Will Artificial Intelligence Play a Role in Cancer Detection?

9th December 2024

2 minutes read

Will Artificial Intelligence Play a Role in Cancer Detection?

Experts suggest that artificial intelligence (AI) technologies, such as genetic solutions and data analysis, could revolutionize how cancer is diagnosed and treated, according to a report published by “Business Standard.”

Leading life sciences companies are leveraging AI to enhance early detection of melanoma, particularly in distinguishing between benign and malignant skin tumors. AI will also be used to streamline breast X-ray screenings, reduce errors, and improve efficiency.

The report highlights that by analyzing large amounts of patient data, AI can predict treatment outcomes, refine care plans, and allocate resources more effectively, resulting in better prognoses.

Swaraj Basu, a principal bioinformatics engineer at “Strand Life Sciences,” a company specializing in life sciences and bioinformatics technologies, emphasized that AI significantly reduces costs and time in drug discovery and treatment planning.

He stated: “Machine learning-based models can classify skin cancer with an accuracy of up to 94.2%, with sensitivity and specificity exceeding 90%.”

Basu also noted that “smart algorithms, combined with access to vast datasets, enable deeper insights into complex biological mechanisms and patient behaviors.”

AI helps reduce radiologists’ workload by up to 30%, enhancing diagnostic accuracy and improving patient interaction.

In radiation oncology, AI is advancing task automation, such as delineating natural structures and preparing treatment plans.

Precision genetic and clinical tests, like the “Oncotype DX” test for breast cancer, also rely on advanced systems to analyze receptor and mutation data, helping physicians assess recurrence risks and guide treatment decisions.

The report acknowledges that the success rate of AI in cancer care remains a topic of discussion. Dinesh Madhavan, president of the oncology group at Apollo Hospitals in India, pointed out that while AI has shown promise in early detection and improved care, its success heavily depends on patient outcomes.

Madhavan explained that cancer survival rates depend on factors such as remaining disease-free for five years. “Although AI aids in early detection and flags cases needing consultation, patient conversion rates remain a critical factor in its effectiveness,” he said.

AI-driven technological advancements enable healthcare providers to analyze massive datasets, including X-rays, tissue images, and electronic health records, to identify patterns often overlooked by human evaluation.

AI also enhances genetic solutions by focusing on standardizing medical texts and using AI platforms to discover drug targets and develop precision medicine.

The growing need for AI in cancer care is attributed to increased data availability and challenges in managing the disease. AI also strengthens capabilities in radiation oncology.

Major companies have integrated AI-based features such as automatic boundary identification and adaptive planning into their devices, helping improve treatment precision and efficiency.

As healthcare systems face resource pressures, such as a shortage of radiologists, AI proves its value by reducing errors, improving scalability, and streamlining workflows.