The Future of Healthcare: MIT, Bayer, and Others Leverage AI and Machine Learning
From search engines to social media, algorithms are quickly becoming part of everyday life, and businesses and academic institutions like Bayerthe Massachusetts Institute of Technology (MIT) and others use them to their advantage.
In artificial intelligence (AI) and machine learning (ML), algorithms are used to solve complex problems, especially in preventive healthcare, diagnostics and drug discovery. Keep reading to learn how these technologies are being used in the life sciences.
Bayer improves X-ray diagnostics with AI
One of the most time-consuming diagnostic tools available is radiology. First, the patient remains seated for the required length of time, before a radiologist sits down to analyze the captured images. A number of problems can arise during this long process, including misdiagnosis or overlooking a small critical detail in a scan. Industry giant Bayer saw this problem and set to work finding a solution that could shorten radiology times while increasing accuracy.
Bayer has introduced Calantic Digital Solutions, a cloud-based technology designed to improve planning and enhance radiology diagnostics using AI. Planning is optimized as patients are prioritized based on need and treated accordingly.
The technology can be used for computerized tomography (CT), X-rays or even magnetic resonance imaging (MRI). A article Posted in PharmaPhorum regarding Bayer’s new approach indicates a study conducted in 2018 that reported up to 40 million misdiagnoses per year, all attributed to medical imaging.
Gerd Krueger, head of radiology at Bayer, explained the company’s incentive to launch the new technology.
“With Calantic Digital Solutions, we are entering the fastest growing segment of the radiology market and taking the next step on our journey from product provider to solution provider,” Krueger said.
MIT praises ML and AI while highlighting ethical concerns
The renowned Massachusetts Institute of Technology recognizes the changes taking place in biotechnology and healthcare, going so far as to publish a recognition coin who states, “It was exciting to see technology that rewrites and improves on what we thought was an established health concept.”
The article goes on to explain how AI and ML have infiltrated human life under the guise of electronic assistants such as the FitBit or Siri, translating our speech into real purchases or calling 911 because dangerous vital signs have been recorded.
However, the MIT article provides a short disclaimer between the words of praise. While these systems seem omniscient, ethics cannot be programmed. Concerns about AI and the ethics of ML wonder whether the technology will mimic the way some doctors overlook or misdiagnose conditions in underrepresented populations. Because AI and ML learn by instruction, this problem could follow medicine into the technological future.
MultiOmic Health and Mesh Bio use AI to fill research gaps
While some remain skeptical of AI’s ability to uniformly improve the lives of all patients, others are stepping forward and addressing concerns.
A study based in Asia sponsored by MultiOmic Health and Mesh Bio is in the works, specifically aimed at using AI to access and analyze data from patients with chronic metabolic diseases.
Andrew Wu, Ph.D., co-founder and CEO of Mesh Bio, commented on the collaboration goal.
“We are delighted to partner with MultiOmic Health in this important study for patients in Asia. Their therapeutic development programs for metabolic disease intervention have deep synergies with Mesh Bio’s mission to develop digital care delivery solutions for these diseases,” he said.
Asian populations are historically underrepresented in medical literature and research, including in chronic metabolic diseases. The AI technology will use samples of biological substances from patients to analyze genetic, proteomic and metabolic data alongside traditional clinical and/or diagnostic tests. Information gathered may be used in future research and treatment development efforts.