Applications of artificial intelligence multiomics in precision oncology

Area of Science:

• Oncology
• Bioinformatics
• Computational Biology

Background:

• Cancer is a leading global disease driven by genetic mutations.
• Next-generation sequencing (NGS) generates vast amounts of data crucial for understanding cancer.
• Machine learning (ML) and artificial intelligence (AI) offer powerful tools for analyzing complex biological data.

Purpose of the Study:

• To explore the application of NGS and ML/AI in cancer research and clinical practice.
• To highlight the role of bioinformatics in managing and analyzing multi-omics cancer data.
• To discuss the potential of AI in personalizing cancer diagnosis, prognosis, and treatment.

Main Methods:

• Utilizing multi-omics analyses from NGS data.
• Employing bioinformatics tools for data management and integration.
• Applying ML-based AI techniques for patient-specific insights.

Main Results:

• NGS data facilitate the detection of oncogenic mutations and abnormalities.
• AI applications enhance risk prediction, early diagnosis, and prognosis.
• Personalized patient information regarding treatment, progress, and lifestyle is improved.

Conclusions:

• Bioinformatics and AI are transforming cancer care by enabling personalized treatment strategies.
• These technologies provide deeper insights into cancer biology, leading to improved patient outcomes.
• The integration of AI promises faster and more tailored cancer therapies in the future.