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The ability of AI to help in the early detection of cancer and offer personalised treatment solutions makes a strong case for why it needs to be integrated into treating the disease
As per the Global Cancer Observatory (GLOBOCAN), India witnessed 1.32 million new cancer cases in 2020. This number is expected to surge by 57% to 2.08 million by 2040. The surge in cancer cases not only poses a significant health challenge but also brings to light the financial burden associated with cancer treatment. With the average cost of treatment in India hovering around ₹5 lakhs, cancer presents a daunting diagnosis for patients across the nation.
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In India, over two-thirds of cancer patients are diagnosed in advanced stages III or IV, necessitating multimodality treatments with added costs and increased morbidity. This is often a consequence of delayed diagnoses. Shockingly, more than half of these patients succumb to the disease within the first year of diagnosis. With escalating cancer numbers, inadequate insurance coverage, and a low per capita income, the urgency for timely and cost-effective cancer treatment has never been more pressing.
Amidst these challenges, Artificial Intelligence (AI) emerges as a transformative force, reshaping the landscape of cancer care in India. From early detection and diagnosis to personalized treatment planning and monitoring, AI holds immense potential to revolutionize the way we approach cancer treatment.
Early detection and diagnosis
AI can swiftly and precisely analyse clinical data, radiological imaging, and genetic profiles. This enables the detection of pre-cancerous lesions and early-stage cancers, facilitating timely and less expensive interventions. By leveraging machine learning algorithms, AI systems can sift through vast amounts of data with remarkable speed, aiding in the identification of potential malignancies.
Personalised treatment planning
The integration of AI in cancer care allows for the personalisation of treatment plans. Biomarkers, critical in identifying cancers and tailoring treatment protocols, can be efficiently identified with AI assistance, reducing both time and costs associated with these processes. AI’s ability to analyze complex genetic data aids in predicting treatment responses, guiding oncologists towards more effective and personalised interventions.
Continuous monitoring and timely interventions
AI’s analytical capabilities extend to continuous monitoring of patient data and clinical parameters. This facilitates timely interventions that can prevent treatment-related complications, reduce hospital re-admissions, and minimize adverse events. By doing so, healthcare costs are curtailed, and the overall quality of care is enhanced.
CHALLENGES IN AI INTEGRATION
While the potential benefits of AI in cancer care are immense, several challenges hinder its seamless integration. They include:
High implementation costs: Developing and implementing AI-driven solutions in the healthcare sector demand substantial financial investments. The high costs involved may impede widespread adoption, especially in resource-constrained settings.
Data limitations: AI relies heavily on data, and the lack of structured cancer-related health data poses a hurdle. Establishing comprehensive databases that encompass diverse patient profiles and treatment outcomes is crucial for the accurate and effective application of AI in cancer care.
Ethical considerations: The ethical dimensions of AI in healthcare cannot be overlooked. Issues surrounding data privacy, patient consent, and algorithmic bias must be addressed to ensure the responsible and equitable use of AI in cancer diagnosis and treatment.
STRATEGIES FOR ADVANCEMENT
To fully unlock the potential of AI in cancer care, concerted efforts are required to overcome these challenges.
Investment in R&D: Encouraging investment in research and development will expedite the creation of cost-effective AI solutions tailored to the specific needs of the Indian healthcare landscape.
Data standardization: Efforts should be directed towards standardizing cancer-related health data, creating interoperable systems that facilitate seamless data exchange among healthcare providers and institutions.
Ethical frameworks: Establishing robust ethical frameworks is imperative. Addressing concerns related to data privacy, obtaining informed patient consent, and mitigating algorithmic bias will ensure the responsible and equitable deployment of AI in cancer care.
PUBLIC AWARENESS AND EDUCATION
The journey towards integrating AI into cancer care may be challenging, but it is one worth undertaking. Through research, investment, and a commitment to ethical practices, we can unlock the full potential of AI, providing hope and improved outcomes for cancer patients across the nation.
Promoting public awareness about the benefits and limitations of AI in cancer care is essential. Educating both healthcare professionals and the general public will foster a better understanding of AI’s role in improving cancer diagnosis and treatment. By harnessing the power of AI for early detection, personalized treatment planning, and continuous monitoring, we have an unprecedented opportunity to enhance the quality of cancer care while making it more accessible and affordable.
Dr. Kanav Kumar is a surgical cncologist at the Punyashlok Ahilyadevi Holkar Head & Neck Cancer Institute of India, Mumbai.
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