The complexity and diversity observed in cancer make it a major challenge for modern medicine.The study of its pathology, development, and treatment requires genomic, transcriptomic, and proteomic analyses, along with clinical observation.Bioinformatics tools are useful and accurate in integrating different data and establishing correlations and pathways.Machine learning and AI have improved the accuracy and efficiency of existing bioinformatics tools; they accelerate the analysis of large datasets and accurately recognize patterns.Additionally, using data from online repositories, machine learning tools can accurately assess pathways, conduct virtual drug screening, and determine patient outcomes.The integration of machine learning and artificial intelligence has helped clinicians in detection and treatment strategies.Various new developments, such as CAR-T therapy, drug repurposing, and liquid biopsies, have been developed and improved.Personalized medicine, with variables such as patient history, drug interactions, and clinical trials, is optimized by artificial intelligence.The next step is wearable technology that can provide real-time monitoring of the patient for early diagnosis and determination of treatment strategies.India Vision 2047 has established Integrated Research and Diagnostic Laboratories for a joint approach, where clinical diagnosis is carried out in conjunction with research.The aim is to accelerate the discovery of diagnostic procedures such as biomarkers.Viral Research and Diagnostic Laboratories have also been established to study the connections between pathology and oncogenic viruses.The mission aims to effectively improve outcomes by integrating machine learning into workflows.
Vats et al. (2026) studied this question.