Medical Search Technology Relies on Google Alphabet and Big Data
The U.S. is learning more as to how artificial intelligence technologies such as machine learning play a major role in shaping daily life; apparently Google regards searches around medical symptoms as significant.
Engagement of medical search technology is rapidly expanding, as is new forms of structure data for healthcare services. One aspect of Artificial Intelligence is an effort to build machines and to advance technology using Google Alphabet that can learn from environments, from mishaps, and from real-life user experience to help individuals seeking a medical diagnosis. This takes advantage of Google’s intelligent medical search engine. A lot of research and testing goes into finding the right path and the right breakthrough. Google CEO Sundar Pichai said in a company’s annual Founders’ Letter to stockholders back in April, “This is another important step toward creating artificial intelligence that can help us in everything from accomplishing our daily tasks and travels to eventually tackling even bigger challenges like climate change and cancer diagnosis.”
He cited examples such as voice search, translation tools, and image recognition; he spoke about how Google scientists work to build products that improve over time, making them increasingly useful and helpful to the human race. Right along with food, water, and a roof over our heads, ranks good medical care.
U.S. Internet users can now search Google for help sorting out medical symptoms and not just actual conditions. Many medical answers win clicks in Google SERP featured snippets. While it may be surprising the number of individuals who ask Google to help to diagnose ailments, Google’s mobile site, as well as its iOS and Android apps, now have a feature that that proposes to track down information on medical symptoms. Instead of having to search for a medical condition, an individual can search for a certain symptom, such as “I have a pounding headache.”
Next, Google offers a summary of potential medical conditions, possible treatments a doctor would suggest, leads on how to obtain additional information online, and which type of doctor it suggests that the searcher turns to.
Historically, when a web searcher sought details on medical ailments, Google typically served up specialized sites such as WebMD, the Mayo Clinic and Medline Plus in search engine result pages (SERPs). With the move to Google Quick Answers in response to the user thirst for immediacy, you no longer need to sift through pages and pages of information drawn from big data to get answers to your search query. Finding and reading an abridged source information in one single place simplifies search. If voice search takes off in a momentous way, then, we may anticipate seeing a greater percentage of web searches attributed to longer search queries over time.
Astonishing Growth in Artificial Intelligence Market for the Medical End-user Industry
Big data and Artificial Intelligence is revolutionizing medical treatment.
The November 2016 market research report “Artificial Intelligence Market by Technology (Deep Learning, Robotics, Digital Personal Assistant, Querying Method, Natural Language Processing, Context-Aware Processing), Offering, End-User Industry, and Geography – Global Forecast to 2022”, reveals that the global artificial intelligence market is projected to be worth USD 16.06 Billion by 2022. That’s a growth rate “at a CAGR of 62.9% from 2016 to 2022, according to Markets and Markets.
This enormous investment is projected to pay off for patients who will benefit during medical treatment, advanced medical services/devices embracing this technology, and those who correctly implement medical ontology on their websites.
In an August 4, 2016 article titled Artificial Intelligence Will Redesign Healthcare, the Medical Futurist* points to the expansion of digital capacity as the amount of data produced and stored in the digital space escalates. “The amount of available digital data is growing by a mind-blowing speed, doubling every two years. In 2013, it encompassed 4.4 zettabytes, however by 2020 the digital universe – the data we create and copy annually – will reach 44 zettabytes, or 44 trillion gigabytes (!), it states.
Google Answers Search Queries for Medical Symptoms
Google’s API is ushering in a lot of new innovative applications that are advancing its role in the medical field. Available this week in the U.S. when users conduct a Google search query about medical symptoms, a list of related conditions and information on self-treatment options will be displayed.
The number of mobile search that uses voice recognition and relies on big data is growing, especially as Google AMP (Accelerated Mobile Pages) are rolled into the core of search. All an individual has to do is speak into their smartphone with a medical symptoms query to see results. Google says, ”we’ll show you a list of related conditions (“headache,” “migraine,” “tension headache,” “cluster headache,” “sinusitis,” and “common cold”). For individual symptoms like “headache,” we’ll also give you an overview description along with information on self-treatment options and what might warrant a doctor’s visit.”
The intent behind this is to help those who turn to Google Search to find and explore helpful information about health conditions related to the symptoms that are referenced. This should be a quick way to “get to the point where you can do more in-depth research on the web or talk to a health professional.” This technology has been in development for some time. GitHub states that, “the US English data is stored in /speech_recognition/pocketsphinx-data/en-US/”.
