The integration of Artificial Intelligence (AI) in the fight against cancer can revolutionise the way cancer is diagnosed, treated, and managed, a medical expert and Vice Chancellor, Summit University Offa, Kwara State, Nigeria, Professor Abiodun Musa Aibinu, has said.
Prof. Aibinu said AI has made a significant impact across a myriad of industries, especially in healthcare, adding that the primary aim of AI applications in healthcare is to analyse links between prevention or treatment approaches and patient outcomes.
He said AI has immense potential to transform every aspect of healthcare, from diagnosis and treatment to administration and research. By harnessing the power of AI, healthcare organisations can deliver more effective, personalised, and accessible care to patients worldwide.
He stated this during a webinar organised by Khayr Cancer Health Initiative (KCHI) titled, ‘Artificial Intelligence and Cancer Care’ in Kaduna, Kaduna State. The initiative brought together leading experts in information and communication technology, robotics, healthcare professionals, and stakeholders to explore the intersection of Artificial Intelligence (AI) and cancer care within the Nigerian context.
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Prof. Aibinu who was the guest speaker at the lecture said AI could revolutionise cancer care in the following ways:
Early detection and diagnosis
AI algorithms can analyse medical imaging data such as mammograms, MRIs, and CT scans to detect early signs of cancer with high accuracy.
He said, “By identifying subtle abnormalities that human observers may miss, AI enhances early detection, enabling prompt intervention and potentially improving patient outcomes. Similarly, AI enhances risk stratification in patients identified with a higher risk of developing specific cancers, prompting earlier screening.”
Treatment planning and decision support
AI enables the development of personalised treatment plans tailored to cancer patients’ genetic makeup, tumor characteristics, and individual preferences.
He explained that, “By analysing large-scale genomic and clinical datasets, AI algorithms can identify biomarkers, predict treatment responses, and recommend targeted therapies most likely adequate for each patient.”
Drug discovery and development
The medical expert said AI accelerates the discovery process by analysing vast amounts of biomedical data to identify potential drug candidates, predict their efficacy and safety profiles, and optimise their molecular structures.
“ AI-driven drug discovery platforms enable the rapid screening of large chemical libraries, leading to the discovery of novel cancer therapeutics and repurposing of existing drugs for cancer treatment,” he added.
Patient monitoring and risk assessment
Prof. Aibinu said AI-powered wearable devices and mobile health apps enable remote monitoring of cancer patients’ symptoms, medication adherence, and treatment-related side effects to monitor recurrence after treatment.
He said AI algorithms analyse data from these devices to provide personalised health insights, offer timely interventions, and empower patients to participate actively in their care management.
He said additionally, AI could analyse data to identify patients with a higher risk of recurrence, allowing doctors to develop personalised follow-up plans with more frequent monitoring.
Also speaking, Dr Bilkisu Farouk Usman, Head, Department of Radiology, Barau Dikko University Teaching Hospital, and Member, Board of Trustees, KCHI, emphasised the need for early screening of breast cancer as an antidote for early treatment.
Madinat Hassan, the Executive Director, Khayr Cancer Health Initiatives (KCHI), said, “The convergence of Artificial Intelligence and cancer care presents unprecedented opportunities to revolutionise healthcare delivery in Nigeria.
“ By harnessing the power of AI-driven technologies, we can overcome barriers to access, improve diagnostic accuracy, and ultimately save lives.”
The webinar attracted participants from diverse stakeholders, including healthcare providers, policymakers, researchers, and patient advocacy groups and was facilitated by Dr Adesola Akinyemi of the Centre for Augmented Intelligence and Data Science (CAIDS), University of South Africa, Florida Campus, Johannesburg, South Africa.
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