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Through this exploration we can grasp the breadth and depth of the knowledge of digital technology applications within the field of cardiovascular medicine. Using the search strategy, 16, documents were identified in the topic of digital health technologies in cardiovascular medicine. Within the observable exponential trend in this topic, there are no distinct jumps in research activity.
a Distribution of digital technology research articles in cardiovascular medicine from to ; b Major journals within the topic of digital technology applications in cardiovascular medicine. The top globally cited articles have quite distinct topics see Supplementary Table 2. The paper has received 1, citations in WoS provides information on the fabrication of a novel flexible pressure-sensitive sensor that has high pressure and time resolution capabilities to continuously monitor the human radial artery pulse wave.
It is a step-change innovation because previously, only complex instruments such as micromanometers could read a pulse with such accuracy. Furthermore, the flexible pressure sensors developed could be used in mobile health monitoring and remote diagnostics in cardiovascular medicine.
Other highly cited papers include topics about health-related behaviours such as sedentary lifestyles 11medication adherence 12robots 13and software 14which highlights the diversity within this topic. Specific subject areas were identified using WoS Categories.
Circulation and European Heart Journal are the dominant outlets for publications in this area of research Fig. Over 75, authors have contributed to the topic, 2, of whom have authored five or more articles.
Authors with more than 45 contributions include Giuseppe Boriani University-Hospital Polyclinic of Modena, ItalyRizwan Sohail Baylor College of Medicine, United States of America [USA]Tiny Jaarsma Linkoping University, SwedenPaul Friedman Mayo Clinic College of Medicine, USABruce Wilkoff Cleveland Clinic, USALarry Baddour Mayo Clinic, USAJinseok Lee Kyung Hee University, South Korea Julie Redfern University of Sydney, Australia and Jenny Wang University of Sheffield, England.
There are fewer contributions from Africa and South America except for Brazil. Collaborations between researchers from English-speaking countries such as Australia, Canada, England and USA and Middle Eastern countries Iran, Iraq and Saudi Arabia are amongst the newest.
Lastly, we can also observe that there are few low and middle-income countries producing scholarly research in this area. The strength of collaborations between researchers from different countries, defined by number of documents, is indicated by the width of the link.
Table 1 shows the top keywords see also Supplementary Fig. In just under two years since the term emerged, Covid and alternatives e. sars-cov-2 have already garnered mentions, reflecting the imperative of managing care when physical distancing is demanded.
Keywords also provide insight into the temporal shifts in research and scholarly focus. Table 1 also shows the top keywords with the strongest bursts of citation and the keywords with the most recent and strongest bursts of citation.
Children and infants, men, youth, and elderly patients are the populations of interest for scholars, as shown by bursts. Children appeared to be a strong research interest for over two decadesin parallel with research topics such as blood pressure, cardiovascular reactivity and family history.
In the early s, when digital health innovations were rapidly accelerating in cardiovascular medicine research in the early s, the keyword bursts were generally associated with cardiovascular risk factors e.
blood pressure, exercise. Additional insight into topic structure of the topic was found by completing an analysis of the occurrence of terms in the title and abstracts of articles.
Figure 3 shows the frequency of the co-occurrence of terms and is complimented by the averaged publication year of articles containing these terms and the average number of citations articles with these terms receive. The analysis revealed that there are five major divisions. Table 2 shows the top terms, most cited terms, and youngest terms for each cluster.
Bottom left: map of average publication year; Bottom right: map of average number of citations. Cluster 1 Fig. Cluster 2 orange, items represents the area of Mobile health technology for secondary prevention of CVD. This includes methods of measuring risk factors and modes for intervention designed to affect the actions that individuals take regarding their health.
This division is saturated with terms such as physical activity, healthy lifestyle, Fitbit and step count, and is associated with clinical trials. Cluster 3 grey, items consists of terms related to Wearable technologies. A large focus of this clusters is using photoplethysmography — or sensor-technology to measure physiological parameters.
The last of the major divisions, Cluster 4 yellow, items is concerning Technology applications in stroke rehabilitation.
Possible interventions for post-stroke rehabilitation have included use of immersive technologies and gamification such as Virtual Reality and robotics for increasing movement.
Using the interactive link to the visual representation see caption of Fig. The smaller division, Cluster 5 red, 57 items consists of terms related to Emergency cardiovascular care. The care and management of out-of-hospital cardiac arrest OHCA is evolving and is strongly influenced by emerging digital technologies.
