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AI to drive advancements in cancer diagnoses: Report
Artificial intelligence
Incorporation of artificial intelligence (AI) technology in oncology-based in vitro diagnostic (IVD) products is expected to result in advancements in cancer diagnosis, according to a report on Friday.
New Delhi: Incorporation of artificial intelligence (AI) technology in oncology-based in vitro diagnostic (IVD) products is expected to result in advancements in cancer diagnosis, according to a report on Friday.
AI-based IVDs have the potential to exponentially improve healthcare decisions by identifying disease signatures that can help in early detection and treatment. It can also improve patient care, management, as well as outcomes.
The report by GlobalData, a leading data and analytics company, showed that currently, there are 569 clinical trials focused on developing IVD devices in oncology out of 1,490 active clinical trials.
Out of the total IVD trials, nine are being conducted to test partial or full analysis by AI to improve oncology diagnosis. AI-driven machine learning is pushing the advancement of IVD device development in terms of accuracy and reliability.
"Some of the active oncology clinical trials with AI are focusing on using AI to optimise workflows, such as which patients require additional analysis and prioritising severe cases. Another use for AI in oncology IVD devices is to predict which treatment responses would be the most effective using patient samples," said Selena Yu, Medical Analyst at GlobalData, in a statement.
One of the trials is using AI to assess treatment responses in patient samples, while another is currently testing the AI's ability to detect central nervous system (CNS) tumours unsupervised and fully automated.
"These advancements will push more manufacturers to partner with AI algorithm providers to improve their existing cancer diagnostic software," Yu said.
"This, in turn, will not only decrease the time needed for diagnosis feedback to patients and early diagnosis with more sensitive software but also provide effective treatment options for patients and decrease the workload for healthcare professionals," she added.
