Transforming Healthcare With AI

According to predictions, the worldwide market for artificial intelligence (AI) in healthcare would expand from an initial valuation of $15.1B in 2022 to more than $187.95B in 2030, a compound annual growth rate (CAGR) of 37 percent. The North American artificial intelligence healthcare industry was worth USD 6.8 billion in 2022.

By 2024, artificial intelligence is expected to make great strides in the medical field. Deep learning algorithms improve the accuracy of X-ray, MRI, and CT scan interpretation, which is useful in medical imaging and diagnostics. AI plays a crucial role in the drug discovery process by sifting through large datasets in search of promising compounds and automating development. Using a patient’s unique genetic and molecular profile, personalized medicine employs AI to create individualized treatment plans. Using natural language processing to glean insights from unstructured clinical data, predictive analytics helps with patient outcome prediction and at-risk population management.

The research examines six key areas where AI directly affects the patient and three sectors of the healthcare value chain that might gain from more scaling of AI. It also looks at specific instances of current AI solutions in healthcare.

With the help of AI, telemedicine and RPM may provide patients with up-to-the-minute health information. To guarantee ethical AI use, legislative frameworks, and ethical concerns have come to the fore. Instead of seeing AI as a replacement for human healthcare providers, the focus is on how AI systems may work in tandem with them. The picture highlights the revolutionary integration of AI into several aspects of healthcare, which holds great promise for better diagnoses, personalized treatments, and overall patient care.

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10 Personal Healthcare Trends To Look Out For In 2024

AI and ML are transforming personal healthcare by enhancing diagnostics, treatment, and overall wellness.

Here are 10 trends to watch out for in AI and ML in personal healthcare in 2024:

1. Personalized Treatment Plans: AI will analyze individual health data to create personalized treatment plans, including medication regimens and lifestyle recommendations. There will be an uptick in the number of chances for patients to get individualized healthcare in 2023. Precision medicine is a part of this, and it involves making individualized medicines and treatment plans for groups of patients based on characteristics like age, genetics, and risk factors, rather than using a cookie-cutter approach. By considering an individual’s genetic information, or genome, the most cutting-edge customized healthcare systems can assist doctors in determining the efficacy of medications and the likelihood of adverse effects. These forecasts are occasionally assisted by AI and ML systems.
2. AI for Mental Health: AI-driven mental health apps and platforms will provide therapy, counseling, and support for individuals dealing with mental health issues. Forecasts indicate that by 2023, the market for AI tools, particularly ML tools used in healthcare, will surpass $20 million. There is a lot of evidence that AI-aligned technologies like pattern recognition algorithms, computer vision, and natural language processing may improve healthcare. These technologies are now widely used in the industry and will only become more so as 2023 progresses. Drug discovery is one area where AI is used; it helps predict the results of clinical trials and the side effects of new drugs. Another area is medical imaging analysis, where AI is used to use computer vision algorithms to detect early warning signs of disease in X-rays or MRI scans. It has also shown promise in the diagnosis and treatment of neurological diseases, such as Alzheimer’s and Parkinson’s.
3. Wellness and Lifestyle Management: AI will help individuals make healthier choices by analyzing data from wearables and providing personalized fitness and nutrition guidance. In 2023, wearable technology will be more popular among both patients and doctors for remote patient monitoring and health and fitness tracking. Smartwatches that can do complex scans like electrocardiograms (ECGs), smart fabrics that can detect blood pressure and predict the likelihood of heart attacks, and smart gloves that can alleviate tremors experienced by Parkinson’s disease patients are just a few examples of the incredible growth of the “Internet of Medical Things” in the past few years. The development of wearable gadgets that can monitor and identify indicators of mental diseases is gaining attention alongside physical sickness. Medical wearables could soon include some of the features shown in research published this year that show how physical markers like sleep patterns, heart rate, and activity levels can be used to determine when someone might be at risk of depression.
4. Health Data Security: AI will strengthen data security by monitoring and identifying potential breaches and unauthorized access to personal health information. These trends indicate the increasing role of AI and ML in personal healthcare, with a focus on enhancing individual health, improving diagnoses, and making healthcare services more accessible and convenient. Staying informed about these developments will be crucial for individuals and healthcare professionals seeking to harness the benefits of AI and ML in healthcare in 2024 and beyond.
5. Remote Patient Monitoring: AI-powered wearables and devices will monitor patients’ health remotely, providing real-time data to healthcare providers for proactive care. Patients with non-emergency ailments may now see their physicians more quickly and inexpensively through remote, live video sessions utilizing their computers or mobile phones. This is due to the restricted access to healthcare staff. Patients can also message their doctors and organizations using telehealth technologies to ask questions about insurance or adjust their prescriptions. Additionally, it facilitates easy access to health education for patients. In addition, a patient’s whole medical history can be more easily accessible with telehealth systems as they enable the integration of data from various patient visits and test findings into electronic health records. Particularly for long-term health issues like hypertension and cardiovascular disease, telemedicine allows patients to stay active participants in their treatment when integrated with data from health wearables.
6. AI-Powered Virtual Assistants: Virtual health assistants will use AI to answer medical queries, provide health advice, and assist with appointment scheduling and medication reminders. Accenture found that 62 percent of those who use healthcare prefer virtual solutions. The same poll also indicated that 57% of people would prefer a way to have their chronic health conditions monitored remotely. Also, for regular checkups, 52% would choose virtual treatment. Given the chance, 42% of customers would “definitely or probably” go for a virtual option, even for disease diagnosis. Babylon Health and other health service companies are now offering new telehealth services.
7. Genomic Medicine: ML algorithms will assist in the interpretation of genomic data, aiding in the diagnosis and treatment of genetic conditions. Medications are usually made with a “one-size-fits-all” mentality, prioritizing maximum effectiveness with minimal adverse effects. Genomic research, digital twins, and artificial intelligence have all enabled doctors to take a more individualized approach, leading to medicines that are a perfect fit for each patient. While it has the potential to alleviate chronic pain effectively, it also carries the risk of side effects when taken in large quantities. Working together, pharmaceutical firms and healthcare facilities can develop individualized diagnostic and therapeutic instruments. Based on particular criteria such as blood sugar levels, personalized therapy offers individualized advice for exercise, nutrition, and disease management. It swiftly results in safe medications for long-term health problems like preventing heart attacks, arthritis, cancer, and Alzheimer’s.
8. Predictive Healthcare Analytics: AI will predict health trends and disease outbreaks, helping healthcare systems prepare for and mitigate health crises. Software like this may do things like remind patients of their next check-ins or find out if people tend to miss their appointments. Hospitals may enhance patient satisfaction and prevent staff overburden by optimizing wait times and staffing based on more accurate patient counts.
9. Drug Discovery: ML-driven drug discovery will accelerate the development of new pharmaceuticals, improving treatment options for various medical conditions. It can take a long time—and a lot of money—for pharma firms to bring a medicine to market. To save time and money, machine learning might sift through mountains of health-related or biological data for previously unseen insights. From the first idea to the final results of a medication study, machine learning is already an integral part of the process.
10. AI in Radiology: AI will continue to enhance radiological diagnostics, aiding radiologists in the detection of diseases and abnormalities with greater accuracy. The resolution of these photographs can be improved by artificial intelligence using upscaling algorithms. The use of image data augmentation techniques allows for the synthetic generation of data for these types of models. To complete the radiology workflow, other AI algorithms may be fed these improved pictures.

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Smart Use of Artificial Intelligence in Health Care

The MGI has investigated the potential effects of AI and automation on the future of employment. Healthcare is one of the industries with the least amount of time that might be automated—only 35% of the time, and this varies by job type—but automation will impact most employment across all industries to varying degrees. The possibility of automation and the probability of its implementation are distinct.

The research is based on a middle-ground scenario that predicts that 15% of healthcare workers’ current shifts will be automated. The following graphic displays, for a variety of healthcare vocations in certain European nations, the percentage of working hours that might be eliminated by automation by the year 2030. This doesn’t take into account the possibility of subsequent upheaval due to other variables, such as customization, which can transform healthcare by centering on a “portion of one.”

When it comes to healthcare, how many jobs will be eliminated by AI and automation? The truth is that there is a huge and predicted growing manpower gap in the European healthcare sector. As an example, the present supply of 8.6 million nurses, midwives, and healthcare assistants across Europe will not be enough to fulfill present or expected future demand, according to the World Health Organization, which forecasts overall need for healthcare professionals to climb to 18.2 million across Europe by 2030.4Care providers essential to the daily lives of European people, such as home health aides, licensed practical and vocational nurses, and others, will be in high demand in the future, according to MGI’s demand analysis of healthcare activities. It shows that automation has the potential to help with healthcare manpower shortages, as demand for healthcare jobs is expected to rise. For instance, even though around 10% of nursing tasks might be eliminated by automation, the overall number of nursing employment is projected to rise by 39% by 2030.