Research at Google states, “Machine Intelligence at Google raises deep scientific and engineering challenges, allowing us to contribute to the broader academic research community through technical talks and publications in major conferences and (medical) journals.”
Let’s cover some foundational definitions that will be helpful to readers of this article.
What is Google Alphabet?
According to Wikipedia:
“Alphabet Inc. (commonly known as Alphabet, and frequently informally referred to as Google) is an American multinational conglomerate created in 2015 as the parent company of Google and several other companies previously owned by Google. The reorganization of Google into Alphabet was completed on October 2, 2015. Alphabet’s portfolio encompasses several industries, including technology, life sciences, investment capital, and research. Some of its subsidiaries include Google, Calico, GV, Google Capital, X, and Google Fiber. Some of the subsidiaries of Alphabet have altered their names since leaving Google—Google Ventures becoming GV, Google Life Sciences becoming Verily.”
What is Verily Life Sciences?
According to Wikipedia:
“Verily Life Sciences (formerly Google Life Sciences is Alphabet Inc.’s research organization devoted to the study of life sciences. The organization was formerly a division of Google X, until 10 August 2015 when Sergey Brin announced that the organization would become an independent subsidiary of Alphabet Inc. This restructuring process was completed on October 2, 2015. On December 7, 2015, Google Life Sciences was renamed Verily.”
Advancing Medical Search
A whole raft of different approaches are coming about to advance medical search using artificial intelligence, one of the subfields is labeled pattern recognition. It draws from the artificial neural network and engages reinforcement learning, statistical inference from big data, and probabilistic machine learning. Much trial and testing under both supervised learning and unsupervised learning will lead to better techniques and improved systems.
“Any progress we make in building truly intelligent systems is going to depend on progress in technology generally. And until recently, we didn’t have computers that were fast enough or data sets that were big enough to do that. And so being able to take a particular problem and spread it out over lots and lots of machines is a very important approach because it makes our research faster,” states Google in Machine Learning: Making Sense of a Messy World.
Google repeated reinstates its commitment to invest in the mobile web; therefore, it is not surprising that Google Symptoms Search is foremost designed as a mobile experience. Already, mobile is the primary source of traffic for the vast majority of sites. Both past and currently, Google developers are working closely with publishers, partners, and other developers in the ecosystem to help make the mobile web a smoother, quicker user experience. Consider the Accelerated Mobile Pages (AMP) project, which Google launched this year as an open-source initiative in tandem with news publishers, to help them craft content for the mobile-first world.
The most widely recognized application of artificial intelligence in healthcare is data management. That alone involves collecting it, storing it, normalizing it, and tracing its ancestry. And it is revolutionizing the existing healthcare systems. The Google Deepmind Health project is used to source the data of medical records to improve health services. The key benefit to patients is that it is faster. Medical search is also relying more than ever on patient reviews.
Turning to the Web for Assistance with Medical Symptoms
The National Center for Complementary and Integrative Health says, “The number of Web sites offering health-related resources—including information about complementary health approaches (often called complementary and alternative medicine)—grows every day.” It also urges Internet users to be cautious when you evaluating the health information one can find on the Internet.
Additionally, the White House wrote on May 3, 2016, on the topic in an article titled Preparing for the Future of Artificial Intelligence. “Today’s AI is confined to narrow, specific tasks, and isn’t anything like the general, adaptable intelligence that humans exhibit. Despite this, AI’s influence on the world is growing. The rate of progress we have seen will have broad implications for fields ranging from healthcare to image- and voice-recognition. In healthcare, the President’s Precision Medicine Initiative and the Cancer Moonshot will rely on AI to find patterns in medical data and, ultimately, to help doctors diagnose diseases and suggest treatments to improve patient care and health outcomes.”**
How Google Symptom Search Relies on Alphabet and Big Data
Artificial intelligence (AI) in medicine is a relatively a newcomer in the research arena; it consolidates modern representational and computing techniques with the acumens of expert physicians to produce tools for advancing health care. The following statement illustrates how this form of intelligence may be needed to augment the best of practicing physicians.
According to healthinformatics.com, “Medicine is a field in which technology is much needed. Our increasing expectations of the highest quality health care and the rapid growth of ever more detailed medical knowledge leave the physician without adequate time to devote to each case and struggling to keep up with the newest developments in his field. Due to lack of time, most medical decisions must be based on rapid judgments of the case relying on the physician’s unaided memory. Only in rare situations can a literature search or other extended investigation be undertaken to assure the doctor (and the patient) that the latest knowledge is brought to bear on any particular case.”
