Topic: AI-Powered Genetic Insights and Counseling

Advances in genomics and bioinformatics have profoundly transformed our understanding of genetic diseases, enabling precise identification of pathogenic variants and deeper insights into genotype–phenotype relationships. As artificial intelligence (AI) technologies rapidly evolve, they are increasingly being integrated into genetic research and clinical practice—ushering in a new era of data-driven precision medicine.

This Special Issue, AI-Powered Genetic Insights and Counseling, aims to showcase innovative applications of AI in the analysis, interpretation, and clinical integration of genetic data. By leveraging machine learning, deep learning, and other computational approaches, researchers and clinicians are beginning to decode complex genomic datasets with unprecedented speed and accuracy, offering new opportunities for early diagnosis, risk prediction, and personalized genetic counseling.

Topics of interest include, but are not limited to:

● AI in genomic data analysis: Development and application of AI tools for variant prioritization, functional annotation, and prediction of pathogenicity.

● Machine learning in risk assessment and prediction: AI-driven models for predicting disease susceptibility, penetrance, and genotype–phenotype correlations.

● AI-assisted genetic counseling: Tools that support decision-making in clinical genetic counseling, including risk communication, family history analysis, and psychosocial impact assessment.

● Integration of multi-omics and clinical data: AI approaches to integrate genomics, transcriptomics, proteomics, and phenotypic data for comprehensive patient stratification.

● AI in rare disease diagnostics: Use of computational phenotyping, facial analysis, and symptom recognition algorithms in diagnosing Mendelian and complex genetic disorders.

● Ethical, legal, and social implications (ELSI): Considerations around data privacy, algorithmic bias, and the responsible use of AI in genomics and patient care.

● AI-enhanced newborn screening and carrier testing: Optimization of population screening programs through predictive algorithms and automated variant interpretation.

● Clinical decision support systems: AI-powered platforms for supporting diagnosis, treatment planning, and long-term management in genomic medicine.

We welcome original research articles, comprehensive reviews, and perspectives that explore the intersection of AI and human genetics, particularly those that demonstrate translational relevance and clinical utility. Through this Special Issue, we aim to highlight the transformative potential of AI in reshaping genetic diagnostics and counseling, ultimately contributing to more equitable and efficient precision healthcare.

Artificial intelligence (AI), genetic counseling, genomic medicine, human genetics, genomic data analysis, genetic risk assessment