Project Background

  1. Overview

    1. What is the Human Diagnosis Project?

      The Human Diagnosis Project (also referred to as “Human Dx” or “the Project”) is a worldwide effort, created with and led by the global medical community, to build an open intelligence system that maps the steps to help any patient. By combining the collective intelligence of medical professionals and trainees with machine learning, Human Dx intends to enable more accurate, affordable, and accessible care for all. The Project’s creation and development has been inspired by other civilization-scale scientific projects (e.g., the International Space Station, the Large Hadron Collider at CERN, and the Human Genome Project) and open technology efforts (e.g., Wikipedia, Linux, and the Internet Protocol Suite).

      The Project is structured as a partnership between the social, public, and private sectors. Its partners include many of the nation's top medical societies (including the American Medical Association and National Association of Community Health Centers), boards (including the American Board of Medical Specialties and American Board of Internal Medicine), academic centers (including Harvard, Hopkins, UCSF, Berkeley, and MIT), and financial supporters (including the MacArthur Foundation, Moore Foundation, Commonwealth Fund, Union Square Ventures, Andreessen Horowitz, and Y Combinator). Human Dx has also been honored by the MacArthur Foundation in its 100&Change competition as one of eight organizations globally with a bold solution to a critical social problem.

      Using the Human Dx system, medical professionals and trainees can collaborate on any case, question, or other medical topic. As they do, the system encodes their thought processes and decisions into structured clinical data to map the steps to help any patient. Today, thousands of medical professionals and trainees from over 80 countries and 500 medical institutions are involved in building the Project, which is already impacting both medical training and clinical decision-making.

    2. Why was the Project started?

      To nearly every person on Earth, the wellbeing of oneself and one’s loved ones is the most important concern. However, perhaps the most essential question of human wellbeing is still very difficult to answer: when someone isn't well, what should be done?

      Patients, doctors, insurers, foundations, governments, and many other health stakeholders struggle with this question. The information we seek is siloed in medical research, academic handbooks, disparate closed systems, and the minds of individual practitioners. However, relevant answers are not readily available in a single, open system that is universally accessible.

      Diagnosis is a crucial early step in assessing, treating, managing, and ultimately curing disease. By improving humankind's fundamental understanding of clinical decision-making, the Project could elevate wellbeing for current and future generations.

    3. What is the Project's Mission?

      The Mission of the Human Diagnosis Project is to empower anyone with the world’s collective medical insight. Applications will eventually range from helping an individual recognize when and where to seek professional medical attention to helping a world-class specialist physician consider options for a complex patient presenting with a rare illness.

      The Project intends to consider all relevant categories of data, as well as the relevant details and relationships among them, to encode the richness of effective medical diagnosis. Such data includes: symptoms; physical exams; medical, social, and family histories; medical sensor and device data; diagnostic and laboratory tests; medical imaging; genomics; epigenomics; proteomics; published medical research; and health outcomes data.

      To accomplish this, the Project is building a common frame of reference for all stakeholders in the health system. This is conceptually similar to an online map. Just as online maps have become the primary means of pathfinding from one location to another, the Project will give patients, family members, doctors, hospitals, and others a shared path to helping any person.

      Today, online maps make navigating the world faster and more efficient. They help us move seamlessly from origin to destination by synthesizing valuable insight from information sources such as speed limit, traffic, accident, weather, event, and topography data. Without geographic locations, all of the other information sources are not nearly as useful. As an example, using traffic data alone to determine how to get from one place to another is difficult without knowing the geographic locations of where the traffic is located.

    4. What is the Project's Vision of the future?

      Our Vision is a world in which each person benefits from and contributes to the collective insights of each other (including doctors, patients, and organizations). It would empower each stakeholder with the necessary information to make the best decisions for themselves, their loved ones, and their patients.

      Over time, humans (e.g., patients, nurses, doctors), machines (e.g., wearable devices, mobile phones, medical sensors/devices), and organizations (e.g., governments, multilaterals, health systems, insurers, employers) will work in concert to collect, analyze, and interpret real-time medical data. These parties will enable connected, distributed systems to effectively identify, treat, and prevent the development of disease.

