Evidence map›Paper›PMID 39479277›Full record

ReviewHealth care science2024

Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future-A comprehensive review.

Aswin Thacharodi, Prabhakar Singh, Ramu Meenatchi, Z H Tawfeeq Ahmed, Rejith R S Kumar, Neha V, Sanjana Kavish, Mohsin Maqbool, Saqib Hassan

Abstract readReview
In one paragraph

Review in Health care science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Recent Advances in AI and GenAI for Health Informatics.Healthcare (Basel, Switzerland) · 2026
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3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Aswin ThacharodiDepartment of Research and Development Dr. Thacharodi's Laboratories Puducherry India.
Prabhakar SinghDepartment of Biotechnology, School of Bio and Chemical Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India.
Ramu MeenatchiDepartment of Biotechnology, SRM Institute of Science and Technology Faculty of Science and Humanities, Kattankulathur Chengalpattu Tamilnadu India.
Z H Tawfeeq AhmedDepartment of Biotechnology, School of Bio and Chemical Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India.
Rejith R S KumarDepartment of Biotechnology, School of Bio and Chemical Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India.
Neha VDepartment of Biotechnology, School of Bio and Chemical Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India.
Sanjana KavishDepartment of Biotechnology, School of Bio and Chemical Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India.
Mohsin MaqboolSidney Kimmel Cancer Center Jefferson Health Thomas Jefferson University Philadelphia Pennsylvania USA.
Saqib HassanDepartment of Biotechnology, School of Bio and Chemical Engineering Sathyabama Institute of Science and Technology Chennai Tamilnadu India.ORCID 0000-0001-7912-1865

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing integration of new technologies is driving a fundamental revolution in the healthcare sector. Developments in artificial intelligence (AI), machine learning, and big data analytics have completely transformed the diagnosis, treatment, and care of patients. AI-powered solutions are enhancing the efficiency and accuracy of healthcare delivery by demonstrating exceptional skills in personalized medicine, early disease detection, and predictive analytics. Furthermore, telemedicine and remote patient monitoring systems have overcome geographical constraints, offering easy and accessible healthcare services, particularly in underserved areas. Wearable technology, the Internet of Medical Things, and sensor technologies have empowered individuals to take an active role in tracking and managing their health. These devices facilitate real-time data collection, enabling preventive and personalized care. Additionally, the development of 3D printing technology has revolutionized the medical field by enabling the production of customized prosthetics, implants, and anatomical models, significantly impacting surgical planning and treatment strategies. Accepting these advancements holds the potential to create a more patient-centered, efficient healthcare system that emphasizes individualized care, preventive care, and better overall health outcomes. This review's novelty lies in exploring how these technologies are radically transforming the healthcare industry, paving the way for a more personalized and effective healthcare for all. It highlights the capacity of modern technology to revolutionize healthcare delivery by addressing long-standing challenges and improving health outcomes. Although the approval and use of digital technology and advanced data analysis face scientific and regulatory obstacles, they have the potential for transforming translational research. as these technologies continue to evolve, they are poised to significantly alter the healthcare environment, offering a more sustainable, efficient, and accessible healthcare ecosystem for future generations. Innovation across multiple fronts will shape the future of advanced healthcare technology, revolutionizing the provision of healthcare, enhancing patient outcomes, and equipping both patients and healthcare professionals with the tools to make better decisions and receive personalized treatment. As these technologies continue to develop and become integrated into standard healthcare practices, the future of healthcare will probably be more accessible, effective, and efficient than ever before.

Indexed as

Artificial Intelligencehealthcaremachine learningmulti‐omicsprecision medicine

Identifiers

PMID39479277
PMCPMC11520245

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.