AI-Driven personalized medicine: Leveraging machine learning for precision treatment plans

This text evaluates the implementation of artificial intelligence (AI) and machine learning (ML) technologies for developing precise medical treatments in personalized healthcare. The research evaluates important AI technologies: genomic data processing, machine learning principles, and electronic health record implementations. The study investigates different clinical examples and real-world uses to demonstrate how AI transforms disease-specific medical interventions, primarily for oncology patients, those diagnosed with cardiological conditions, and those with rare diseases. The essential results indicate that AI diagnostic capabilities excel at precise disease recognition while generating personalized treatment projectanduperior patient healthcare benefits. Various obstacles, including data protection concerns, unclear algorithm functions, and interdisciplinary workforce integration, continue to exist. The study moves forward existing research into AI healthcare applications by studying its complete potential release. The proposed solutions offer solutions to manage current challenges and construct healthcare delivery strategies for the future time period.

Authors

Publication Details

Journal
Global Journal of Engineering and Technology Advances
Published
2024-08-30
DOI
https://doi.org/10.30574/gjeta.2024.20.2.0141
Citations
1
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.35
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article

AI-Driven personalized medicine: Leveraging machine learning for precision treatment plans

Znu Zartashea
1 citations
Global Journal of Engineering and Technology Advances
Machine Learning in Healthcare
0.35
article

AI-Driven personalized medicine: Leveraging machine learning for precision treatment plans

Znu Zartashea
article en
1 citations

Abstract

This text evaluates the implementation of artificial intelligence (AI) and machine learning (ML) technologies for developing precise medical treatments in personalized healthcare. The research evaluates important AI technologies: genomic data processing, machine learning principles, and electronic health record implementations. The study investigates different clinical examples and real-world uses to demonstrate how AI transforms disease-specific medical interventions, primarily for oncology patients, those diagnosed with cardiological conditions, and those with rare diseases. The essential results indicate that AI diagnostic capabilities excel at precise disease recognition while generating personalized treatment projectanduperior patient healthcare benefits. Various obstacles, including data protection concerns, unclear algorithm functions, and interdisciplinary workforce integration, continue to exist. The study moves forward existing research into AI healthcare applications by studying its complete potential release. The proposed solutions offer solutions to manage current challenges and construct healthcare delivery strategies for the future time period.

Global Journal of Engineering and Technology AdvancesVol. 20(2)
Openalex Percentile: Top 29%
Machine Learning in Healthcare
0.35
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AI-Driven personalized medicine: Leveraging machine learning for precision treatment plans — Znu Zartashea · Global Journal of Engineering and Technology Advances (2024) | TGRS Research Map | TGRS