      For example, an integrated system could recognize patterns in a patient’s physical activity, sleep patterns, and mobile phone use to provide constructive recommendations on how the patient could effectively sustain or improve his or her general health and fitness. The system would encourage healthy practices by providing personalized information on how the patient’s lifestyle influences his or her overall wellbeing and by suggesting courses of action to potentially improve the patient’s health status (e.g., going for a walk, drinking more water, getting more sleep, etc.).

      Furthermore, the patient’s desired doctors and other medical professionals could access this data and personalized recommendations at any time, from anywhere in the world. If the system detected a potentially serious health anomaly, the patient’s healthcare team could receive automated alerts and related details. With the permission of the patient, the identification, prioritization, and coordination of care could potentially begin prior to the manifestation of a critical medical issue. Thus, a patient who formerly would have received medical care during the latter stages of a given health condition’s development would receive accurate, preventative care well beforehand.

      The Human Diagnosis Project intends to facilitate any organization or individual that is committed to and interested in making this Vision possible. When such a system is ultimately built, it must be readily accessible and open to all.

    5. Why is now the right time to begin building Human Dx?

      The need is urgent. Currently, 3.5 billion people lack access to essential health services, fewer than two doctors are available per 1,000 patients globally, and 100 million people are pushed into poverty each year because of their medical costs (Sources: World Bank, World Health Organization). Moreover, the number of deaths attributed to poor quality healthcare is staggering: an estimated five million people in low and middle-income countries, compared to the estimated 3.6 million in those countries who die due to a lack of access to care (Source: The Lancet).

      The challenges and opportunities presented by these growing trends are immense, but not insurmountable. Novel approaches must be implemented to make healthcare more affordable, accessible, and accurate.

      Over the next several years, global mobile device penetration is likely to more than double in scale. Patients, doctors, and other medical professionals who lack sufficient access to appropriate care and cost-efficient resources represent a significant portion of this growth trend. For example, mobile device penetration has steadily grown among elderly and low-income individuals in the United States. Additionally, many other types of connected devices (e.g., wearables, sensors, appliances) are coming online in the next few decades, enabling us to collect useful information relevant to wellbeing that was never previously possible.

      With these advances we have the ability, and the responsibility, to tackle humankind’s most challenging problems.

    6. What are potential applications of the Project?

      As a synthesis of the global medical community’s collective insight, the Project will initially support medical professionals and trainees in medical training, diagnosis, and effective decision-making. It also has applications in numerous other fields, including: patient medical information, online search, web content sites, appointment booking, telemedicine visits, insurance fraud detection, clinical trial enrollment, research funding allocation, continuing physician education, medical sensors, and the Internet of Things.

      However, there are many applications of the Project that have not yet been conceptualized, and will only become apparent over time through the novel ideas of doctors, patients, engineers, policymakers, and organizations from around the world.

    7. How long will the Project take to complete?

      Unlike other civilization-scale scientific projects, the Human Diagnosis Project will not take decades for its potential applications to be of widespread use. Its efforts will be initially applicable to people in many geographies and socioeconomic classes, not just a subset of the most fortunate. The Project is already being pilot-tested to impact point-of-care clinical decision-making among underserved patients in the United States. Other initial applications of the Project’s data will hopefully be available in the next few years.

      The Project has no definite endpoint, and will continue to collect and interpret medical data as long as it has the support and resources to do so.

    8. Who organizes and leads the Project?

      Unlike other efforts at the intersection of medicine and machine learning, many of which state their intention to “replace the doctor,” the Human Diagnosis Project is created with, designed for, and led by the medical community. The combination of collective human intelligence with machine learning has the potential to be vastly more powerful than either on its own. While contributing to the Mission, medical professionals and trainees can enhance their clinical abilities and benefit from the community’s collective insights.

  2. Community

    1. How does the medical community contribute to the Project?

      Similar to how people around the world contribute encyclopedia articles to Wikipedia, or engineers contribute code to open source software projects like Linux, the global medical community submits clinical case contributions to Human Dx. The Project extends upon the ideas of open technology efforts by bringing together multiple other communities (e.g., patient, scientific, and technology) with the medical community to create and measure the quality and accuracy of clinical case data.

      This can be done from any connected device. As medical practitioners, residents, and students give and receive input on clinical cases within Human Dx, the open system automatically contextualizes their decisions and individual clinical insights.

    2. Why do members of the medical community contribute to the Project?

      The primary reason the medical community lends its efforts to the Project is a shared interest in our Mission, with its potential to elevate wellbeing for all.

