MedWhat is a medical artificial intelligence company based in Silicon Valley. We are building a unified algorithmic architecture to achieve human-level intelligence in medicine. Currently, we are focused on deep learning for medical conversations, diagnosis & treatment, medical questions answering, medical image recognition, personalized medicine, and curation of genetic variance in biotechnology. We are interested in general solutions that work well across multiple medical domains and tasks.
One of our products is Medwhat’s AI Personal Medical Assistant which answers consumers’ health and medical questions by personalizing the answers using user’s EMRs. Our Personal Medical Assistant can help payers and providers keeping patient population healthy, patient engagement after discharge from doctor office or hospital, and lower readmission rates. We offer two tiers, Tier 1 is a free app for consumers for general answers and Tier 2 a paid app for a personalized assistant used through providers and payers.
MedWhat has an enterprise product for doctors, nurses, and hospitals. MedWhat’s Artificial Intelligent Doctor can help medical providers scale faster, take care of ‘blind spots’ while practice medicine and seeing patients, make less errors, prevent wrongful deaths by human mistakes, and improve patient outcomes.
The MedWhat team leverages progress in machine learning and computer vision communities, and we are always looking for exceptional researchers to join our team.
MedWhat Offers a More Intelligent Conversation About Healthcare
While access to insurance and healthcare in the United States is expanding, the healthcare industry is under relentless pressure to deliver quality care to more people at lower cost. The scarce resource at the center of the healthcare economy is the time and attention of medical professionals. There are only so many providers and so many hours in the day to follow up on patient care and respond to routine questions.
So far, technology has not addressed this issue very well. Information resources for patients online are spotty at best, and the medical profession has been slow to adopt the kind of tools that have boosted productivity in other industries. The results? Unreliable information, poor patient experience and systemic inefficiencies.
But now, a team of healthcare and data science experts from Stanford has developed a patient-centered solution that uses cutting edge machine learning and artificial intelligence (AI) to assist healthcare providers, improve outcomes and reduce costs. And to access those benefits, all you have to do is ask.
Let’s have a chat. From Apple’s Siri to Microsoft’s Cortana and Amazon’s Echo, we are becoming more accustomed to interacting with our technology through conversation. While general purpose chatbots can help with personal productivity and other tasks, they are not “trained” to be experts in any one domain. If you want to talk medicine with an AI, you need a specialist.
Enter data scientist Arturo Devesa. He saw an opportunity to combine the simplicity of a voice-based chatbot with the growing needs of the healthcare industry. Working with Stanford colleagues Dr. Mark Munsen (Biomedical informatics director), Dr. Oliver Aalmi (Hospital professor) and David Iraola (Ph.D. in natural language processing and machine learning), Devesa founded MedWhat to build and deliver a solution to fit the needs of patients, providers, institutions and insurers.
“Doctor-patient interaction is at the center of the healthcare model, but demand is placing strains on the system,” says Devesa. “We wanted to find a way to use AI to extend the reach of providers by making it easier for doctors to interact with information in patient-care settings, and offering patients convenient, personalized responses to medical questions when the doctor is not available.”
A doctor in your pocket. From the patient perspective, MedWhat is an app that provides authoritative answers to medical questions, reminders and follow-ups to maintain wellness, and a single dashboard to track data from wearable sensors and other sources of data. Interacting with the technology is as simple as asking, “is it safe to take my medication with alcohol?” or “how many miles did I run today?”
But underneath the surface is a vast database containing the entire body of medical knowledge, curated exclusively from trusted sources and peer-reviewed journals. The more you interact with the AI, the more it learns about your specific health concerns and issues, so the answers it provides become increasingly relevant to your lifestyle.
“Just having this information available can make a measurable impact on individual health,” says Devesa. “It provides many of the advantages of consulting with a personal caregiver, without the cost or impact on the healthcare system.”
For that reason, he says, insurance companies are becoming very interested in promoting this technology to policyholders as a way to keep costs down.
Enhancing the capabilities of caregivers. The term “artificial intelligence” can cause alarm among professionals concerned about displacement and devaluation of their services, and few professions guard their prerogatives as closely as doctors. But Devesa says there is no need to worry that chatbots will replace MDs.
“MedWhat offers information, not diagnosis,” he says. “People will still rely on doctors to use their skill and experience. But even the best doctors don’t have access to all the current research. MedWhat gives doctors another tool to provide excellent patient care.”
In addition, MedWhat can be personalized according to the caregiver’s preferred protocols. “It’s a way for healthcare professionals to provide continuity of care according to their own practices, without having constant personal contact with the patient,” says Devesa.
Healthy for the system. Since Devesa and his team launched MedWhat in 2013 with support from Stanford, a range of insurance companies, hospitals, telehealth customers, pharama companies and institutions have taken an interest. The company has raised $1.8 million in seed money and, in 2016, joined the Microsoft Ventures Accelerator in Seattle to turbocharge its technology and sales efforts.
“A number of factors are forcing us to think about these kinds of innovations for healthcare, not just in the US but around the world,” says Devesa. “A shortage of doctors, the drive to improve outcomes with evidence-based medicine, the adoption of secure electronic medical records, an aging population that requires more routine check-ins and followup, and the emergence of new treatments.”
The MedWhat team believes they have built a smart solution that holds the cure for many of these ailments. And the beauty of it is, it keeps getting smarter.
Arturo Devesa, Founder & CEO
Arturo is a data scientist researcher and medical entrepreneur. He’s a Research Scholar at Stanford University School of Medicine. He has participated in the Stanford University startup accelerator StartX and StartXMed. Arturo has a Bachelor in Finance ’06, an MBA ’09, and a Masters of Science in Economics and Econometrics ’11 all from Florida Atlantic University. Arturo was a teaching assistant and later an adjunct faculty academic teaching statistics and information technology from 2008-2011 at Florida Atlantic University. Arturo moved in 2012 from Florida to Palo Alto to research & develop MedWhat technology at Stanford University and grow the company in Silicon Valley.
Dr. Mark Musen, Director of Biomedical Informatics Research at Stanford University’s Medical School, MedWhat Advisor
Dr. Mark Musen is a professor of medicine and a biomedical informatics researcher. He’s a member of Stanford’s Bio-X and Director of Stanford Center for Biomedical Informatics Research since 1992. Dr. Musen is a principal investigator at the National Center for Biomedical Ontology (2005 – Present). His awards and recognitions include: General Chair, Association for Computing Machinery Conference on Knowledge Capture (K-Cap ’11) (2011), Elected Member of Association of American Physicians (2010), Donald A. B. Lindberg Award for Innovation in Informatics, American Medical Informatics Association (2006). His education include a Ph.D. from Stanford University, Medical Information Sciences (1988), an M.D. from Brown University, Medicine (1980), and a Sc.B. from Brown University, Biology (1977). You can learn more about Dr. Mark Musen at https://med.stanford.edu/profiles/Mark_Musen
Sasidhar Madugula, MD/PhD student at Stanford Medical School
Sasidhar Madugula is a third year MD/PhD student at Stanford Medical School, in neuroscience. Prior to that he completed a master’s in Clinical Neuroscience at Oxford, and a bachelor’s in bioengineering at the University of Illinois at Chicago. He currently works on retinal electrophysiology with Professor E.J. Chichilnisky.