Revolutionizing early diagnosis and personalized care: The role of AI in healthcare

Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy and enabling personalized medicine. Deep learning and machine learning models have demonstrated superior performance in medical imaging, disease prediction, and patient-specific treatment optimization. Convolutional neural networks have achieved remarkable results in detecting abnormalities in radiology scans, often surpassing human-level accuracy. AI-driven genomic analysis also aids in identifying disease susceptibility, enabling precision medicine approaches. Case studies on AI's role in detecting conditions such as cancer, Alzheimer's, and cardiovascular diseases highlight its ability to improve early diagnosis and optimize therapeutic interventions. However, challenges including data privacy, model interpretability, and regulatory compliance require careful consideration. The integration of diverse patient data sources and the development of real-time monitoring systems represent promising future directions. Overall, AI has substantial potential to revolutionize healthcare by reducing diagnostic errors, personalizing treatment plans, and improving patient outcomes, particularly in resource-limited settings.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-05-22
DOI
https://doi.org/10.30574/wjarr.2025.26.2.1821
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Revolutionizing early diagnosis and personalized care: The role of AI in healthcare

KRISHNA CHAITANYA YARLAGADDA
World Journal of Advanced Research and Reviews
Machine Learning in Healthcare
article

Revolutionizing early diagnosis and personalized care: The role of AI in healthcare

KRISHNA CHAITANYA YARLAGADDA
article en

Abstract

Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy and enabling personalized medicine. Deep learning and machine learning models have demonstrated superior performance in medical imaging, disease prediction, and patient-specific treatment optimization. Convolutional neural networks have achieved remarkable results in detecting abnormalities in radiology scans, often surpassing human-level accuracy. AI-driven genomic analysis also aids in identifying disease susceptibility, enabling precision medicine approaches. Case studies on AI's role in detecting conditions such as cancer, Alzheimer's, and cardiovascular diseases highlight its ability to improve early diagnosis and optimize therapeutic interventions. However, challenges including data privacy, model interpretability, and regulatory compliance require careful consideration. The integration of diverse patient data sources and the development of real-time monitoring systems represent promising future directions. Overall, AI has substantial potential to revolutionize healthcare by reducing diagnostic errors, personalizing treatment plans, and improving patient outcomes, particularly in resource-limited settings.

World Journal of Advanced Research and ReviewsVol. 26(2)
Openalex Percentile: Top 95%
Machine Learning in Healthcare
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.