      Within minutes, any member of the medical community can collaborate on clinical cases from around the world. Practical benefits to contributors include the ability to:

      1. Access the collective insights of colleagues and the medical community on clinical cases.
      2. Accelerate learning and clinical reasoning in many different fields of medicine, using rapid clinical cases and feedback.
      3. Store, modify, and share anonymized cases seen in the field, for personal reference and professional use.
      4. Satisfy education and ongoing medical education, licensing, and maintenance of certification requirements.
      5. Garner broader recognition within the medical community for excellence in clinical reasoning and topical knowledge.
    3. How do I use Human Dx?

      Human Dx is currently open to all medical professionals and trainees. Please see our tutorial page: and start contributing at

    4. How are clinical cases used to build the Project?

      The Project’s data structure is generated when the medical community’s cases intersect with the Project’s technologies. Cases are currently created via web and smartphone, though longer-term from any connected device. This enables the fast, scalable, and distributed creation of one of the most highly structured and high-fidelity medical data sets that currently exists.

      As cases are added to Human Dx, the system encodes structured data based on contributors' thought processes and decisions. To do so, Human Dx employs medical ontologies, information retrieval, semantic text extraction, natural language processing, machine learning, data mining, and other techniques. Though there are many ways for contributors to interact with the Project, the primary ones are creating and providing input on cases.

      When contributors create a case, they receive a prompt based on their preferences and capabilities, as well as the Project’s immediate requirements. They then begin creating around this prompt, which could include constraints like the patient’s diagnosis, background (e.g., age, gender, race), symptoms, medical history, etc. They can draw upon an actual case they have seen in the field, develop a plausible simulation of the patient, or something in-between. Contributors start by adding anonymized medical findings that describe the given case. These findings could be any medical information described in any form of content (e.g., a text description of a physical exam result, an image of an X-ray, an audio recording of lung sounds). As findings are added, their details can also be specified as appropriate. The created case is then sent to the Human Dx central repository for other contributors to provide input on.

      When contributors give input on a case, they first receive a partially revealed set of findings associated with that case. They then create a list of possible diagnoses (referred to in medicine as a “differential diagnosis” or “differential”) based on the information they currently have. Contributors update their differentials as additional findings are subsequently revealed. Because the contributor who created the case is not necessarily revealed to the contributors who are attempting to give input, the system learns whether the case appears to be reliable. Both correct and incorrect attempts help the model become more accurate, as long as they are identified as credible attempts to be correct.

    5. How does Human Dx measure the quality and accuracy of clinical cases?

      Human Dx measures quality and accuracy using the collective insights of the medical community and comparing this against the Project’s stored data and algorithms.

      Cases are not validated until a member of the Project community gives input on the contribution without knowing the identity of the contributor. This ensures that one or more objective, independent parties have arrived at similar conclusions with the data available. Moreover, any member of the Project community can dispute a contribution as invalid, which then triggers a review by more senior contributors in the system.

      Such a system allows for a distributed community of contributors to provide input into the Project, while still maintaining the highest levels of quality. Thus, longer-term, the Project will not only learn from traditional allopathic medicine perspectives but also from the perspective of other important health stakeholders including scientists; public health professionals; osteopathic, complementary, and alternative healers; as well as patients and families contending day-to-day with the health conditions considered.

      Additionally, by using its stored data and algorithms, Human Dx can automatically flag potentially false, specious, or incorrect contributions for manual review by a sufficiently senior contributor.

    6. Why is Human Dx only focused on diagnosis, and not triage, treatment, discharge, and other important parts of the medical problem solving process?

      The Project is focused on diagnosis as the primary step towards identifying, treating, curing, and ultimately preventing disease. However, while the Project name suggests diagnosis is the sole focus, we are simultaneously tackling the rest of the care continuum as well.

    7. What are existing computerized diagnostic solutions and how do they compare to the Project?

      Traditional diagnostic solutions can be broadly segmented into two categories of approaches: human-based and machine-based. Primarily human-based approaches (e.g., static content providers, clinical decision support systems, symptom checkers, and crowdsourcing) have not scaled well because of their rigid, inflexible, and archaic architecture. Primarily machine-based approaches (e.g., unstructured machine learning, electronic medical/health record intelligence, health analytics, patient simulators) have difficulty sifting through and creating valid recommendations from unstructured data.

