The medical sector is constantly trying new medicine and drug combinations to help lead to the most effective cancer treatment. There are an endless number of new cancer drugs in development and new research published daily, with the intention of helping treatment through personalized combinations that target specific building blocks of their disease. There is so much for both patients and doctors to process regarding the best option for each case that the introduction of AI to this process is a blessing to using technology for societal benefit.
Firstly, Algorithm technology has improved dramatically over the past few years and medical algorithms have shown tremendous progress and promise in “working behind the scenes to aid in diagnosis, treatment, short- and long-term prognosis, care management and claims processing.” Various organizations have confirmed the importance of this step forward in healthcare however what should be noted is that bodies like Cancer Research UK have said, “it could become a useful toll for doctors”. This tells us that it is important to remember this this kind of AI isn’t about hospitals being taken over robots it’s about developing an intelligent algorithm that can spot complex patterns and detect cancerous tumours.
Until this point cancer surveillance relies on manual analysis of clinical reports to extract important bimarkers of cancer progression and outcomes. The use of AI will be to generate new information as well as better utilizing existing information. In addition, it will help researchers sift through massive amounts of data and uncover subtle patterns and relationships. That information will help researchers determine the best treatment for a particular person. The three following businesses are using AI and technology to improve cancer survival rates, diagnosis and disease management.
|Figure 1: CureMetrix logo|
CureMetrix is focusing on perfecting a powerful image analysis platform which aims to create a precision tool for mammography. This is very much a piece of technology aimed at helping an already solid medical team giving them data driven answers they need to support patients and their healthcare team as they make decisions about breast cancer screening, treatment and diagnosis. Through the use of the most advanced technology they will hopefully lead to improved clinical outcomes, reduced healthcare costs and increased assurance that patients are getting the highest standard of care available from screening through to post-biopsy follow-up.
2. Cyrcadia Health
Another collaborative piece of technology that can give women more control over their health. The iTBra features two wearable, comfortable intelligent breast patches which detect circadian temperature changes within breast tissue. This information is then processed through a smartphone or PC, and then forwarded to the Cyrcadia Health core lab for analysis. They then employ machine learning predictive analytic software, a series of algorithms to identify and categorize abnormal circadian patterns in otherwise healthy breast tissue, and the results are then passed on to health care providers. They focus on dense breast tissue as an issue for normal mammograms and how their technology can give a much more effective reading, with 1 out of 8 women being affected by breast cancer this development is most certainly worthwhile.
3. Project Hanover
|Figure 2: Hoifung Poon who is helping to lead Project Hanover|
This project is striving towards an AI-powered decision support for precision medicine as there will be a huge growth in cloud-based health analytics and they are aiming to do this through three different areas:
- Machine reading: They are firstly developing NLP technology for converting text into structured databases which will allow them to build a knowledge base by automatically reading millions of biomedical articles.
- Cancer decision support: like CureMetrix they are working to develop AI technology for cancer precision treatment, with a current focus on developing a machine learning approach to personalize drug combinations for Acute Myeloid Leukemia, where treatment hasn’t improved in the past three decades.
- Chronic disease management: They have a long term aim to cut the cost in caring for cancer and other chronic diseases by developing predictive and preventive personalized medicine.
At LUCA we love to see the use of AI and Big Data for social good and hope that businesses and data scientists alike continue to strive for solutions in the medical field!