It also notes the role Alphabet may have in diagnostic assistance. “When a patient’s case is complex, rare or the person making the diagnosis is simply inexperienced, an expert system can help come up with likely diagnoses based on patient data.”
AI looks at raw big data and then makes an effort to hypothesize relationships within the data; RankBrain has startled even its creators with the supremacy of its learning systems and how they are able to produce quite complex characterizations of those relationships. The outcome is the ability to better discover and match humanly understandable concepts. Google’s Symptom Searches offer quick answers for individuals who turn the web for reliable information on which to base a decision or approach to obtaining medical treatment.
Watch CNET’s video, “Google symptom search will help diagnose you” that was posted on June 21, 2016
How the Intelligent Medical Search Engine Works
According to Wikipedia, not everyone using the web for a medical search knows the right search keywords to use. To make it easier:
1st, it uses an interactive questionnaire-based query interface to guide users to provide the most important information about their situations. Users perform search by selecting symptoms and answering questions rather than by typing keyword queries.
2nd, it uses medical knowledge (e.g., diagnostic decision trees) to automatically form multiple queries from a user’ answers to the questions. These queries are used to perform search simultaneously.
3rd, it provides various kinds of help functions.
The FDA’s Supportive Involvement
Both Google and Apple are taking strides to help protect the quality of health apps available for use by the public. These are not game apps like Pokémon Go; a misleading or low-quality health app could potentially result in real harm to real people. Apple, for example, studiously monitors published apps by checking for content that “could provide inaccurate data or information, or that could be used for diagnosing or treating patients.”
Of perhaps greater significance, the US Food and Drug Administration (FDA) is actively accepting a lead role by setting guidelines for Mobile Medical Applications (MMAs), including a published list of those it currently regulates.
Essentially, if an app allows a mobile device to perform medical device functions, The FDA wants to make sure that an app used in this way is under its supervision to protect lives and govern the growing health app industry. One benefit is that users can feel protected knowing that there’s a safety net built in.
Predicting Medical Outcomes With Modern Technonoly
Dave Gershgorn published a Jan 27, 2018 article on Quartz titled Google is using 46 billion data points to predict the medical outcomes of hospital patients He discusses a research document published Jan. 24 summarized by 34 co-authors claims that Google’s medical search software surpasses other competitors at predicting medical outcomes such as the likelihood of a patient’s life passing in a hospital, being discharged and readmitted, and their final healthcare diagnosis.
To ground the research, Google acquired the de-identified data of 216,221 adults, with more than 46 billion data points cumulative among the individuals. The patient data spanned eleven combined years at the University of California San Francisco Medical Center (years 2012-2016) and from the University of Chicago Medicine (years 2009-2016). Google stated that it has enormously improved over traditional models that others currently rely on for predicting medical outcomes. The part that is raising eyebrows is Google’s ability to predict patient deaths 24-48 hours before current methods, which could allow time for doctors to administer life-saving procedures.
Current Well-Known Google Health and Healthcare Projects
Just in recent years, Google, through its various units and business partnerships, has an array of health and healthcare projects going on. A few more widely recognized include:
• Google Glass with work in progress for application inroads in hospital emergency services
• Miniscule, one-use sensors for easier diabetes supervision
• Wristband monitors that collect real-time clinical trial data between patient visits
• HIPAA compliant web cloud platform
• Genetic and molecular research called the Baseline Study that relies on big data
• Drug research for cancer and neurodegeneration
• Helping clinical staff detect cases of acute kidney injury at Britain’s National Health Services
• Developing means to prevent cardiovascular disease with the American Heart Association
• Work on wearable sensors to treat multiple sclerosis with Biogen
Future of AI in Hospitals and Medicine
Individual researchers and scientists who are close to advancements in medical search technology are part of the breathless sense that things are moving quickly. Progression in Google’s ability to create things that are increasingly better at improving Google Alphabet which can improve medical care and ultimate lives is a reality. Fund managers of Google Alphabet have indicated that “it is targeting medtech, biotech and digital health opportunities including telemedicine, genomics, population health, and chronic disease management.”