      Furthermore, the shortcomings of existing diagnostic solutions are perpetuated not just by their methodologies, but the data itself. Currently, medical data is not collected in a highly structured format that can be effectively utilized by both humans and machines.

      Drawbacks include:

      • Existing platforms rely on unstructured, unverified, and unclear medical data, which prevents the effective interpretation of their information.
      • The medical data also disproportionately represents the most unhealthy patients, who generate the vast majority of medical data due to the time they spend in the healthcare system. This prevents accurate insights about healthier patients.
      • Many current solutions make recommendations using outdated decision trees and rule-based models. A scalable and adaptable solution must be more flexible in its architecture.
      • Medical practitioners rely on pattern recognition and their intrinsic insights to treat each patient. To sufficiently encode how doctors actually think, solutions must account for subtle nuances which are currently missed.
      • Current solutions lack the means to have many people update, contribute, or add content in a quick and scalable manner. As a result, existing solutions are not sufficiently broad or comprehensive. There are individual systems with some valuable diagnostic information. However, for a solution or platform to be widely adopted, it has to ultimately be able to address a very broad range of queries.
      • Current solutions do not model the processes of how a doctor determines a medical diagnosis when exposed to incomplete information. The Project captures this data and learns what incremental information will best help refine the differential.
      • Most current systems are closed platforms. Open ecosystems have the highest likelihood of successful implementation across many different areas of medicine.
    8. How does the Project differ from existing solutions?

      Human Dx focuses on the ideal intersection of human and machine intelligence. The system maximizes the capabilities of both medical practitioners and machines, allowing the two to work effectively in concert.

      The data captured by Human Dx addresses four fundamental problems in existing health data sources by:

      1. Capturing highly structured data — The Project uses a comprehensive medical ontology, visual system, and structured data protocol for encoding contributions.
      2. Measuring the quality and accuracy of the collected data — The Project uses the process of contributors solving contributions to ensure that the data contained in a given case is of sufficient quality. Because these contributors are not necessarily aware of the case creator’s identity until after they give input, their efforts provide an independent view on the quality of the information contained in the contribution.
      3. Generating data relevant to patients beyond just the unhealthiest few — Human Dx can prompt the contributor for potential cases to create based on what information is currently missing from the system, not by what information the system already has.
      4. More fully capturing the medical community’s decision making processes — Existing solutions lose the richness of how the medical community uses data to make decisions. By having a contributor constantly update differential diagnoses while revealing new information, the Project develops a richer perspective on the subtleties of the contributor’s decisions.
      5. Capturing structured data that is more nuanced and detailed than existing approaches — Symptoms, for example, may include specifiers like intensity, frequency, location, duration, onset chronology, aggravating/mitigating factors, character, quality, size, color, and smell.
    9. How does Human Dx complement the doctor-patient relationship?

      Human Dx is created by medical professionals and trainees (primarily doctors), who give and receive input from other doctors around the country and the world to help their patients. Thus, patients continue to experience a single point of contact — their doctor. Our goal is to help empower and strengthen that relationship with better knowledge, which can lead to better care, and thus an even closer doctor-patient relationship over time.

  3. Data

    1. How are the data and clinical insights shared with the Project made openly available to the public?

      When members of the global medical community contribute cases to Human Dx, the aggregated and anonymized clinical insights are made available via the website, and can be accessed by searching diagnoses and symptoms on the homepage. Additionally, these insights will later be available directly to stakeholders via API using a Creative Commons (or analogous) license. This gives the Project community the ability to share, use, and build upon work that other contributors have created. The specific license we will use as a model is available for review here: CC BY-SA-NC 4.0.

      Over time, as more of the Project’s data reaches a level of fidelity that is practically useful, we intend to make much of the Project's aggregated case insights, metrics, source code, services, and applications available for academic, research, social, and other noncommercial uses.

      Potential partners should contact to request further access.

