Imagine being able to efficiently analyze data on patient clinic visits, prescribed medications, lab tests alongside external data from social media, credit card transactions, and health-relevant internet search logs — and you’ll begin to get a sense of how AI and machine learning in healthcare could create a paradigm shift within medicine. Companies are using AI and machine learning to tackle some of the most complex challenges in diagnosis and patient care, developing cutting-edge technology to improve the lives of millions.

Here’s a look at how ten medical technology companies are using AI and machine learning in healthcare to transform the current medical landscape.

1. Google DeepMind

              Headquarters: London, United Kingdom

              Funding: $500M

Following an announcement in April 2023, DeepMind and the Brain team from Google Research merged into a new unit, Google DeepMind, leveraging their collective expertise to drive AI and machine learning in healthcare. With the goal of “solving intelligence to advance science and benefit humanity,” Google DeepMind has developed AI algorithms to address a range of pressing issues in healthcare, from predicting patient deterioration to improving breast cancer screenings. 

One notable scientific breakthrough Google DeepMind achieved was its ability to reliably determine a protein’s structure from just its sequence of amino acids — a problem that scientists have been trying to solve for decades. The AI system designed to solve this problem, called AlphaFold, analyzed around 100,000 known proteins to predict a protein’s shape down to atomic accuracy. “It is already accelerating the research of diseases and medicines. The fact that we can use AI to solve a task that science has been trying to solve for decades shows how much potential it has,” said Demis Hassabis, CEO and co-founder of DeepMind.

2. Ada Health

              Headquarters: Berlin, Germany

              Funding: $189.5M

Named after Ada Lovelace, the first computer programmer, Ada Health is a digital health company that supports patients and clinics with high-quality medical insights and decision support. At the core of Ada Health’s offering is their mobile app, named Ada, which utilizes AI and machine learning to deliver symptom assessment and health information. The app’s algorithm sources information from medical literature, clinical guidelines, and real-world data from millions of anonymous patients to provide personalized recommendations, complemented with healthcare providers’ services.

“We believe that Ada’s technology can help people all over the world, including people who maybe don’t have full access to the healthcare that they need,” said Dr. Claire Novorol, CMO and co-founder of Ada Health. “We’ve always tried to make Ada as accessible as possible where we can, which is why we launched in more than 160 countries pretty early on and made the consumer app available freely in many, many different languages.”

3. Vicarious Surgical

              Headquarters: Waltham, Massachusetts

              Funding: $185.2M

Vicarious Surgical, a surgical robotics company, was created with inspiration from the movie Fantastic Voyage in which a team of scientists shrink down to microscopic size in order to remove a blood clot from the human brain. “Of course, shrinking people is the work of a science fiction movie, however, it did get me thinking about the benefits of a human being “transplanted” and seeing inside a patient’s body as much as possible,” said Adam Sachs, CEO and co-founder of Vicarious Surgical. “That is the path of thinking this film sent me down, and it would eventually result in me working to make this concept and technology a reality.”

The first surgical robot to receive Breakthrough Device Designation by the FDA, Vicarious Surgical’s robot design combines robotics, virtual reality, and AI to revolutionize minimally invasive surgery. Their robot-assisted surgical system, consisting of a camera and two robotic instruments, uses AI algorithms to guide surgeons through complex procedures. With 28 sensors per arm, the robot is able to move freely in all directions and work from any entry point.

4. Nano-X Imaging

              Headquarters: Jerusalem, Israel

              Funding: $300M

Nano-X Imaging, commonly called Nanox, is a medical imaging technology company designed to empower clinicians, researchers, and patients with data. Their goal is “to increase access, reduce costs, and enhance the efficiency of routine medical imaging technology and processes, in order to improve early detection and treatment, which Nanox believes is key to helping people achieve better health outcomes, and, ultimately, to save lives.”

Nanox has a suite of proprietary medical imaging technology, including the Nanox.ARC, a low-cost Tomosynthesis system, Nanox.CLOUD, a software platform that connects with Nanox.ARC to streamline radiology diagnostics, and Nanox.AI, a collection of AI algorithms that draws from 30 million patient records and 500 million images to analyze CT imaging to detect for early signs of chronic diseases. Nanox.AI’s use of machine learning in healthcare has already left a prominent impact—their AI algorithm that detects coronary artery calcification was recently cleared by the FDA and works to identify patients at risk around the world.

 

5. Butterfly Network

              Headquarters: Burlington, Massachusetts

              Funding: $530M

4.7 billion people around the world lack access to medical imaging. Butterfly Network is bringing medical imaging to underserved communities with its handheld, pocket-sized ultrasound device, the Butterfly iQ+. The device uses AI and machine learning algorithms to generate high-resolution, real-time images, allowing healthcare providers to perform ultrasound examinations at the point of care. To date, Butterfly Network’s technology has reached thousands of people, advancing their mission of democratizing access to ultrasound imaging.

