A team of scientists from the University of Surrey and the University of California have used artificial intelligence networks to help identify and analyze the symptoms of cancer patients.

A new study, published by Nature Scientific Reports, describes how researchers used network analysis to examine the structure and relationships between 38 common symptoms reported by over 1300 cancer patients receiving chemotherapy.

WHY IT MATTERS

This represents the first use of network analysis as a method of examining the relationships between common symptoms suffered by a large group of cancer patients undergoing chemotherapy, researchers say. The NA allowed the team to identify nausea as central, impacting symptoms across all three different key networks.

The development and use of AI is growing rapidly is the medical field, specifically in diagnostics and treatment management.

The ability for AI to "learn" from the data provides the opportunity for improved accuracy based on feedback responses – feedback that includes many backend database sources, input from practitioners, doctors, and research institutions.

The AI systems in healthcare are always working in real time, which means the data is always updating, thus increasing accuracy and relevance.

Assembled data is a compilation of different medical notes, electronic recordings from medical devices, laboratory images, physical examinations and various demographics.

In a similar vein, machine learning techniques use analytical algorithms in order to pull out specific patient traits, which include all the information that would be collected in a patient visit with a practitioner.

Traits such as physical exam results, symptoms, basic metrics, medications,  disease specific data and different laboratory testing all contribute to the collected structured data and through machine learning, patient outcomes can then be determined.

THE BIGGER TREND

A 2018 survey of more than 2000 U.S. adults by McKesson found 44 percent of Americans would trust AI for cancer diagnosis or a treatment recommendation. However, women are less likely (36 percent) than men (52 percent) to put their faith in AI.

A February 2018 report by Signify Research projected hospitals would spend $2 billion annually on AI for medical imaging by 2023, while analyst firm IDC projected even bigger growth, projecting worldwide spending on artificial intelligence and cognitive computing overall technologies would reach $46 billion by 2020.

The Signify report noted AI-based tools are gradually becoming more accurate and sophisticated with added functionalities.

ON THE RECORD

"This fresh approach will allow us to develop and test novel and more targeted interventions to decrease symptom burden in cancer patients undergoing chemotherapy," Christine Miaskowski from the University of California said in a statement.

"It is becoming increasingly clear that AI will transform the diagnostic imaging industry, both in terms of enhanced productivity, increased diagnostic accuracy, more personalized treatment planning, and ultimately, improved clinical outcomes," report author Simon Harris noted.

Nathan Eddy is a healthcare and technology freelancer based in Berlin.

Email the writer: nathaneddy@gmail.com

Twitter: @dropdeaded209

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