The potential for more accurate health diagnoses with AI
Between Apple watches, beds with sensors, and nutrition apps, many people use digital health technology every day to track, monitor, and measure their steps, sleep, calories, reps, and countless other health markers.
But digital health isn’t limited to the individual changes we make based on what we see on our wearable devices. The benefits and use cases of digital health technology are vast, and for Navid Alipour, founder and CEO of AI Med Global, the addition of AI introduces even more compelling innovations. Let’s briefly explore digital health and one way AI is being used to develop what’s next in diagnostic medical procedures.
How Healthcare Has Gone Digital
The use of digital technology applied to healthcare purposes is considered to be digital health, with categories like mobile health, telehealth and/or telemedicine, and personalized medicine falling under this broader category.
While digital health technologies have been in use for several years, the field has grown substantially in recent years, especially in terms of AI investments. Consider these statistics:
- In 2022, the global digital health market’s value exceeded $330 billion, with forecasts showing a value of $650 billion in 2025.
- Research from Statista shows the AI healthcare market was valued at $11 billion in 2021 and is projected to grow to $187 billion by 2030.
- 56% of U.S. healthcare leaders believe AI in healthcare has already proven to be more valuable than originally expected.
AI technology already has many proven use cases in healthcare. For example, AI technology can be used to streamline office operations, such as powering more efficient precheck screenings and chatbots for answering common questions or performing basic assessments.
These improvements alone help to give healthcare providers more face-to-face time with patients, improving the patient-provider relationship. But as scientists and healthcare professionals continue to develop use cases, they’re discovering AI’s incredible potential to power life-saving procedures.
The Potential for More Accurate Diagnoses With AI
To work as intended, AI technology relies on data. “Data” covers a wide range of information; it can come in the form of basic health statistics, like what we learn from wearable devices, or from more advanced medical imaging. As machine learning algorithms improve and researchers gain access to faster computing systems, AI-powered technologies gain more speed and better accuracy in analyzing vast amounts of data to identify patterns.
Data analysis on this huge scale creates an opportunity for more accurate diagnoses and better care planning. Case in point: Alipour and his team of scientists have developed a machine-learning algorithm that detects breast cancer and a person’s risk of heart disease. The software analyzes medical images and data sets to identify anomalies, helping to diagnose breast cancer more quickly and accurately than ever before. This not only speeds up the treatment process, but also has potentially life-extending and -saving implications.
Similar technology is being developed to improve skin cancer screenings, and although this kind of AI-powered software is still in development, IBM notes that, “According to Harvard’s School of Public Health, although it’s early days for this use, using AI to make diagnoses may reduce treatment costs by up to 50% and improve health outcomes by 40%.”
Research indicates that a majority of Americans are hesitant for their healthcare providers to use AI for diagnosis and treatment, but as Alipour explains, “We're not replacing the doctor. We're empowering the doctor and we're another arrow in their quiver in this fight against cancer to deliver better care and select the optimal combinations earlier, that'll help prolong the life of a patient and save their life in many cases.”
There’s still a lot to learn before these types of solutions become more common, including how to properly regulate how data is used and solutions are deployed. As modern medicine advances and digital health solutions become more common and regulated, Alipour is optimistic about the future of healthcare. “I think historians will look back on this decade, which we're in the earlier part of still — we're at a huge cornerstone historically — and I think [modern medicine] is going to advance more in the next 10 years than the last 50 years combined.”
