Cancer is one of the leading causes of death in the U.S. Every year, over half a million people die as a result of this dangerous condition. Meanwhile, millions more are diagnosed. With a public health crisis this big, only big data provides the means to better understand and combat the illness.
That’s because big data is impacting healthcare by streamlining the quality, safety, and accessibility of care. In cancer treatments, the same is true. Big data plays an important role in the fight against cancer through its ability to collate patient insights, reveal new treatment methods, and increase our understanding of cancers in general.
The applications of big data in cancer treatment are broad and full of potential. Here, we dive into the role big data plays in the fight.
First, big data maximizes the potential of oncologists to monitor and treat their patients accurately based on the most recently available information. It’s difficult to collect individual healthcare metrics without also collecting a range of additional data. But all of this information can translate to revelations in the course of cancer treatments with the proper application of big data analytics.
But before any service improvements can be made, cancer treatments must support big data collection in a way that is beneficial to the patient and does not put them at greater risk. Fortunately, this is increasingly possible through innovations in big data technologies.
Big data analysis tools are at the forefront of information technology, empowering the latest information trends. These technologies include:
The IoT is revolutionizing the amount and quality of data able to be collected and processed by a medical team. These smart tools represent a range of sensors and monitors, many of which stand to improve the transparency and reaction time for treating cancer patients.
For example, researchers have devised an IoT system that works in conjunction with a wearable wristband to provide in-home cancer care solutions that are competitive with a hospital experience. From here, cancer care is more accessible and comfortable for patients.
Wearables often go hand-in-hand with IoT systems to track all kinds of patient information. From blood pressure to weight, these tools allow patients to help doctors by sending them accurate information in real-time. As a result, warning signs can be spotted much sooner.
These wearable devices are already being applied in cancer treatment. Researchers made use of wearable bands to report activity levels of chemotherapy patients back to doctors. Their objective health data was then assessed in comparison to rates of emergency visits. Through this wearable-enabled research, clinicians determined that low activity patients were at higher risk of emergencies.
It’s precisely revelations like these that stand to improve how doctors and patients coordinate to fight cancer successfully. Fortunately, data analytics and AI take the potential of big data even further.
Without artificial intelligence, care providers would be hard-pressed to generate better cancer-fighting treatments. AI in big data analytics allows clinicians to parse stores of data far too vast for traditional analytics. The AI crawls over, categorizes, and connects data points to point out revelations in the course of cancer treatment. As a result, problems can be spotted sooner and more accurately.
We’ve seen great strides in diagnosing and treating cancer with the help of big data analytics. In one example, researchers at Massachusetts General Hospital employed a deep learning algorithm to screen mammograms and assess the risk of breast cancer in female patients. The model for predicting risk outperformed traditional assessments. In the future, these tools will continue to improve and become more common in patient care.
With tools like these, all kinds of health metrics can be collected that not only inform on the conditions of patients with cancer but produce a network of connected data points as well. From here, greater insights into patient health are just a step away.
With the potential for all kinds of treatment revelations inherent in big data collection, cancer researchers should be paying special attention to the field of analytics. Big data, like clinical trials, can illustrate possibilities never before thought feasible. This makes applying data in the course of cancer research a must.
All the time, new and innovative approaches to cancer treatment are being developed. Take bioengineering and immunotherapies, for example. Immunotherapy is the process of using a patient’s own immune system to help them fight off cancer and send it back into remission. And this method has had incredible results so far. One trial achieved remission rates of around 90%.
However, the T-cell alteration or checkpoint inhibitor drugs needed to galvanize a patient’s immune system have to be carefully honed to specific proteins and receptors. That’s where big data can make a difference.
Big data, collected and stored respecting patient privacy, can contain the information necessary to optimize these treatments to individual patients. Regardless of how this data is generated, it falls in line with the big data definition as information too vast to be understood using traditional analytics. Instead, researchers require big data systems and AI analytics tools to help them identify the potential of new forms of treatment through assembled medical information.
By applying these resources in cancer care, our understanding of all forms of cancer stands to reach new heights. Could big data even mean the cure for cancer in the future?
Because accumulated medical data provides research potential, big data analysis in oncology can produce insights into patient care. As the level and complexity of this data and the tools to assess it improve, it’s only a matter of time before more ground-breaking innovations in cancer treatment are made.
Big data means information, and what oncologist wouldn’t want to arm themselves with more information in the fight against cancer? Care facilities and patients alike must be careful of how much data is collected and exposed, however. Data presents risks. Too much data can lead to a breach and exposure of sensitive information. Instead, the latest tools, tech, and big data storage strategies should also be applied to help secure an informative network of health insights.
From here, maybe the cure for cancer is right around the corner, ready to be pointed out by an AI algorithm.