    2. How does the Project protect patient and contributor privacy?

      The Project is highly sensitive to patient and contributor privacy. Our focus on this important concern manifests in multiple ways:

      1. How contributors create cases — Contributors create a wide spectrum of possible cases, which can be anywhere on the spectrum of fully real to fully simulated. Contributors can draw upon prior patients they have seen, their understanding of what typically makes up a simulated clinical case, or some combination of the two. Human Dx does not permit contributors to include personally identifiable information in any of these cases, and additionally, Human Dx does not know if an individual case is real or simulated.
      2. How the model processes created cases — After a case is created in Human Dx, the system also can generate novel cases by splitting, restructuring, and blending existing cases for other contributors to give input on. Thus, the case a contributor actually resolves may be even further in its abstraction from the contributor’s original case creation.
      3. How contributors provide input on cases — The cases that contributors give input on are anonymized, and in addition may actually be a part of, combination of, or a wholly machine-generated case. Thus, even if the original data was based on real clinical cases, the case itself could be a simulation generated by the Project.
      4. How we store data — All information is stored on secure servers. In the future, if any personally identifiable data is collected, it will be stored, processed, and transmitted in a way that is compliant with HIPAA and other applicable laws and regulations.
    3. How is Human Dx different from other open health initiatives?

      Existing open health initiatives primarily seek to collect and aggregate health data from multiple sources. Human Dx’s goal is to enable these and other platforms to generate actionable insight that will help them change the cost of, access to, and effectiveness of care globally.

    4. How will existing technologies work with Human Dx?

      Human Dx is architected to be both human-interpretable and machine-processable. This means that the system will be compatible with existing offline workflows and online systems.

    5. Can the data be used for commercial purposes?

      Much of the Project’s aggregated and anonymized case insights will ultimately become available to any individual or organization for academic, research, social, and other noncommercial uses. Paid commercial usage through software-as-a-service contracts, API calls, and licensing/royalty agreements, will help to support and resource the Project over the long-term (see question 5.2 for more information). Reimbursement and regulatory requirements will be dealt with by the party that uses Human Dx’s data for their own processes, as the Project will solely provide information (and not advice).

  4. Technology

    1. How did the Project develop its technical approach?

      Human Dx draws inspiration from many different sectors and technologies, including human-based computation, active machine learning, collective intelligence, and games with a purpose. reCAPTCHA and Foldit are related approaches.

    2. Is there evidence that the Human Dx technology works?

      Research evidence to date suggests that the collective intelligence of doctors working on cases together using Human Dx significantly outperforms the vast majority of individual doctors working on a case alone. This research, published in JAMA Internal Medicine and conducted in collaboration with Dr. David Bates, a professor at Harvard Medical School and one of the world’s leading patient safety and outcomes assessment researchers, compares the diagnostic accuracy of individual physicians from the Human Dx community to the leading computer-based symptom checkers.

      Research collaborations with groups at Harvard, Johns Hopkins, UCSF, MIT, Berkeley, and others of similar prominence will continue to validate the value of Human Dx to help those who need it most. Additionally, Human Dx is already being used as a training and teaching tool at many of the country’s top academic medical institutions.

    3. Is the code open source?

      The Project’s code base is not currently open source, yet we intend to make many parts of it open source in the future. If you are interested in contributing to several major open source projects we are thinking about, please email us at

    4. When and how can developers access Human Dx?

      Please email us at if you would like to be notified when Human Dx APIs become publicly available.

  5. Organization

    1. Who supports the development of Human Dx?

      The Project is developed by the global medical, technology, research, and patient communities as well as the Human Dx Team (including its full-time staff, partners, supporters, and board of directors).

    2. How is Human Dx organized?

      Human Dx (the Institution) is structured as a partnership between the social, public, and private sectors, and will ultimately interface with a wide variety of stakeholders. These include: nonprofits, foundations, governments, multilateral organizations, non-governmental organizations, individual benefactors, private companies, and the Project’s relevant communities (i.e., medical, technology, research, and patient).

      The Project is organized as a tandem structure: a nonprofit corporation (the NPC), which has been granted tax-exempt status under section 501(c)(3) of the Internal Revenue Code, and a Delaware public benefit corporation (the PBC). The NPC and the PBC interface with these stakeholders for complementary purposes. The NPC interacts with academic, research, social, public, other noncommercial and specified commercial stakeholders. In addition to supporting the Project's work with the aforementioned academic, research, social, and public stakeholders, the PBC also regulates all other commercial uses of the Project's intellectual property (similar to an academic research institution’s technology licensing arm).

      A few representative models of such tandem structures include: Mozilla Foundation and Mozilla Corporation; the J. Craig Venter Institute and Synthetic Genomics; Wordpress and Automattic. Other open software projects and the companies that support them also have interesting analogues to the Project. Examples include: Linux and Red Hat; MongoDB and MongoDB, Inc.; Git and GitHub.