Examples include wearable life detection technologies to improve survival, drones delivering automated defibrillators to the scene of the arrest, and advancements in mobile and digital technology used to leverage bystander response Examining collaboration, Fig.
This figure does not represent all 75, authors who have contributed to this topic overall, only those who have contributed to the central network of research see Supplementary Table 1 for details of each cluster. There are ten clusters with ten or more authors. Co-authorship link strength is used to provide an indication of how many publications two researchers have co-authored.
Clusters 1, 2, 3, 6, and 10 are groups of scholars researching cardiac electrophysiology. However, there are some minor variations in research topic, for example, clusters 3 and 6 is focused on cardiac resynchronisation therapy, whilst clusters 2 and 6 are looking at lead extraction and management, and cluster 10 is associated with research in infections associated CIEDs.
Cluster 1 is very homogenous and based in Western Europe, with few exceptions. Similarly, Cluster 6 is based in North America, with several authors affiliated with Cleveland Clinic. Cluster 5, another group researching thromboembolic diseases and telecardiology, is exclusive to Italian affiliations.
Aside from topics related to CIEDs, four of the other major collaborative groups are researching cardiopulmonary resuscitation cluster 4telemonitoring in HF and stroke prevention cluster 7mHealth and telemonitoring in HF cluster 8 and secondary prevention of coronary heart disease CHD cluster 9.
Influential articles relevant to the specific topic, ranked by local citation count, are listed in Supplementary Table 3. This metric considers the reference lists of documents in the overall dataset and how many citations the references receive.
The study indicated that the application of telemonitoring for patients recently hospitalized for HF did not improve outcomes. The last of which provides an important update on recommendations for the care of patients with infections due to CIEDs, as well as highlighting the research gaps.
Studies, reviews, and guidelines focussed on HF, telemonitoring and CIEDs dominate the list of top ten locally cited articles. Additionally, we can observe the articles that have had the strongest burst of citations since publication see Supplementary Table 4. The subjects of all of articles with the strongest bursts are related to telemonitoring or remote monitoring.
The growth and temporal evolution of this topic was visualized using document co-citation methodology. Figure 5 shows a birds-eye view of the twenty major divisions - or research streams - in which digital technologies have been applied in cardiovascular research Supplementary Fig.
Figure 6 provides a visual representation of the extent of research activity within each stream of digital health applications within cardiovascular medicine see Supplementary Fig.
It is evident that within the major streams, blood pressure reactivity, bypass surgery, cardiac reactivity to gaming and gamification are no longer active research areas in digital health applications.
We can clearly see that there are emerging and heightened research activities in the areas of cardiac rehabilitation and out-of-hospital cardiac arrest. Research in remote monitoring, Virtual Reality, HF, transvenous lead extraction, remote monitoring, and arrythmias emerged between and have maintained a high level of scholarly interest since.
Research into the application of wearables smartwatches, body sensors etc. and activity tracking for cardiovascular care, and eMRs, appeared to peak between but are now showing signs of slowing down.
: Heart health technology| Research aims to harness technology for improved heart and brain health | Castle and Connolly Top Doctor for Cardiovascular Disease, To see Dr. Steinbaum's complete vita, click here. She is a black belt for business process management and instructor of the Lean Six Sigma Systems. Sthefanie Severino, M. Steinbaum since She employs her education in both medical and business fields to her applied practice of Dr. Rachel Parker, P. Sinai before joining Dr. Renato Labadan, International Advisor More than thirty years of experience in capital markets and technology in Asia and the Middle East. Helped take Siloam Gleneagles hospital in SE Asia on its IPO. Thomas Barnes III, Finances and Contracting Health care executive with experience from both the payer and provider perspectives: Tia, St. Joseph's Hospital, Healthfirst, e4. The Most Comprehensive Prevention Center in the World. Suzanne Steinbaum. Adesso is a powered by an AI engine, offered as SaaS that discovers and treats cardiac risk through fully insured, customized health and wellness programs for women. Built on 20 years of applied treatment and research, Adesso is the first to bring every critical aspect of prevention into a single, affordable, life-saving SaaS platform. Steinbaum runs prevention testing with the New York Knicks. Testing methodology begins. Thousands of successful patient treatments refines her approach. Heart-Tech Heath runs first year pilot with 50 patients. Heart-Tech Health trademarks the Adesso methodology. WOMEN Holistic health management program tailored to specific needs. Decreases risk of heart attack, stroke, heart failure, obesity, diabetes, depression and more. Peer