“When you work in healthcare, you hope to maximize the opportunity for impact and drive societal change. Butterfly is doing that,” said Joseph DeVivo, CEO of Butterfly Network. “I’m so excited to join Butterfly because it can bring millions of patients greater access to early detection, enable caregivers to help patients sooner and, ultimately, forge a path to significant reductions in healthcare spend. It’s the right place to be to do right by society.”

 

6. Tempus

              Headquarters: Chicago, Illinois

              Funding: $1.3B

Tempus envisions a world where data in healthcare is accessible and useful. “A few years ago, when a loved one was being treated for cancer, I was amazed that doctors didn’t have access to the same technology and data that has transformed so many other industries,” said Eric Lefkofsky, the founder and CEO of Tempus. “The experience set me on this quest to try to figure out if there was a person or a company that was applying technology at scale to help cancer patients in a clinical setting.”

With the vision of AI-powered precision medicine, Tempus has developed a platform that accelerates the discovery of novel targets, predicts the effectiveness of treatments, identifies life-saving trials, and diagnoses diseases earlier. With 100+ petabytes of data and 6,000,000+ de-identified research records, Tempus has collected one of the world’s largest libraries of clinical and molecular data, sourced from electronic healthcare records, imaging data, and radiology scans to “help shape the treatments of tomorrow.”

7. Atomwise

              Headquarters: San Francisco, California

              Funding: $176.6M

Drug development is a process that often takes 10 to 15 years and can cost an average of $2.5 billion to bring a new drug to market. Atomwise uses patented machine learning technology, called the AtomNet model, to transform the field of small-molecule drug discovery. Atomwise aims to “make novel, better and safer drugs, with the ultimate goal to get medicines into the hands of patients faster,” said Abraham Heifets, CEO and co-founder of Atomwise.

AtomNet technology is the “first drug discovery algorithm to use a deep convolutional neural network,” studying vast quantities of target and ligand data to predict the binding of small molecules to proteins. For the past two years, AtomNet has been in active use for real drug research, predicting candidate treatments for more than 600 unique diseases, from Ebola to Parkinson’s.

 

8. PathAI

              Headquarters: Boston, Massachusetts

              Funding: $255.2M

On a mission to “improve patient outcomes with AI-powered pathology,” PathAI combines the use of machine learning in healthcare with vast amounts of medical data to advance drug and diagnostic development. The company is working to transform the current medical practice of pathology — in which diagnoses are made using microscopes and glass slides — into a data-driven process where diagnoses can be augmented with AI and pathologists can work with digital glass slides. “Instead of just using a microscope, now they’re going to have the world’s most powerful AI pathologist assisting them in making diagnoses faster and more accurately,” said Andrew Beck, CEO and co-founder of PathAI.

PathAI has pioneered a variety of impactful initiatives, including PathAI’s AISight, a precision pathology platform that allows researchers, academic institutions, laboratories, and physicians to view whole slide images. They also help hundreds of providers with pathology diagnoses through PathAI Diagnostics, a laboratory service that uses AI technology trained with data from more than 15 million annotations.

9. Esper Bionics

              Headquarters: New York, New York

              Funding: $150K

A study conducted in 2017 concluded that 57.7 million people were living with limb amputations worldwide. In just the United States alone, around 185,000 amputations occur annually. Unfortunately, only about 5% of amputees have access to prosthetics because of their high cost and barrier to use. New-York based startup Esper Bionics is tackling this problem with their AI-powered prosthesis, designed to be incredibly dexterous and light. The Esper Hand has 24 sensors that detect the movement of 20 muscles in the forearm and utilizes advanced machine learning algorithms to predict the user’s movement and optimize their grip.

“When developing Esper products, we always remember that it’s about rewriting millions of life stories, about helping people live more fulfilling lives. In our development process, technology and design play together,” said Dima Gazda, CEO and co-founder of Esper Bionics. “Marrying these two makes it possible for us to incorporate the beauty, diversity, and evolution of a human body into designing Esper products.” 

10. Eko

              Headquarters: Oakland, California

              Funding: $128.2M

The COVID-19 pandemic has rapidly increased the adoption of remote health: telemedicine services to patients from a distance, rather than face-to-face, with the use of digital technologies. While telehealth often simply means a video chat with a clinician, companies like Eko are building a platform of machine learning algorithms and proprietary sensors to help remote health reach its full potential. The company produces digital stethoscopes that analyze a patient’s heart rhythm, comparing it against a repository of tens of thousands of past patient exams in seconds to detect early heart and lung problems.

With a 99% accuracy rate, Eko’s machine learning algorithms have proven to be significantly more accurate at detecting potential heart and lung problems than traditional stethoscopes, used by human physicians. “These algorithms can be accessed anywhere in the world, enabling better care for patients regardless of where they are,” said Connor Landgraf, CEO and co-founder of Eko.

Future Outlook

These medical tech companies exemplify the power of AI and machine learning in healthcare. By leveraging these technologies, they are enhancing diagnostic accuracy, enabling personalized medicine, automating medical imaging analysis, and streamlining healthcare workflows. As AI continues to advance, the potential for improving patient outcomes and transforming healthcare as a whole becomes even more promising.

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