Cancer Screening & Early Detection
AI in Cancer Screening Trials: The Potential and the Problems
AI has radically changed the medical industry. Doctors use it to create custom treatment plans and analyze the results of the treatment. Researchers use it to collect and analyze large amounts of medical data. There is even an AI-designed drug making its way through clinical trials. Given these facts, it's not surprising that experts have found multiple ways to include AI in cancer screening trials. Even so, some challenges remain, as artificial intelligence, despite its ability to solve problems in ways that humans never could, has some limitations that could pose challenges for medical facilities that want to utilize the technology to prevent and treat health conditions.
AI in Cancer Screening Trials: The Potential
One exciting area of research involves using AI to analyze disease data and predict the odds of cancer development in different population segments. Instead of trying to motivate everyone in certain age groups to schedule cancer screenings (which, at present, can only detect certain types of cancer), doctors would be able to input a patient's data into an AI-powered database to determine how likely it would be that a particular patient would develop any type of cancer. High-risk patients could then be informed so they could undergo further screening to catch cancer early on.
Other studies have focused on the use of AI in improving the accuracy of existing screening tools. In this setting, AI would be used after a person has undergone cancer screening to detect evidence of cancer that a doctor wouldn't be able to see on his or her own. AI has the potential to be used with CT scans, mammograms, blood tests, and liquid biopsy screenings to analyze results and offer expert advice on treatment options.
Additionally, some cancer screening researchers are using AI to improve clinical trial matching. AI has the potential to help determine the scope of a trial, making it possible for researchers to conduct testing that would otherwise have been considered outside the realm of possibility. Furthermore, AI has the potential to help scientists select the right participants for a particular trial. This could enable researchers to start trials faster and with more suitable participants than in times past.
AI in Cancer Screening Trials: The Problems
While AI has the potential to revolutionize cancer screening and preventative care, there are some problems that need to be ironed out in order for this tool to be used to its fullest potential. Perhaps the biggest issue that cancer screening researchers have on their hands is AI's inherent biases. AI is trained on data sets collected by the medical industry, and this data is often incomplete, flawed, or even inaccurate. For example, AI may not recognize cancer risks in certain demographics simply because there is not as much healthcare data available for certain minorities as there is for Caucasian patients. Furthermore, current AI recommendations may be based on past gender biases in treatment simply because AI doesn't have sufficient data to make more accurate recommendations. This can be addressed and remedied with the intentional inclusion of additional data from minority demographics, but it will take time for researchers to collect enough data for AI to make accurate diagnoses of patients of all ages, genders, and ethnic backgrounds.
Privacy is yet another concern that researchers are working to address. The HIPAA Privacy Rule makes it clear that doctors, nurses, and medical researchers must not expose medical data and information that can be used to identify specific patients. Before widespread use, AI models must be trained to completely anonymize patient data without removing important information that screening tools need to accurately detect cancer and other health conditions. There are indications that current AI models can, with minimal human scrutiny, anonymize data in line with HIPAA requirements. However, as AI involvement in healthcare screening and treatment grows, additional research and development are needed to ensure that sensitive information isn't inadvertently leaked to unauthorized third parties.
AI will likely play at least some role in just about every modern cancer screening trial. Its ability to sift through data and offer expert recommendations, coupled with the fact that it can catch indicators and information that humans can't, makes it a key tool in the medical industry's efforts to find screening tools to catch any type of cancer in its earliest stages. It's not perfect; in fact, it has some serious issues that need to be addressed and remedied before it can be used for cancer screenings by the medical community at large. Even so, its amazing potential remains as medical researchers look for ways to create and distribute affordable, accurate cancer screening tools that can save tens of thousands of lives around the world.