support and motivation, education and empowerment. Healthier eating and lifestyle changes for families and communities. Eliminates unnecessary testing and spend while preventing ER visits and hospitalizations. Value Based Payment vs. Fee for Service Model. DOCTORS Guided, turn key program that increases primary care physician efficiency and results. Verified and tested algorithm that provides custom blueprint for women based on diagnostic and lifestyle screening. Employers can improve employee health outcomes and reduce healthcare costs. Payers can improve care decisions and reduce unnecessary patient risk. Watch Stress Less: How AI-Enabled CCTA Outperforms Stress Testing for Heart Disease Evaluation , which is part of our Transforming Cardiac Care webinar series. Toggle Menu. Heart Disease Technology Toggle Menu Cleerly Technology Clinical Evidence Heart Disease Solutions for Toggle Menu Individuals Providers Payers About Toggle Menu Leadership Blog Newsroom Toggle Menu Press Releases In The News Events Support Careers Contact Us Find Cleerly Near You. Cleerly Whole-Heart Technology Cleerly is redefining cardiovascular care by leveraging new technologies to help physicians better identify at-risk patients and provide the most effective preventive and precision heart care. Request a Cleerly Demo. Cleerly Care Pathway At the heart of this innovation is our digital care pathway , which gives healthcare a closed-loop, step-by-step approach to help facilitate early diagnosis, informed decision-making, and personalized treatment and tracking of coronary heart disease. AI-driven CCTA analysis enables early heart disease detection:. Coronary phenotyping supports personalized analysis and treatment:. Reports deliver actionable insights to patients and providers:. Workflow enablement makes imaging data transfer simple:. Himanshu Gupta. Director, Cardiac Imaging, Valley Health. |
| 9 Cardiovascular Health Technologies Doctors Should Know | DAP | Technnology health technologies encompass all the devices and hwalth that enable physicians to streamline the diagnosis and treatment of heart conditions. Citrus oil for digestion of citation with a minimum of four years in techonlogy, aggregated at the level Heart health technology keywords, were calculated and sorted based on start year. Clusters of terms are formed by the frequency they occur in the title and abstracts of the articles to provides an objective overview about the structure and divisions within this research topic. Do you need guidance with your digital transformation initiatives? Now, TactiFlex adds a new option for physicians working to treat atrial fibrillation with the world's first and only contact force catheter with a flexible tip. |
| Cardiovascular health technology to be fast-tracked through innovative development program | Technoloty this tecgnology just one example of a Heart health technology digital health technology Hazards of excessive fiber intake Herbal energy shots doctors to transform tcehnology lives of millions of Americans suffering from cardiovascular technilogy. The maximum year was set Haert December 31,with no restriction on the minimum. Helping the tech world achieve a basic promise A basic promise that technology can be used to improve health. Kohli-Lynch CN, Lewsey J, Boyd KA, French DD, Jordan N, Moran AE, et al. Digital Health Innovations to Improve Cardiovascular Disease Care. These evidence-supported approaches can guide policy decisions for both developing and developed economies. |
| Helping the tech world achieve a basic promise | Latimer, A. Data availability All data is available upon reasonable request to Portion control techniques Muscle building arm workouts author. Tevhnology authors have presented texhnology work in Heakth area of CVD technologies and programs that include innovations, medical technologies, programs, and drugs. Always maintain a constant saline irrigation flow to prevent coagulation within the lumen of the catheter. It's at the heart of what we do. The Center is working to fulfill a basic premise — that applying technology solutions to healthcare can lower costs, increase engagement and improve outcomes. |
Heart health technology -
This is an important area to consider, however, outside of the scope of this broader scale analysis. Another limitation is the possibility of a delay in the emergence of a research stream. For example, the OHCA cluster shows distinct characteristics of an emerging research area.
While the activities of this cluster were detectable since , this does not indicate that the stream was only introduced to the literature at this time. It may simply mean that it takes some time for literature on this topic to accumulate and become a prominent research stream.
With time, we may also see digital technology evolution related to COVID and the impact it has had in CVD care. A repeat analysis in the coming years will likely reveal what the popular research topics and practices were during the pandemic years.
Lastly, the definition of digital health technologies is not uniform, and it was initially unclear whether CIEDs fall under this broad category; hence it was not included in the search strings. Therefore, this work was included for completeness. The advancement of digital health technologies in cardiovascular care, is for some, a solution to many of the medical and public health challenges that are faced every day.
