Artificial intelligence (AI) is breaking new ground in healthcare, especially for cancer detection and treatment. This rapidly-evolving technology is streamlining oncology, making early detection and treatment more possible than ever before. Here’s more about AI and cancer detection, diagnosis, and treatment.
How AI is Transforming Cancer Detection and Treatment
AI is a powerful pattern recognition tool, making it invaluable for cancer detection, cancer research, cancer treatment, and more. While AI curing cancer is unlikely (at least, right now), AI that detects cancer and AI in cancer treatment is here — proving what a powerful breakthrough AI for cancer can be.
It all starts with research. AI in cancer research involves utilizing machine learning algorithms to analyze data, removing bias and human error in interpreting complex statistics. It can also summarize research studies to make it easier for busy, practicing oncologists to stay up-to-date on the latest cancer research findings.
However, cancer AI shows the most promise in early detection and personalizing cancer treatment.
AI in Early Cancer Detection: Breaking New Ground
One of the biggest issues plaguing oncology is how to detect cancer early. Before AI, early cancer detection tests depended heavily on human interpretation of medical imaging. And while we trust and appreciate the expertise of oncology practitioners, AI cancer detection methods can pick up on minor aberrations that may not be visible to the human eye. AI has proven particularly useful at identifying the following types of cancer:
- Breast cancer
- Lung cancer
- Skin cancer
- Colorectal cancer
- Brain cancer
However, it’s not limited to just these types. A properly trained AI can be used to detect any type of cancer in medical imaging.
In addition, AI technology can analyze medical imaging and lab work with incredible speed and precision. It can also flag certain images or lab results so that they can be more closely and carefully analyzed by oncologists or other healthcare professionals.
Personalized Cancer Treatment: AI-Driven Precision Medicine
Highly individualized therapies are the future of cancer treatment, and AI offers a way to streamline the process of creating personalized treatment plans. Based on inputs regarding an individual patient’s genetic profile, medical history, risk factors, and response to current treatments, AI can almost instantaneously offer calculated predictions about which treatments to pursue next. This saves oncologists’ valuable time and helps prevent wasted time and resources on treatments that may not be effective for a patient based on the big picture of their health status.
Using natural language processing, AI can also interpret written chart notes to provide even more personalization.
Additionally, AI can flag potential drug interactions as they arise — eliminating the need for a member of the oncology team to pull out a reference book to look up interactions manually.
AI is also being used in the development of customized cancer vaccines. These vaccines use the genetic sequence of a person’s cancerous cells to “immunize” them, helping their immune system to mount a more robust defense against cancer. AI can be used to help streamline both the genome sequencing process and the manufacturing of these immunotherapy vaccines.
AI vs. Traditional Cancer Diagnosis: Advantages and Challenges
As you can see, AI offers many advantages over traditional cancer diagnosis. More precise than the human eye, it has revolutionized early cancer detection.
It’s also a valuable tool in cancer therapy — offering personalized treatment guidance and streamlining treatment plans, so oncology teams can more effectively and efficiently care for cancer patients.
However, there are also some challenges to incorporating AI in cancer healthcare. These include:
- Data privacy concerns: To be properly trained, AI programs need access to a great deal of sensitive medical data. While it is possible to uncouple medical data from identity data for the purposes of training AI, it’s important to do this ethically and to get patient consent for their data to be used in this way.
- Access to large amounts of data: Related to data privacy, AI requires access to huge amounts of medical data in order to be accurate. Amassing large amounts of data from diverse groups of people, and ensuring that AI has consent to use this data, can be a major challenge.
- Legal and regulatory compliance: AI must be trained to work within the legal and regulatory parameters set forth in different countries, regions, states, etc.
- Integration with electronic healthcare systems: AI technologies must be able to integrate seamlessly into existing electronic medical record systems. If there is friction between AI and the existing system, it’s likely that integrating AI will be a challenge at the ground-level — among professionals working directly with cancer patients.
With the advent of AI cancer treatment, there are oncologists, cancer researchers, software developers, and regulatory agencies actively working on solutions to these challenges. Because we know how helpful AI can be in healthcare and cancer treatment, experts are making it a priority to address these issues.
The Future of AI in Oncology: What’s Next?
Will AI cure cancer? No, of course not. We will always need a human touch. However, it’s one more tool in our arsenal — one that’s powerfully perceptive and that can continuously learn and synthesize new information to help direct cancer research, detection, and treatment.
AI could be a tool that helps us find a cure, and we are looking forward to seeing how AI can be utilized next to help treat this disease. Be sure to follow along at 2Cancer — we will keep you updated as artificial intelligence and cancer treatment continue to evolve.