AI-DRIVEN ADVANCES IN CANCER DIAGNOSIS AND TREATMENT

Hemani Mistry*, Riddhi Gandhi, Anjali Patel, Sakshi Gandhi, Satyajit Sahoo, Dhananjay B. Meshram

Cancer is one of the most significant concerns of the health system in the world and early diagnosis and personalised treatment will be significant drivers in improving the outcome of patients. Cancer prevention, screening, diagnosis, treatment and monitoring are today an exciting area of Artificial Intelligence (AI) for cancer. Using AI, machine learning, deep learning and natural language processing (NLP) have the potential to capture tremendous amounts of information from clinical and imaging data, pathology, the genomic and molecular data. AI analysis of the CT, MRI, PET and histopathological images can aid in early diagnosis and the detection and classification of tumours. Precise oncology uses AI to integrate genomic information and clinical data and make precise, personalized treatment choices, patient categorization, prognosis of how patients will respond to treatment and predict whether they will return. AI is also playing a role in anticancer drug discovery in repurposing drugs, prediction of drug-target interaction and optimization of drug candidates. However, there are issues like robustness of data, privacy, algorithmic bias, transparency, clinical validation and regulatory issues that need to be addressed. In total, the possibilities for AI to enhance the accuracy, efficiency, individualisation and patient-centredness of cancer treatment and care are huge.