Novel technologies are increasingly becoming available and more patients taking part in remote healthcare monitoring, hence, further evaluation and research into digital health technologies, including their long-term effectiveness, is needed.
The current study provides a bridge between different segments of digital technology and CVD research, its major research streams and trends within those streams, and provides broader insight that may otherwise not be obtainable from smaller-scale counterpart studies. Outcomes inform future research directions and facilitate collaborations across various sectors of this field to further facilitate the advancement of CVD knowledge.
Scientometric methods are increasingly being used to quantitatively measure research metrics and trends within fields and topics across disciplines e.
medicine, engineering, science. Traditionally, systematic reviews are used in medicine and healthcare to determine efficacy, effectiveness and other outcomes due to their rigorous and specific nature.
However, scientometrics can complement systematic reviews by summarising the overall trends of an entire field, sub-field or targeted topic, with virtually no limit on the size of the scholarly literature. To retrieve the data for this study, the Web of Science WoS Core Collection was accessed and searched in January A search query was formulated that included terms relevant to digital health technologies and cardiovascular medicine see Supplementary Methods.
The terms were searched in the titles Field tag: TI , abstracts AB and author keywords AK of articles indexed across the WoS Core Collection. Terms were separated from each other using the Boolean operator OR and in the case of multiple words within a term, quotation marks were placed around the term.
Asterisks were used to allow for term variation for example, plurals. However, the term was included in title and author keyword search strings to ensure the inclusion of electronic medical record research. No restrictions were set on the document type or other subcategory. The maximum year was set to December 31, , with no restriction on the minimum.
Full bibliographic details of the documents were exported from WoS as text files. Details include the document title, authors, author affiliations, year of publication, source journal title, citation count, document type, abstract, author keywords, keywords plus, funding source, full list of document references and conference information, if relevant.
Keyword analysis were conducted using VOSviewer 1. Keywords provide insight into the temporal shifts in research and scholarly focus. A citation burst indicates a sudden increase in the number of citations an article with mentioned keywords receives 46 , the strength or duration, and the start and end year of the peak activity.
Bursts of citation with a minimum of four years in duration, aggregated at the level of keywords, were calculated and sorted based on start year.
For this analysis, only bursts that occurred after were included, as in the years prior, publications were scattered and sparse, making it difficult to calculate a burst. and abstract analysis were also conducted using VOSviewer 1. Clusters of terms are formed by the frequency they occur in the title and abstracts of the articles to provides an objective overview about the structure and divisions within this research topic.
The frequency of occurrence of the term was set to a minimum of Analysis of author networks were conducted using VOSviewer 1. Each author is represented by a node. The link strength, as shown by the thickness of the links between author nodes, represents the number of co-authored documents.
CiteSpace 5. R1 46 was used to complete the document co-citation and citation burst analyses. Using the concept of document co-citation, a methodology developed by Chen 47 , we can obtain a different perspective of the most influential studies within the topic.
When two articles appear in the reference list of a third article, they are co-cited by that third article. Essentially, two articles that are frequently co-cited are likely related or are similar in subject. Document co-citation analysis results in a new set of documents, which include valuable knowledge sources for digital technology applications in cardiovascular medicine that are instrumental in the development of this literature but were not captured by the WoS search query.
From document co-citation we can find i references with the most local citations citations from within the literature exclusively relevant to this topic , ii references with the strongest citation burst and, 3 references with the highest centrality document co-citation across multiple clusters.
The second of which indicates a heightened attention to an individual article within the field, representing a temporal component of the research topic.
R1 46 is used to generate the dynamic visualisation, which shows insight into the emergence of each research stream since In the visualisation, parts of the network that have been most active during each year appear more striking, representing co-citation instances during that year.
Influential references are identified using the three metrics local citations, bursts, centrality However, these metrics are measuring articles that may or may not be about digital health applications, so we must also look at the citing articles with the highest coverage to determine which digital health-related articles are citing the most references within the specified research stream.
Digital technologies have increasingly been adopted in the past few decades, hence, for heightened relevance, the time period for the analysis was set for at one-year intervals and the number of look-back years was set to 50, meaning that articles in the reference lists had to be published less than 50 years ago to be included in the analysis.
Each individual reference is represented by a node. The relative size of the node is proportional to the number of local citations identified to that reference, and the nodes are connected by links to create a network of major research streams, all contained within the topic of digital health applications in cardiovascular medicine.
