Hematologic malignancies comprise a highly heterogeneous spectrum of cancers, where accurate diagnosis, molecular classification, and risk stratification are critical for optimal patient management. Over the past decade, Next-Generation Sequencing (NGS) has emerged as a cornerstone in hemato-oncology, enabling comprehensive genomic profiling through the detection of clinically relevant mutations, copy number alterations, and gene fusions. This genomic advancement has significantly enhanced diagnostic precision and has guided the development of targeted and personalized therapeutic strategies across leukemias, lymphomas, and plasma cell neoplasms.

In parallel, Artificial Intelligence (AI) is rapidly transforming the landscape of molecular oncology by providing advanced computational tools to interpret complex genomic datasets. AI-driven approaches support variant prioritization, prognostic modeling, treatment response prediction, and identification of actionable molecular targets. Machine learning models are increasingly being integrated into diagnostic workflows, combining sequencing data with morphology, flow cytometry, and cytogenetic findings to enable holistic and clinically meaningful decision-making.

The convergence of AI-powered analytics with NGS technologies represents a paradigm shift toward the future of precision cancer care, offering unprecedented opportunities to improve diagnostic accuracy, personalize therapy, and ultimately transform outcomes for patients with hematologic malignancies.

Meghana P is a consultant hematopathologist and molecular pathologist at Bagchi Sri Shankara Cancer Centre and Research Institute, a 750-bedded tertiary care hospital dedicated exclusively to Comprehensive Cancer Care in Bhubaneswar, India, and one of the largest cancer care facilities in the country. She holds an MBBS and an MD in pathology, along with a PDCC in molecular pathology and cytogenomics. With over six years of experience spanning hematopathology, molecular oncology, transplant immunology, and genomic diagnostics, she has developed expertise in the clinical application of Next-Generation Sequencing, cytogenetics, flow cytometry, and molecular assays for the evaluation and management of hematologic malignancies. Her academic and professional interests focus on precision oncology, integration of AI-driven tools into molecular pathology workflows, and improving personalized diagnostic and therapeutic strategies in hemato-oncology. She is committed to advancing cancer diagnostics through translational innovations and evidence-based genomic medicine.