Matthew Urwin | Jul 11, 2022

The healthcare sector has long been an early adopter of technological advances. These days, machine learning — a subset of artificial intelligence — plays a key role in many health innovations, including the development of new medical procedures, the handling of patient data and records and the treatment of chronic diseases.

Machine Learning in Healthcare

  • Predicting and treating disease
  • Providing medical imaging and diagnostics
  • Discovering and developing new drugs
  • Organizing medical records

Machine learning is applied in a wide range of healthcare use cases.

For instance, by crunching large volumes of data, machine learning technology can help healthcare professionals generate precise medicine solutions customized to individual characteristics. 

Machine learning and AI are expected to play a critical role in central nervous system clinical trials in the future, according to a report in the Mercury News.

Other potential machine learning developments in healthcare include telemedicine, as some machine learning companies are studying how to organize and deliver patient information to doctors during telemedicine sessions, as well as capture information during virtual visits to streamline workflows.

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Pharmaceutical companies, too, use machine learning — for helping with drug discovery and drug development. ML could one day lead drugmakers to predict the way patients will respond to various drugs and identify which patients stand the greatest chance of benefiting from the drug, for example.

Meanwhile, the U.S. Food and Drug Administration has passed a few policies that allow medical devices to use AI and machine learning technologies.

Given all these applications, we rounded up 16 companies that use machine learning in healthcare.


Machine Learning in Healthcare Examples

Machine Learning in Healthcare Examples

  • Microsoft
  • Tempus
  • PathAI
  • Kareo
  • Beta Bionics
  • KenSci
  • Ciox Health
  • Subtle Medical
  • Pfizer
  • Insitro


Founded: 1975 

Location: Redmond, Washington

Microsoft’s Project InnerEye harnesses computer vision and machine learning to differentiate between tumors and healthy anatomy using 3D radiological images that assist medical experts in radiotherapy and surgical planning. With this AI-based approach, Microsoft aims to produce medicine that is tailored to the unique needs of each patient.


Founded: 2015 

Location: Chicago, Illinois

Tempus aims to make breakthroughs in cancer research by gathering massive amounts of medical and clinical data to deliver personalized treatments for patients. Analyzing its data library with AI-powered algorithms, Tempus helps with genomic profiling, clinical trial matching, diagnostic biomarking and academic research.


Founded: 2016

Location: Boston, Massachusetts

PathAI’s technology employs machine learning to help pathologists make quicker and more accurate diagnoses. The company also offers AI tools for compiling patient info, processing samples and streamlining other tasks for clinical trials and drug development. A partnership network of biopharma groups, labs and clinicians equips PathAI with the resources to provide more effective treatments for patients.


Founded: 2004 

Location: Irvine, California 

To support the tech and business needs of independent practices, Kareo offers a cloud-based clinical and business management platform. Organizations can transfer patient health and financial data over to Kareo’s billing platform, making it easier to manage records and complete transactions. In addition, Kareo applies AI technology to automate repetitive tasks, cutting down even more time and operational costs for practitioners.

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Founded: 2015 

Location: Boston, Massachusetts

To make the lives of diabetes patients more stress-free, Beta Bionics is developing a wearable “bionic” pancreas called iLet. This device — which is still in the investigational stage — constantly monitors blood sugar levels in patients with Type 1 diabetes, so patients don’t have to shoulder the burden of tracking their blood glucose levels on a daily basis.


Founded: 2015  

Location: Seattle, Washington 

KenSci uses machine learning to predict illness and treatment, so physicians can intervene earlier and help patients avoid potentially serious events. With KenSci’s analytics, healthcare professionals can also predict population health risk by identifying patterns and surfacing high risk markers and model disease progression.


Founded: 1976 

Location: Alpharetta, Georgia

Ciox Health powers its Datavant Switchboard platform with machine learning to give healthcare professionals faster access to patient data. Organizations can develop personalized controls within the platform, allowing staff to submit requests for specific types of data. Ciox Health’s technology also follows privacy compliance rules to keep patients’ electronic health records secure.


Founded: 2017 

Location: Menlo Park, California 

Subtle Medical taps into the potential of AI, machine learning and deep learning to produce clearer medical images for radiologists. With its product SubtleMR, the company is able to block out image noise and focus on areas like the head, neck, abdomen and breast. Higher-quality images make it easier for radiologists to finish exams, reducing the time it takes for patients to receive care and diagnoses.


Founded: 1848 

Location: New York, New York

With the help of IBM’s Watson AI technologyPfizer uses machine learning and natural language processing for immuno-oncology research about how the body’s immune system can fight cancer. This partnership enables Pfizer to analyze large amounts of patient data and develop faster insights on how to produce more impactful immuno-oncological treatments for patients.


Founded: 2018

Location: San Francisco, California

Insitro combines machine learning and computational biology to make drug development more efficient and cost-effective. After building predictive models from massive biological data sets, the company applies machine learning to sift through this data and reveal crucial trends, such as new disease subtypes. Health professionals at Insitro can then adjust drugs and medicines to better protect patients from evolving diseases.


Founded: 2015

Location: Boston, Massachusetts

Via its machine learning platform and contingent AI, Biosymetrics helps organizations analyze large amounts of raw data to streamline the development of precision medicine. The company has access to millions of electronic health records and human-relevant disease models, allowing its platform Elion to deliver more comprehensive insights on how to improve medicines.


Founded: 2018 

Location: New York, New York

ConcertAI uses machine learning to analyze oncology data, providing insights that allow oncologists, pharmaceutical companies, payers and providers to practice precision medicine and health. The company’s product RWD360 serves as an extensive database for tumor clinical data, so healthcare professionals can fine-tune treatments with demographic and clinical patient info.

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Founded: 2015

Location: Denver, Colorado

Orderly Health serves organizations with a B2C concierge chatbot that interacts via text, email, Slack and video conferencing. The company’s goal is to help employers and insurers save time and money on healthcare by making it easier to understand their benefits and locate the least expensive providers.


Founded: 2012

Location: Santa Monica, California

MD Insider’s platform uses machine learning to better match patients with doctors. After collecting data from thousands of institutions, machine learning technology analyzes physician factors such as years of experience and quality of service. This way, health networks can pair patients with doctors who are able to provide treatments that meet their individual needs.


Founded: 2010

Location: New York, New York

Prognos Health gives healthcare organizations more complete patient profiles by using machine learning to compile and analyze data from prescriptions, medical claims, lab results and other sources. With the company’s marketplace Prognos Factor, companies can quickly sell and acquire health data to detect diseases, underwrite policies and note gaps in care.


Founded: 2006 

Location: Framingham, Massachusetts

Berg’s Interrogative Biology platform employs machine learning for disease mapping and treatments in oncology, neurology and other rare conditions. Using patient-driven biology and data, cell models and clinical data, the company allows healthcare providers to take a more predictive approach rather than relying on trial-and-error experimentation.


Dawn Kawamoto contributed reporting to this story.  

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