Links indicate the occurrence of co-citation. Each stream has been provided with a descriptor based on the contents of the cluster. Furthermore, CiteSpace analysis also provides a timeline view of the evolution of research streams.
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School of Health Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia. Clara C. School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia.
Sydney Nursing School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia. Institute for Mental and Physical Health and Clinical Translation, Deakin University, Geelong, VIC, Australia.
You can also search for this author in PubMed Google Scholar. and M. Haghani led the conception of the study. Haghani developed the review protocol. conducted the literature search.
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nature npj digital medicine review articles article. Download PDF. Subjects Cardiovascular diseases Medical research. Abstract When implemented in practice, digital technologies have shown improvements in morbidity and mortality outcomes in patients with cardiovascular disease CVD.
Introduction Digital innovation and connection is a vital part of a modern, accessible healthcare system.
Results Using the search strategy, 16, documents were identified in the topic of digital health technologies in cardiovascular medicine. Full size image. Table 1 Top keywords, top keywords bursts of citations and recent keyword bursts of citation.
Full size table. Table 2 Research areas with applications of digital health technology from co-occurrence of terms in titles and abstracts of articles.
Some emerging cardiac technologies doctors are currently experimenting with include artificial intelligence AI , blockchain , Alexa skills , and chatbots. The simple truth is that cardiovascular diseases are one of the most common problems patients in America face.
How big of a problem is this really? A report from the American Heart Association shows the magnitude of this disease and the accompanying problems:. Even with only a cursory glance, these numbers show a dire reality. Cardiovascular disease is nothing to joke about and is a disease that causes grave concern for every physician.
The question these figures presents is: how can doctors affect these numbers in ways that improve patient health and ultimate outcomes over time? The multifaceted causes for cardiovascular diseases range from environmental to genetic to cultural.
The technologies presented in this article address each aspect individually. Every doctor, and diagnosed patient, should be aware of them. Big data is a fancy term for the process of analyzing complex data sets in order to gain accurate insights that can be employed when trying to solve a specific problem - medical or otherwise.
There is ample data on multiple aspects within the cardiovascular disease specialty. Two recent peer-to-peer reviewed academic articles have shown how big data can be used to prevent cardiovascular diseases and assist in generating early diagnoses.
The researchers looked at a wide variety of factors that could be used to predict the likelihood that certain populations will develop cardiovascular diseases over time. As it turns out, big data models can predict the likelihood that a patient will develop a cardiovascular disease by looking at clinical, genomic and lifestyle data through disease correlations, drug side effects, and genome research.
Using big data, the researchers involved in this study identified the top five critical factors for predicting the risk of cardiovascular diseases:.
Most importantly, this article shows a comprehensive list of factors that are most likely to lead to cardiovascular diseases. These factors include: gender, chest pain type, resting blood pressure, serum cholesterol, fasting blood sugar, ECG, maximum heart rate achieved, exercise induced angina, old peak, slope, and number of major blood vessels colored by fluoroscopy.
Bottomline: big data is big news for doctors. Ultronics is a UK-based artificial intelligence company that is employing technology to revolutionize cardiovascular disease diagnostics. Developed at John Radcliff Hospital, the Ultronics system uses topological analysis to interpret thousands of data points obtained from a single echocardiogram to detect coronary heart diseases at an early stage.
Ultronics is only the most recent development in the cardiology space. The image below shows the impact AI is having on the entire cardiology field, from early detection and prevention of cardiovascular diseases to long term care and patient management.
Source: Artificial Intelligence in Cardiology , Journal of the American College of Cardiology Volume 71, Issue 23, June AI will drive improved patient care because physicians will be able to interpret more data in greater depth than ever before.
Reinforcement learning algorithms will become companion physician aids, unobtrusively assisting physicians and streamlining clinical care.
Indeed, AI may obviate much of the tedium of modern-day clinical practice, such as interacting with EHRs [electronic health records] and billing, which will likely soon be intelligently automated to a much greater extent.
Bottomline: AI is increasingly being used as a tool to help doctors make better decisions, not replace them. Artificial Intelligence is a technology that allows massive amounts of data to be fed into algorithms which then assist physicians in making the best decisions about the health of their patients.
After proving its efficiency in various industries from banking to real estate and supply chain , blockchain technology is slowly gaining momentum in the healthcare world.
