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Paper ID:IJSREM67291

Artificial Intelligence In Healthcare And Medicine

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM67291

Volume:

10 |

9 |

Sep 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM67291

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

ZA

Zeenat Aisha

Department of Science

K K Modi University

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Mentors

DMBA

Dr Mohammad Bhaktawar Ahmed

Department of Science

K K Modi University

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Abstract

Artificial Intelligence (AI) is becoming an important technology in healthcare and medicine. It is being used to support doctors, researchers and nutrition professionals in areas such as disease diagnosis, medical imaging, patient monitoring, drug discovery and treatment planning. AI can process large amounts of information and identify patterns that may be difficult to find manually. Its use is also growing in nutrition, especially in dietary assessment, food recognition, personalized diet planning and management of nutrition-related diseases. AI can make nutrition care more personalized by considering factors such as age, lifestyle, food habits and health conditions. At the same time, the use of AI has challenges, including data privacy, incorrect results, bias and lack of human judgment. This paper discusses the major applications, benefits and limitations of AI in healthcare, with special focus on nutrition and dietetics.

KEYWORDS

Artificial Intelligence Healthcare Medicine Nutrition Machine Learning Personalized Nutrition Dietetics

Cite This Article

Zeenat Aisha, Dr Mohammad Bhaktawar Ahmed, "Artificial Intelligence In Healthcare And Medicine," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 9, pp. 1-6, Sep 2026. https://doi.org/10.55041/IJSREM67291

Full Article/Conclusion

Artificial Intelligence is becoming an important technology in healthcare and medicine. It can support disease diagnosis, medical imaging, patient monitoring, drug discovery and many other areas. Its role in nutrition is also growing, especially in dietary assessment, food recognition, nutrient estimation and personalized diet planning. Despite these advantages, AI has limitations related to accuracy, privacy, bias and lack of human understanding. It should not be used as a complete replacement for doctors, dietitians or nutrition professionals. The most useful approach is to combine AI with human expertise. With proper research, validation and responsible use, AI can become a valuable supportive tool in healthcare and nutrition and may contribute to more personalized and efficient patient care.

References

[1]   E. J. Topol, “High-performance medicine: The convergence of human and artificial intelligence,” Nature Medicine, vol. 25, pp. 44–56, 2019. [2]   A. Rajkomar, J. Dean, and I. Kohane, “Machine Learning in Medicine,” New England Journal of Medicine, vol. 380, pp. 1347–1358, 2019. [3]   A. Esteva et al., “A Guide to Deep Learning in Healthcare,” Nature Medicine, vol. 25, pp. 24–29, 2019. [4]   K. H. Yu, A. L. Beam, and I. S. Kohane, “Artificial Intelligence in Healthcare,” Nature Biomedical Engineering, vol. 2, pp. 719–731, 2018. [5]   World Health Organization, Ethics and Governance of Artificial Intelligence for Health, Geneva: World Health Organization, 2021. [6]   World Health Organization, Ethics and Governance of Artificial Intelligence for Health: Guidance on Large Multi-Modal Models, Geneva: World Health Organization, 2025. [7]   “Applications of Artificial Intelligence, Machine Learning, and Deep Learning in Nutrition: A Systematic Review,” 2024. [8]   A. Agrawal, M. Goktas, R. Kumar, and B. Leung, “Artificial intelligence in personalized nutrition and food manufacturing: A comprehensive review of methods, applications, and future directions,” Frontiers in Nutrition, 2025. [9]   J. Belkhouribchia and J. J. Pen, “Artificial intelligence in clinical nutrition: A narrative review,” Clinical Nutrition ESPEN, vol. 72, p. 102822, 2026.

Editorial & Review Transparency

Publication Date

9/15/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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2

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