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Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

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Published on: August 17, 2022

ChatGPT in precision medicine.

Chengliang Yin, Xiaochun Sun, Anlin Dai¹

¹National Engineering Laboratory for Medical Big Data Application Technology, Chinese PLA General Hospital, Beijing 100853, China.

APL Bioengineering

|March 20, 2026

Summary

This summary is machine-generated.

Artificial intelligence, like ChatGPT, is revolutionizing precision medicine by analyzing data for early diagnosis and improving patient communication. This technology enhances medical research and healthcare efficiency.

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Area of Science:

Biomedical Informatics
Artificial Intelligence in Healthcare
Precision Medicine

Background:

Precision medicine aims to tailor treatments to individual patients.
Artificial intelligence (AI) offers advanced capabilities for analyzing complex health data.
Generative language models present new opportunities for healthcare applications.

Purpose of the Study:

To explore the capabilities of ChatGPT in precision medicine.
To identify applications of ChatGPT in analyzing health data and improving patient outcomes.
To review the role of ChatGPT in research and healthcare delivery.

Main Methods:

Review of existing literature and capabilities of ChatGPT.
Analysis of ChatGPT's potential in processing genetic sequences and identifying biomarkers.
Evaluation of natural language processing for patient communication and education.

Main Results:

ChatGPT can analyze large datasets, identify biomarkers, and predict disease risks for early diagnosis.
Natural language processing enhances patient engagement and understanding of complex medical information.
ChatGPT streamlines research, aids clinical trial recruitment, and supports healthcare professionals.

Conclusions:

ChatGPT represents a transformative tool for precision medicine, optimizing patient prognoses.
The integration of ChatGPT enhances the operational efficacy of the healthcare delivery system.
Addressing data concerns is crucial for maximizing the benefits of AI in healthcare.