Intelligence is really not going to be something that we ever succeed in defining in a succinct and singular way. It’s really this whole constellation of different capabilities that all are beautifully orchestrated and working together. Predicting the long-term future is very difficult. Nobody can really do it. And the bad thing to do is take whatever is working best now and assume the future’s going to be like that forever.
According to Pharm Exec, “Verily is also involved in data-driven projects that fit closer in Alphabet’s traditional wheelhouse. Baseline will develop a comprehensive snapshot of what a healthy person looks like. It is also building what it calls “the Google of human systems biology”, with the broad ambition of gathering information from academic hospitals, physicians, universities and patients to make it easily accessible to researchers.”
Medical Searches help Patients Better Understand Their Current Treatment
Not all medical search queries are an effort to gain a health perspective or for self-care. An interesting discussion titled “Impact of Scientific Versus Emotional Wording of Patient Questions on Doctor-Patient Communication” was posted on Nov 25, 2015 by NIH.gov. It may shed insights on why some individuals turn to the internet to just better understand the medical words used by their treating physician.
Physicians are experts in their niche and may often face helping explain medical symptoms or care in layman’s terms. The conclusion in this article was, “Communication training for medical experts could aim to address this issue of recognizing patients’ communication styles and needs in certain situations in order to teach medical experts how to take those aspects adequately into account. In addition, communication training should also make medical experts aware of their individual therapeutic health concepts and the consequential implications in communication situations.”
Google Faced with Unique and New Medical Symptom Questions
It is easier to see why the California-based Google giant, who faces an average of 15 percent of queries a day that its systems have never seen before, would take this direction. For example, when dealing with ambiguous queries, like, “how to stop bleeding”, serving up immediate answers may be very important. The use of Google Alphabet is different from other technologies among search engines. Keeping on the cutting edge of search is central to Google, and making it’s systems savvier and better able to deal with ambiguous queries that indicate a searcher may need immediacy in deciphering how to respond to medical queries is being user-focused. This is one of the ways Google is responding to it jobs of answering queries each day for on time-starved users, who are now mostly searching using their mobile devices.
“It’s very carefully monitored. The other signals, they’re all based on discoveries and insights that people in information retrieval have had, but there’s no learning,” said Greg Corrado, a senior research scientist with the company. Also from the Oct 15, 2016, Google Turning It’s Lucrative Web Search Over to AI Machines article, we learn that Google episodically updates its search system by feeding it loads of new big data to help it improve reasoning with new concepts and new query forms.
Google AdWords Medical Ads Under FDA Eye to Replaces Ad URL With Web Site Type
While some may wonder why Google may seem to be playing doctor, the search giant is under the eye and regulation of the FDA. Questions have surfaced on Twitter as to why is Google replacing a display URL with the “type” of a website. The short answer is that the FDA requires Google to label these ads with the type of website. Glen Gabepoints to an article from last year that gives an example of an FDA violation: “When the ad is clicked on, the user is directed to the brand website. Even though the ad shows www.disease-state-info.com. The ‘vanity URL’ redirects to the brand website. Outside of pharma, using redirects in this fashion is against Google’s advertising policies.” All paid search marketing strategy teams need to be fully appraised and know how to follow medical-legal and regulatory policies such as ad formats and use verbiage that will meet the FDA’s guidelines. Read the article published by CMI: Updates To Google Advertising Policy for Medical Ad Formats.
Just like you would want a surgeon in charge for complex surgeries versus a general practitioner, work on your paid search URL parameters should only be carried out by an expert who fully understands it. URL parameters are values that are dynamically entered for each site URL. For example, owners of an e-commerce website with a global market may set a Country parameter that distinguishes web pages that should be served in different geo regions. Sections of your Google Search Console permit webmasters to instruct Google about your URLs. Setting the URL parameters incorrectly can destruct your SEO.
Additionally, the Institutional Review Boards of Duke and Stanford University reviews how it plans to utilize the information collected.
Future of AI in Hospitals and Medicine
Individual researchers and scientists who are close to advancements in medical search technology are part of the breathless sense that things are moving quickly. Progression in Google’s ability to create things that are increasingly better at improving Google Alphabet which can improve medical care and ultimate lives is a reality. Intelligence is really not going to be something that we ever succeed in defining in a succinct and singular way. It’s really this whole constellation of different capabilities that all are beautifully orchestrated and working together. Predicting the long-term future is very difficult. Nobody can really do it. And the bad thing to do is take whatever is working best now and assume the future’s going to be like that forever.
