical Sciences, Lahore

Associate Professor

Department of Physiology

Services Institute of Medical Sciences, Lahore

References

Wang H, Fu T, Du Y, Gao W, Huang K, Liu Z et al. Scientific discovery in the age of artificial intelligence. Nature . 2023 Aug;620(7972):47-60. doi: 10.1038/s41586-023-06221-2.

Jebari K, Lundborg J. The intelligence explosion revisited. foresight. 2019 Mar 11;21(1):167-74.

Hersh WR, Hoyt RE, Chamberlin S, Ancker JS, Gupta A, Borlawsky-Payne TB. Beyond mathematics,statistics, and programming: data science, machine learning, and artificial intelligence competencies and curricula for clinicians, informaticians, science

journalists, and researchers. Health Systems. 2023 Jul 3;12(3):255-63.

Bajwa J, Munir U, Nori A, Williams B. Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthc J. 2021 Jul;8(2):e188-e194. doi: 10.7861/fhj.2021-0095.

Bhinder B, Gilvary C, Madhukar NS, Elemento O. Artificial Intelligence in Cancer Research and Precision Medicine. Cancer Discov. 2021Apr;11(4):900-915. doi: 10.1158/2159-8290.CD-21-0090.

Morrow E, Zidaru T, Ross F, Mason C, Patel KD, Ream M, Stockley R. Artificial intelligence technologies and compassion in healthcare: A systematic scoping review. Front Psychol. 2023 Jan 17;13:971044. doi: 10.3389/fpsyg.2022.971044.

Ibrahim H, Liu X, Denniston AK. Reporting guidelines for artificial intelligence in healthcare research. Clin Exp Ophthalmol. 2021 Jul;49(5):470-476. doi:10.1111/ceo.13943.

Secinaro S, Calandra D, Secinaro A, Muthurangu V, Biancone P. The role of artificial intelligence in healthcare: a structured literature review. BMCmedical informatics and decision making. 2021 Dec;21:1-23.

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Published

2024-02-03

How to Cite

1.
Wasim T, Zaheer A. Artificial Intelligence (AI) Revolution in Research: Transforming Data into Discovery. Esculapio - JSIMS [Internet]. 2024 Feb. 3 [cited 2024 Apr. 28];19(04):376-7. Available from: https://esculapio.pk/journal/index.php/journal-files/article/view/1053