Title:Application of Artificial Intelligence in Stem Cells and Gene Therapy for Gynecological Cancers
Volume: 21
Issue: 2
Author(s): Shiva Gholizadeh-Ghaleh Aziz, Sakineh Aghazadeh, Anosha Malik, Amir Javed, Sania Shaheen, Laiba Naseem, Younas Sohail, Aliasghar Tabatabaei Mohammadi and Muhammad Farrukh Nisar*
Affiliation:
- Department of Physiology and Biochemistry, Cholistan University of Veterinary and Animal Sciences (CUVAS), Bahawalpur, 63100, Pakistan
- Ministry of Education and Jiangxi Key Laboratory of Crop Physiology, Ecology and Genetic Breeding,
Jiangxi Agricultural University, Nanchang, 330045, China
Keywords:
Artificial intelligence, machine learning, stem cell therapy, gene therapy, gynecology, cancers.
Abstract: The application of artificial intelligence (AI) in stem cell and gene therapy offers significant
advancements in the treatment of gynecological cancers, including breast, ovarian, and cervical
cancers. This review explores how machine learning (ML) enhances both diagnostic and therapeutic
strategies in regenerative medicine. AI integration allows for more accurate disease progression
predictions, identification of therapeutic targets, and optimization of personalized treatment
plans. Additionally, AI improves the efficacy and safety of stem cell and gene therapy approaches
by facilitating the identification of biomarkers and genetic variations, enabling tailored therapies
for individual patients. The use of AI-supported analytics in combined treatment strategies presents
new avenues for effective cancer management. Furthermore, AI-driven regenerative
medicine optimizes stem cell functions, refines treatment protocols, and contributes to the identification
of less frequent biomarkers, improving prognostic algorithms and therapy outcomes. As
ML targets specific molecular changes in cancer cells, they enhance the precision of gene silencing
and anti-aging interventions, offering new possibilities for combined therapies. These innovations
position AI as a transformative tool in the development of personalized and effective treatments
for women's cancers, with future studies likely to expand the scope and impact of AI-driven
strategies.