    3. What is the Human Dx Alliance for the Underserved?

      The Human Dx Alliance for the Underserved is a partnership of many of the nation’s top medical societies, institutions, and boards dedicated specifically to expanding physician access for those who cannot afford it. The Human Dx Alliance for the Underserved includes:

      • The American Medical Association
      • The Association of American Medical Colleges
      • The National Association of Community Health Centers
      • The Association of Clinicians for the Underserved
      • The American Board of Internal Medicine
      • The American Board of Medical Specialties
    4. How is Human Dx supported and funded?

      Human Dx is currently supported by some of the world’s top thinkers in medicine, computer science, data, design business, and social impact. A sample of the Project’s stakeholders and supporters are below:


      • Dr. Don Berwick (former head of Centers for Medicare and Medicaid Services and founder of the Institute for Healthcare Improvement)
      • Dr. Mike Klag (Dean of the Johns Hopkins Bloomberg School of Public Health)
      • Dr. Gurpreet Dhaliwal (Professor of Medicine at UCSF Medical Center and one of the world’s leading diagnosticians)
      • Dr. Richard Baron (President & CEO of the American Board of Internal Medicine)
      • Dr. Darilyn Moyer (Executive Vice President and CEO of the American College of Physicians)
      • Mitch Kapor (first chair of the Mozilla Foundation and co-founder of the Electronic Frontier Foundation)


      • The MacArthur Foundation (one of the world’s largest private foundations)
      • The Gordon and Betty Moore Foundation (one of the world’s largest private foundations)
      • The Commonwealth Fund (one of the leading foundations in U.S. healthcare)
      • Rx Foundation (whose board includes Dr. Howard Hiatt, former Dean of Harvard School of Public Health and Dr. Atul Gawande, surgeon and author)
      • Union Square Ventures (first investor in MongoDB)
      • Andreessen Horowitz (first investor in GitHub)
      • Y Combinator (the world’s top technology accelerator)

      If you are interested in learning more about how you or your organization can support the Project, email the Team at

      Over time, the Project will be funded by products, services, applications, implementations, royalty, and licensing agreements related to commercial uses of the Project.

    5. How can I join the Team?

      The Project is uniting talented individuals to tackle one of humankind’s most challenging problems. The Team includes diverse backgrounds at the intersection of medicine, global health, computer science, information science, mathematics, software engineering, design, business, and public policy. The Team has included alumni from leading organizations (including the World Health Organization, the White House, NASA Jet Propulsion Laboratory, Lawrence Livermore Labs, Lincoln Laboratory, Facebook, Amazon, McKinsey & Company, Goldman Sachs, the Blackstone Group, and IDEO) and academic institutions (including Oxford, Cambridge, Harvard, MIT, Stanford, Berkeley, Yale, Penn, Dartmouth, and Cornell).

      Applicants must be passionate about the Project’s Purpose of elevating wellbeing for all and its Mission to empower anyone with the world’s collective medical insight.

      Please visit the Human Dx Team page to learn more about joining us.

    6. Where can I find the latest information regarding Human Dx?

      Future updates, articles, and news will be available on an upcoming Human Dx blog. Please sign up on our home page ( to receive occasional emails from us. You can also follow us on Twitter and Facebook.

    7. Where is Human Dx located?

      The Project is global in nature and currently has presences in New York City, San Francisco, and Washington, D.C. Over time, the Project intends to have regional presences throughout the world.

    8. What does the name Human Dx mean?

      The name Human Dx has multiple meanings. The first is literal: “Dx” is the medical shorthand notation for diagnosis, thus translating to Human Diagnosis.

      The second is less apparent, and is related to mathematics. A definite integral can be used to express the summated area formed by a function and an axis over an interval. The general notation for an integral is  ∫f(x)dx. In this case, the “function” being integrated, or integrand, is “human.” Thus, it metaphorically describes the summated potential of many humans working together to tackle a complex problem.

      The third meaning is a connection between mathematics and medicine. Dx in integration is literally translated as the “differential of x.” Differentials are the list of possible diagnoses that medical practitioners, residents, and students apply when thinking about what a given patient (x) may have.

    9. How can I contact Human Dx?

      Please feel free to reach us through our contact page with any general inquiries.