A team led by scientists at the University of California and the University of Surrey, Gilford, the UK is taking Artificial Intelligence to the heart of cancer. They are leveraging AI-powered networks to help identify, anticipate, and analyze some common symptoms of cancer patients undergoing chemotherapy.
This is the pioneering use of AI network analysis as a technique to evaluate the connection between common symptoms exhibited by a large group of cancer patients receiving chemo treatment. It’s truly groundbreaking news for healthcare as a whole.
If the AI platform works as scientists envision, it can help zero in and predict cancer development like never before. More specifically, this will have a huge positive impact on the early diagnosis, prognosis, and treatment of cancer.
Published by Nature Scientific Reports, this groundbreaking study showcases how the team of scientists employed network analysis, alongside machine learning, to examine the interconnection and structure between a group of 38 common symptoms often reported by more than 1300 on-chemo cancer patients.
“While these findings warrant confirmation in an independent sample, we believe that NA [Network Analysis] has the potential to improve our understanding of the oncology patients’ symptom experience so that individualized and targeted interventions can be prescribed to reduce each patient’s symptom burden,” says Nikolaos Papachristou, the Surrey lead scientist.
There’s a big reason to celebrate such wins in cancer prediction.
For starters, the study constitutes the first use case of NA in digging up trends between common cancer symptoms. The AI-driven platform enabled the team of scientists to identify nausea as the core symptom and place it at the heart of its network analysis.
Why does it matter? The application and development of AI solutions is a trend that’s catching on rapidly in the medical arena, particularly in prognostics, treatment management, and diagnostics.
The power of artificial intelligence to adapt and “learn” from medical data gives researchers a chance to study and predict cancer on a whole new level. AI can help improve the precision of diagnosis and cancer treatment relying on feedback responses. Oftentimes that means the feedback includes those given by research institutions, pharma, physicians, and practitioners, as well as backend database sources.
The beauty of it is that artificial intelligence platforms in healthcare often work in real time, implying that the data is always up to date, relevant, and accurate. And the data could be assembled from a diversity of forms and sources, including physical examinations, EHRs, medical notes, outputs by medical devices, medications use records, basic metrics, reported symptoms, laboratory testing, and even demographic-based assessments.
All these pieces of data, when collected, structured and analyzed through AI and machine learning, could yield incredible patient outcomes.
This study comes hot on the heels of another high-level AI application to cancer prognosis. Late last year, another team of researchers from The University of Edinburgh and The Institute of Cancer Research, London used an AI platform to predict how cancer will evolve and progress.
By anticipating the growth pattern of particular cancer, scientists and pharma companies can design the most effective treatment for each cancer patient. For example, if doctors can anticipate how breast cancer will evolve, they could take interceptive measures earlier to halt cancer in its tracks before it had an opportunity turn into a drug-resistant form. You read all about this study in the journal Nature Methods.
Despite cancer mortality rate shrinking by a whopping 27 percent in the last quarter of a century, cancer is still one of the biggest challenges for the healthcare system and researchers alike. American Cancer Society predicts that 606,880 deaths and around 1.7 million new cancer cases will occur in the course of 2019 in the US alone. Breast cancer alone accounts for 30 percent of new cases in women, while prostate cancer takes the mantle when it comes to newly diagnosed cancers in men (around 20 percent).
Whichever angle you look at it, cancer is a devastating killer. That’s why the new AI platform promises to add a new string in the fight to make it easier to diagnose and treat cancer early enough.
AI adoption is a hot topic in healthcare right now, and deservedly so. In fact, in a recent fireside chat on Artificial Intelligence in healthcare, experts agreed unanimously that the sector could use industry-wide adoption of AI.
The good news is that artificial intelligence innovation has already made inroads and demonstrated a potential to reduce costs for providers as well as improve healthcare access and quality for patients. Accenture estimates that the AI market in healthcare will be worth around $6.6 billion by 2021.
As we previously reported, the future of big pharma also is brighter than ever in the age of AI. The big 10 global pharmaceutical companies, namely Novartis, Roche, Pfizer, Merck, AstraZeneca, GlaxoSmithKline, Sanofi, Abbvie, Bristol-Myers Squibb and Johnson & Johnson, are already actively investing in artificial intelligence. They are hoping AI will be a positive force in many areas of pharma, from drug discovery and development to drug adherence management and everything in between.
Despite a few barriers, AI has been welcomed with open arms by healthcare stakeholders. A 2018 McKesson study involving over 2000 people revealed that 44 percent of Americans would trust artificial intelligence for cancer treatment recommendation or diagnosis. Men (52 percent), however, seem to have more trust in healthcare AI than their female counterparts (only 36 percent).
Healthcare CIOs are also viewing AI as a worthy investment. According to a Signify Research report, hospital CIO’s are planning to spend more than $2 billion in AI for medical imaging annually by 2023. In fact, 54 percent of the CIOs expect to witness widespread adoption of artificial intelligence in healthcare within the next half decade or so. On the overall, 83 percent of the CIOs believe that AI will provide their healthcare organizations with a competitive advantage.
As AI-driven solutions are perfected, IDC predicts that global spending on machine learning, AI, and network analysis will hit $46 billion by 2020.