Early lung cancer detection with artificial intelligence:
A guide for patients
The earlier the better
The earlier doctors can diagnose lung cancer, the easier they can treat it.
Unfortunately, lung cancer is difficult to catch on time. Symptoms such as persistent cough or shortness of breath develop late, when the disease has already advanced.
Medical imaging plays a central role in early lung cancer detection. Chest CT scans – which are detailed chest images using a very low dose of radiation – may show lung nodules. These are tiny lesions in the lung and may be signs of early disease. But to interpret these findings, we need radiologists.
Why do we need AI in radiology?
For starters, we don’t have enough radiologists.
Only two thirds of the radiology roles are currently filled in the UK; the US are not doing much better. And, as the world’s population is growing and ageing, there are more and more medical images to read. Thus, radiologists are under pressure.
To detect lung cancer early, they must find very tiny lung nodules in the 200-300 images that constitute a CT scan. They then need to measure these nodules and monitor their growth over time, which are manual, cumbersome tasks. Due to the nature of this work and the high volume of scans, radiologists may feel tired, stressed, or bored – they are human, after all.
Artificial intelligence (AI) is the perfect radiology assistant. It can automatically find, measure, and track the growth of lung nodules, with excellent precision, and without ever getting weary.
Getting the terms right
Artificial Intelligence (AI) is sophisticated software created by computer experts and data scientists.
You may have heard of AI, but also about ‘machine learning’ and ‘deep learning’. These words are often used as synonyms, yet they refer to different things.
Imagine a Russian doll. The outer doll is AI, the overarching concept. Machine learning is a subset of AI, a technique to train computer systems to perform specific tasks. Deep learning is a class of machine learning algorithms. It focuses on processing big data to learn how to identify patterns automatically.
No AI without data
AI systems need a lot of data to do pretty simple things. We are much better learners ourselves.
Once we see one chair, we will easily identify the next one because we use our experiences to understand what the object is and how it is used.
On the other hand, an AI system might need to see 10,000 images of chairs, each with a label that says ‘chair’, before it can recognise one on its own. But once it has ‘learned’ what a chair is, it will spot the next one in under a second, in a stack of furniture, even after seeing hundreds of stacks for days in a row.
So, with lots of data, AI can help us or even do specific things better than us. Imagine if we used this power to find early signs of cancer!
AI in the
AI in medical imaging is the radiologists’ extra pair of eyes. It helps them manage their workload and make sure they don’t miss anything. The doctor always has the final say in your diagnosis, treatment, and next steps. This will not change anytime soon - AI is very, very far from replacing physicians.
Your journey as a patient stays the same. You will still see a radiographer when you come for a scan and your doctor to discuss the results once a radiologist has reported your scan. A radiologist using AI might have more time to focus on your case or explain the results than one who is not.
To get a better idea of how AI is helping radiologists, let’s have a look at what we do. Here is an example of how our AI-based solution, Veye Lung Nodules, is used to detect and manage possibly threatening pulmonary nodules:
Answers to your
It may seem like AI is all about big data, but, actually, it can play an essential role in making medicine better tailored to your unique needs.
AI systems can compare your data with thousands or hundreds of thousands of other patients with similar illnesses. As a result, the system could predict, for example, the chance that you will develop a specific condition or how well you would respond to a particular treatment.
The doctor is always the one to make the final diagnosis or treatment decision based on the information on hand.
No data is used without your consent. When you visit a hospital for a scan, you will be informed of how your health data is used and asked for permission before proceeding.
At Aidence, we use the most advanced technical and organisational measures to protect the data we process. As such, we comply with the European Data Protection Legislation and with requirements set out in the ISO 27001, an international standard on managing information security. For more on how we process patient information, have a look at our data processing policy.
AI companies, like all medical companies, are under strict legal scrutiny by relevant authorities. In the EU, any devices that support physicians in diagnosing severe conditions must comply with EU legislation (Conformité Européenne or ‘CE’). In the US, medical devices must be approved by the Federal Drug Administration (FDA).
AI helps your doctor make better decisions and have more time to focus on the more complicated cases. AI is a new technology, and we are still learning and investigating its full impact on healthcare. We are regularly publishing new research into our products on this page.
By agreeing to share your health data for research and medical device development.
Spot the difference
Early symptoms of lung cancer are often subtle and easy to dismiss as something else.
Learn to recognise them and take action.
A campaign from Roy Castle Lung Cancer Foundation
Learn about the signs, symptoms and not so well-known risk factors associated with lung cancer.
A campaign from Lung Cancer Europe (LuCE)
Look up 'TLHC'
Across England, current and past smokers ages 55-74 may be eligible for a lung health check. If you received an invitation from your GP, go for a free check – even if you feel fine.
You can find more info on the programme here.
Join a study
The French CASCADE study aims to demonstrate that chest CTs for lung screening can be read by a single trained radiologist, with AI. Women meeting eligibility criteria are invited for a low-dose scan.
Learn more here.