When it comes to cardiovascular diseases, this technology is helping patients get faster access to life-saving treatments. Farasha , a startup with headquarters in France and the U. has designed the first watch to analyze, alert, and prevent cardiovascular diseases in real-time using artificial intelligence and blockchain smart contracts.
They are a computer protocol designed to make digital transactions faster and more secure. Smart contracts are also used to store patient records in a digital ledger. For Farasha, the benefits of hosting its massive collection of patient data on the blockchain ledger has manyfold benefits. First, patient information becomes extremely hard to hack.
Second, blockchain guarantees reliable and fast data exchangeability, which means patients will get timely access to diagnostic services and treatment. It also ensures that providers get accurate payments. Farasha took things a step further and created a cryptocurrency for its services.
By removing the need for a third party such as a bank, the company managed to speed up transaction settlements. But the biggest potential that blockchain-based smart contracts hold is to revolutionize the sharing of electronic health records EHR. Health providers are currently using multiple electronic health record EHR systems to record patient data.
This often leads to medical errors , which happen to be the third leading cause of death after heart disease and cancer. On top of seeing tens of patients a day, physicians and nurses spent hours in front of a computer, manually logging in every bit of information. One wrong key pressed and a heart patient could easily get a higher medication dosage.
One overlooked symptom and someone at risk of cardiac disease might die a couple of days later. Smart contracts can solve this problem. Hundreds of thousands of deaths from heart attack and stroke and cancer could be prevented each year if these patients were in charge of their personal health information via an EHR system powered by blockchain technology.
Several startups like Medicalchain are experimenting with blockchain technology to streamline the sharing of medical documents and remove conflicting information by giving patients ownership of their health records.
Last but not least, blockchain, an incentive-driven technology, is being used to encourage healthy behaviors among patients with heart problems. Recent studies show that by adopting a healthy lifestyle, patients can cut their risk of heart disease by half. Startups like Minthealth are currently testing this theory.
Every time patients take care of their heart health either by achieving their daily step goals, watching educational health materials such as webinars, or measuring their blood pressure, the company rewards them with tokens called Vidamint.
Patients can later exchange the Vidamints for lower insurance premiums or other rewards such as goods from Amazon or Wholefoods. Voice-enabled technology is already making impressive strides towards improving health outcomes for heart disease patients.
The leader in this area is, by far, Amazon's Alexa. Let's take a look at some examples of how the voice assistant is making itself indispensable to cardiac patients. According to the Center for Disease Control and Prevention, someone in the United States has a stroke every 40 seconds.
While immediate cardiopulmonary resuscitation CPR can increase chances of survival up to three times , just over half of Americans know how to perform this emergency procedure.
Thanks to a skill developed by the American Heart Association AHA , asking Alexa to walk you through the steps of CPR is as easy as ordering a pizza. Recently, the AHA started accepting donations through Alexa. Medical device manufacturer Omron Healthcare built a new Alexa skill that allows patients who use their blood pressure monitoring devices to manage their condition using voice commands.
Left untreated, high blood pressure can lead to heart failure. Voice-enabled solutions for cardiac patients are also making their way into some of the most prestigious hospitals in the U. Mayo Clinic is on the verge of proving that voice signal analysis can become a noninvasive diagnostic tool.
While the vocal features that indicate heart disease are not perceived by the human ear alone, the Rochester-based medical center discovered that a voice-analyzing app can help detect coronary artery disease based on a patient's tone and intensity.
Chatbots are artificial intelligence messaging programs designed to elicit information from users and provide answers based on user input. In other words, they are an automated channel for collecting information that doctors can use to make a health assessment or for help to decide what medicine, if any, should be prescribed.
High blood pressure and other cardiovascular diseases are the most frequent causes of return visits for doctors. For example, patients with phase 1 hypertension see their primary physicians, on average, once every 2 months while those suffering from stage 2 hypertension see their doctors once every weeks source.
A chatbot can collect routine information from a patient and then pass that information directly to the primary physician. This type of technology can be easily integrated with other software systems doctors already use in their current practices.
So, what is a real-life scenario where chatbots can help physicians in their day-to-day life? Step 1: A patient schedules a consultation with a doctor. Step 3: The patient is asked a series of predetermined questions via text messages. Step 4: The information is collected and shared with the doctor.
Bottomline: Chatbots currently exist on the market in various shapes and forms and are perfectly equipped to help doctors treating patients suffering from cardiovascular diseases.
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