Proceedings of 3rd International Conference on Library & Technology on “Artificial Intelligence and Humanities in Library and Education 4.0 (AIHLE 2025)

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Harnessing Library Intelligence: A Comprehensive Study of AI-Driven Tools for Medical Diagnostics

Authors
Archana Goswami1, 2, Ajay Kumar3, *, Ashish Sharma4, Mamta Sharma1, Shikha Tayal5, *
1Department of Biochemistry, Giri Diagnostic Kits and Reagents Pvt Ltd, Selakui, Dehradun, 248011, Uttarakhand, India
2Department of Bio-Technology, School of Applied and Life Sciences, Uttaranchal University, Dehradun, 248007, Uttarakhand, India
3Department of Chemistry, School of Applied and Life Sciences, Uttarnchal Institute of Technology, Uttaranchal University, Dehradun, 248007, Uttarakhand, India
4Department of Electronic Engineering, Indian Institute of Science, Bengaluru, Karnataka, India
5Department of Computer Applications, Tulas Institute, Mehre Ka Gaon, Dhulkot Rd, PO, Selakui, 248197, Dehradun, Uttarakhand, India
*Corresponding author. Email: ajaykumar1@uumail.in
*Corresponding author. Email: dr.shikha.aeron@gmail.com
Corresponding Authors
Ajay Kumar, Shikha Tayal
Available Online 16 March 2026.
DOI
10.2991/978-94-6239-618-0_28How to use a DOI?
Keywords
Health AI; AI tools; Conventional method; Medical Chat
Abstract

The fast progression of Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), and cloud-based computing is changing the perspective of healthcare, particularly in the crucial phase before diagnosis, commonly referred to as the pre-diagnostic stage. This comprehensive review scans the latest technologies by modifying the conventional procedure of patient monitoring, risk assessment, and early disease detection. Conventional healthcare approaches mostly depend on occasional clinical visits, manual data collection, and rule-based diagnostic processes that can hinder timely intervention. In other words, AI/ML algorithms, linked with IoT-facilitated wearable devices and assisted by cloud or edge computing infrastructure, facilitate regular health monitoring, quick abnormality detection, individualized threat classification, and point-of-care decision support. Health-associated AI tools like medical chat, Woebot, and Glass AI are used by health workers to provide a correct answer to intricate medical issues. We determine the relative uses of these technologies over conventional methods, including improved sensitivity, scalability, and cost-efficiency, while also highlighting challenges such as data privacy, interpretability, and infrastructure limitations. From present studies and technological developments, this paper highlights the necessity of bright pre-diagnostic systems in increasing healthcare accessibility, efficiency, and patient outcomes, especially in the area of diseases like cancer management and preventive medicine.

Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of 3rd International Conference on Library & Technology on “Artificial Intelligence and Humanities in Library and Education 4.0 (AIHLE 2025)
Series
Advances in Intelligent Systems Research
Publication Date
16 March 2026
ISBN
978-94-6239-618-0
ISSN
1951-6851
DOI
10.2991/978-94-6239-618-0_28How to use a DOI?
Copyright
© 2026 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Archana Goswami
AU  - Ajay Kumar
AU  - Ashish Sharma
AU  - Mamta Sharma
AU  - Shikha Tayal
PY  - 2026
DA  - 2026/03/16
TI  - Harnessing Library Intelligence: A Comprehensive Study of AI-Driven Tools for Medical Diagnostics
BT  - Proceedings of 3rd International Conference on Library & Technology on “Artificial Intelligence and Humanities in Library and Education 4.0 (AIHLE 2025)
PB  - Atlantis Press
SP  - 378
EP  - 397
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-618-0_28
DO  - 10.2991/978-94-6239-618-0_28
ID  - Goswami2026
ER  -