If you wonder where all the health data is being collected from, think if the rage in wearing in health-fitness bands, connected devices like weight scales, heart and blood pressure monitors, and the steady move to improved digital health records. Google owns an enormous role, whether with its Android Wear OS for smartwatches, or its project with Novartis making smart contact lenses that calculate glucose levels in patients with diabetes. Emerging forms of artificial intelligence to analyze information currently proliferate the news. Upon launch, Verily spoke of its leading role in machine learning—an AI process of crunching immense troves of data to discover patterns that may front-runner new insights. Instead of looking for relevant data to prove a theory, machine learning fosters a theory based on an overwhelming amount of data.
Wikipedia on AI for Hospitals and Medicine
Past and current use of artificial neural networks contribute to clinical decision support systems for assisting with medical diagnosis, with one example being the use of Concept Processing technology in EMR software.
Wikipedia suggests this use will grow in the following areas:
Other tasks in medicine that can potentially be performed by artificial intelligence include:
• Computer-aided interpretation of medical images. Such systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. A typical application is the detection of a tumor.
• Heart sound analysis.
• Watson project is another use of AI in this field, a Q/A program that suggest for doctors of cancer patients.
• Companion robots for the care of the elderly.
Internet Users Turn to Search Bots for Go-to Medical Advice
In the U.S. alone, search bots are quickly becoming many individuals’ go-to medical in-the-moment reference source, with close to 75% of adult internet users obtaining online information in the past year. Responding to this user demand, which after all is their consumer, Google recently augmented the Knowledge Graph results for medical search queries. Its endeavor is to streamline and develop the quality of health-related answers.
Desktop and mobile searches are now combined with over 400 medical conditions that are returning enriched knowledge graph results offering quite robust details. These cover potential symptoms and common treatment options, along with additional information. While this update is being welcomed by internet users seeking medical advice who don’t what to call a doctor at that moment, it could complicate tasks for digital marketers providing services to optimize website visibility and web traffic in both the organic and paid search arenas.
Medical search technology includes a broad area of semantic search that leverages Artificial Intelligence to include text and knowledge bases. It leans on “search with meaning” from which it can refer to various parts of the search process: like, understanding the search query (instead of just locating exact keyword matches in big data components available), comprehending the data, and then representing its knowledge in a meaningful way. Medical research focuses is on fundamental techniques, concrete systems, and benchmarks that take into consideration advanced issues such as; ranking, indexing, fundamental natural language processing techniques, ontology matching, and merging, and inference.
Prepare answers to the top questions asked in your medical niche and empower your Google Assistant to provide answers. Additionally, Google Now is a type of personal assitant that can help with medical questions.
Verily Life Sciences LLC hired over 45 new employees in the first quarter of this year as the secretive Google Alphabet Inc. spinout heads toward moving to South San Francisco by the years end. Newcomers to this fascinating and highly advancing field will find a lot of new articles surfacing on the web.
Here is what one physician has to say about it. Faisal Al-Alim, MD, a family medicine physician and a fellowship-trained sports medicine specialist stated: “I think it’s great Google has taken the time to ensure its presenting medical information that’s as accurate and evidence-based as possible. Let’s be honest. This is the electronic generation, and people are going online to research things about their health or pretty much anything else imaginable that affects their lives. So this Google symptom search enhancement is a win-win. When you as a patient arrive for your appointment with some basic and accurate information, it helps your doctor make a more accurate diagnosis.” Read his full article title How Google’s Enhanced Symptom Search Will Affect You.
Additionally check out The Best Medical Search Engine. It calls itself: “A Medicine and Health search engine for the general public and healthcare professionals. It uses the power of Google, whilst prioritizing high-quality medical sites. There is a great read on data analytics in healthcare promise and potential by Health Information Science and Systems.
