Home Healthcare Importance of AI in Cancer Treatment

Importance of AI in Cancer Treatment

Both machine learning and artificial intelligence are some of the latest technologies that have benefited from considerable improvements.

Thanks to the use of algorithms, such technologies can now learn, forecast and provide advice based on huge volumes of data.

The ability of artificial intelligence to disrupt various markets has resulted in some large investments.

For instance, in April this year, the European Commission unveiled an AI plan for Europe amounting to €20 billion.

Also, France announced its €1.5 billion AI program, a move that was followed by the launch of research and development facilities such as Google DeepMind, Fujitsu and Facebook.

The healthcare sector appears to be one of the major areas to experience the impact of AI.

In this field, the technology can be utilized in data interpretation from a large amount of data collected from healthcare providers companies and payers. What’s more, the treatment of cancer could largely benefit from AI technology.

Why is AI Important in Oncology?

Currently, physicians are overcrowded with data gathered from previous treatments, co-morbidities, imaging and genomics.

With artificial intelligence, such data can be analyzed in a bid to predict a patient’s prognosis and advice the medical doctors with the various available options such as clinical trials with experimental therapies and personalized medicine.

  • AI for Precision Medicine

There’s a big potential in stratifying patients through artificial intelligence. However, the challenge is the lack of an array of personalized medicine drugs broad enough to treat all patients.

Sam Natapoff, Bloomberg’s analyst, said that drug development is intended for artificial intelligence applications.

In turn, the opportunity has lured big pharma, large AI developers and numerous startups. In fact, over one hundred startups are currently utilizing AI in drug discovery.

  • Using AI as a Diagnostic Tool

Currently, some entities are selling various solutions for AI as a service ranging from diagnosis to prognosis. For instance, in the case of breast cancer, about 5% of women who are called back after undergoing the first screening are found to be sick.

In turn, this case raises the costs, and it becomes a traumatic experience for many patients.

Therapixel, a startup focusing on medical imaging, is currently leveraging AI to handle the issue of undertaking automated mammography analysis.

  • Cutting Trial Expenses

Artificial intelligence can obtain insights from vast volumes of data and apply it to clinical trials. This undertaking can reduce the cost significantly, considering that the recruitment of patients alone represents approximately 30% of the aggregate clinical trial time.

The Horizon 2020 program gave €16 million to a massive European consortium, which includes big names such as IBM, Philips, Bayer, Charite and Institut Curie.

The move is aimed at using AI technology to boost clinical results in oncology at a reduced cost.

Obstacles to Overcome

Currently, data scientists have to handle unstructured electronic health records as well as data from multiple sources that have been structured and collected for different reasons.

Even so, most routine databases lack enough quality to be used by AI algorithms in attaining the quality standard needed for clinical trials.

Subscribe to our newsletter

Signup today for free and be the first to get notified on the latest news and insights on artificial intelligence

KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
- Advertisment -

MOST POPULAR

AI Model Development isn’t the End; it’s the Beginning

AI model development isn’t the end; it’s the beginning. Like children, successful models need continuous nurturing and monitoring throughout their lifecycle. Parenting is exhilarating and, if...