“ Recently Google has expanded and moved towards research in medical technology. Just a few months ago, the tech giant partnered with Novartis to license a glucose measuring smart contact lens. The company had also recently bought portions of Calico, an anti-aging research company, and 23andme, a company that provides personal genetic tests. Now, Google aims to develop a wearable diagnostic device to detect cancer and heart attacks through the use of nanoparticles.” – medgadget.com
“A big part of the tech presence — the invasion of medicine — is long overdue. The state of technology in medicine is outdated and pathetic, so it’s very logical that Google, Intel, Microsoft, Apple, Qualcomm, IBM are getting into it. They’re all coming into this now. The future of biotech, medical and tech is going to coalesce. We’ve has seen that with medical sensors that do more than count steps, artificial intelligence, and virtual reality,” Topol said. “All these things are going to have a big impact in medicine. It’s a natural evolution.” – Dr. Eric Topol, Scripps Translational Science Institute Director
“At the moment we’re focused on building trust with clinicians and designing stuff hand-in-hand with doctors and nurses. Eventually, DeepMind wants to bring its machine-learning technology to health care. The new division of about 15 people will grow substantially.” – Mustafa Suleyman, who co-founded DeepMind
Modern Medical Search Technology Services
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Schema for Plastic Surgeons
Taking for example, a plastic surgeon who has three locations in the Twin Cities metro, each one basically providing the same treatments and surgical services, can build local web page’s that are each optimized with structured data by location. Following search technology best practices, rather than pointing every time to plasticwaterhouse.com, to reach location specific clientele, point them to plasticsurgeon.com/minneapolis, plasticsurgeon.com/edina, and plasticsurgeon.com/minnetonka, respectively.
From health-lifesci.schema.org: Use “Thing”, then “Property”, followed by “medicalSpecialty”.
Schema for Pharmaceuticals
Alphabet subsidiaries seem to be much health care focused or have significant health care plays that also tie into the pharmaceutical market. There are projects in the works to leverage wearable digital health devices and smart pills to act as nanodiagnostics or drug delivery devices. A specific example is the partnership between Google’s Verily company and Liftware, the developer of a spoon that controls tremors in Parkinson’s patients.
Schema is already used in the pharmaceutical industry. For example there is: Schema.org/DrugClass, Schema.org/TreatmentIndication, and Schema.org/MedicalSymptom.
Schema for Dentistry
Clinical offices in the niche of providing dentistry have a set of data entities that include their relationship and constraints associated with base activities of carrying out clinical processes. These may include diagnostics observations, measurements, etiology, intervention and prognosis, as well as an outcome assessment. A Dentist’s office is a more specific LocalBusiness, which has Organization and Place as parents).
A third normal form database Schema for Dentistry is available. From schema.org: Use Thing > Organization > LocalBusiness > ProfessionalService > Dentist
More specific Medical Business Types Currently Available on Schema.org
Additional Articles on Medical Search Technology
• 5 Ways AI is Changing Healthcare published June 8, 2016 by World Health
• Google Biotech Spinoff Verily Tackles $60M Buildout, published May 3, 2016, in San Francisco Business Times
• Google Streamlines Health Queries with Medical Knowledge Graph Enhancements published April 9, 2016, by iProspect
• Using artificial intelligence to revolutionize diabetes treatment, published April 8, 2016, by Devex
• Google has access to medical data of 1.6M UK patients, published April 30, 2016, by CNET
• Artificial Intelligence Eases Burden of Blindness in Diabetes published March 2, 2016, by the California Health Care Association
• 5 ways Artificial Intelligence is Changing the Face of Healthcare published March 10, 2016, by Health Care Drive
• Google’s DeepMind Forms Health Unit to Build Medical Software, published February 24, 2016, by Bloomberg
• Google Life Sciences Rebrands As Verily, Uses Big Data To Figure Out Why We Get Sick, published December 17, 2015, on Fast Company
• Google X’s “Baseline Study” Applies Big Data Techniques to Healthcare published on July 25, 2014, by ARS Technica
Within the paid search landscape for those in the medical niche, rising competition among top-funnel searches may drive AdWords account managers to increase visibility on lower-funnel searches, targeting people who are seeking treatment options rather than broader medical condition-related information. We are interested to watch and learn if and how Google further monetizes the Knowledge Graph; it now offers three tabs where potential Product Listing Ads (PLAs) could be placed. and perhaps even the opportunity for websites to sponsor curated content within the Knowledge Graph itself.
Our clients in the medical field enjoy semantically optimizing sites using schema.org and other SEO/SEM cutting edge best practices. The combination of big data that lets us explore new site visitor behaviors throughout the day (such as pages visited or location) and offering the solutions viewers want leads to increased engagement and conversions. Look for updates from Hill Web Marketing as we continue to follow how the enhanced Google Knowledge Graph evolves and offers new opportunities for businesses to use structured data along with current methods to win rich snippets within search results. Schema implementation is helpful to ensure that your medical facility has a better chance to show up in local map packs, as people need directions.
Whether your business comes under the medical classification or not, benefit by Request a Schema Markup Audit.