More than only employment gains or losses, the workforce will feel the effects of changes to the nature of work itself. Any shift in perspective is a chance to reevaluate and enhance patient care. Up to 70% of a healthcare provider’s time is devoted to mundane administrative duties; AI can assist in eliminating or significantly reducing this burden.

As a result, healthcare education will need to evolve to place more emphasis on creativity, entrepreneurship, lifelong learning, and collaboration across disciplines rather than rote memorization of data. The most significant shift will be the requirement for healthcare companies to include digital and AI capabilities. This includes training frontline employees to use AI in their daily tasks as well as doctors to alter the traditional consultation model. Practitioners, organizations, and systems must all work in tandem to bring about this massive shift in corporate culture and capabilities.

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The idea that this kind of AI employment would be both popular and controversial-free was a common thread running across the interviews. AI is capable of more. Improved patient outcomes and treatment quality are possible benefits of its ability to supplement various clinical activities and provide healthcare practitioners with access to relevant information. It has the potential to facilitate remote monitoring and patient empowerment through self-care, increase the speed and accuracy of tests, and make more information available to practitioners more quickly and easily.

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Avenda Health, an AI healthcare company creating the future of personalized prostate cancer care, announced the results of a new study, “Prediction and Visualization of Lesion Extent in Intermediate-Risk Prostate Cancer using Artificial Intelligence,” published in the European Urology Open Science. Led by Stanford University School of Medicine‘s Department of Urology, researchers found that Avenda Health‘s artificial intelligence (AI) software Unfold AI, was shown to be accurate and effective in identifying the extent of prostate cancer.  This could be helpful in reducing the likelihood that cancer could be missed and left behind during treatment. The study demonstrates considerable promise for the technology to aid in reducing cancer recurrence rates.

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The study, including 50 prostate cancer patients, found that the AI-driven approach which incorporates biomarker, biopsy, and image features would be better equipped to define cancer risk and treatment margins than the current standard of care. In particular, the rate of complete encapsulation of clinically significant prostate cancer by the AI margins was much higher than that of conventional margins (80% versus 56%). In nearly half of cases, clinically significant disease was found beyond conventional margin boundaries, indicating that a patient-specific treatment planning approach should be adopted for surgery, focal therapy and active surveillance.

“After nearly a decade of research and development, we are thrilled to see these promising results with independent validation of our AI mapping platform,” said Shyam Natarajan, Ph.D.,  co-founder and CEO of Avenda Health.“The prostate cancer space has seen little to no advancement in nearly 40 years, and we look forward to bringing this important information to more prostate cancer patients in the coming year.”

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“Our mission at Avenda Health has always been to bring personalized care to prostate cancer patients to improve quality of life. These study results will be instrumental in forging a path forward in providing an alternative to the standard of care and giving urologists and their patients the confidence in providing an effective prostate cancer treatment,” said Brittany Berry-Pusey, Ph.D. co-founder and COO of Avenda Health.

One in eight men will develop prostate cancer in their lifetime.The current one-size-fits-all approach of treating the entire prostate‒because current MRI technology cannot identify the full extent of the tumor and cancer growth within the organ‒results in nearly 50% of patients losing their sexual or urinary function. Avenda Health‘s AI-driven approach personalizes the patient’s treatment journey providing options to preserve quality of life and prevent recurrence. Providing physicians with a personalized, 3D visualization of the cancer offers a better informed decision on the course of treatment and the opportunity to preserve healthy tissue. Avenda Health‘s prostate cancer management platform, Unfold AI, received FDA clearance in late 2022, opening the door for more precise prostate cancer management using AI.

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Focused on Health GenAI and CERVAI, a generative AI brain health platform

DiagnaMed Holdings Corp, a generative AI healthcare solutions company, is pleased to announce the launch of Health GenAI, a new division focused on the development and commercialization of a suite of generative AI ready-made and customizable applications powered by GPT-4 to support the healthcare market in improving patient outcomes, operational workflow and efficiency. The Company expects to launch at least three products from its Health GenAI division this year.

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DiagnaMed is organized to focus on its two divisions, CERVAI™, a generative AI brain health platform, and Health GenAI. According to Market.us, generative AI in the healthcare market is set to reach approximately USD 17 billion by 2032, driven by the adoption of automation by healthcare operators in drug discovery and development, medical imaging and diagnostics, personalized medical interventions, and hospitals and clinical decision support systems.

Fabio Chianelli, Chairman of DiagnaMed, commented: “We are passionate about developing new generative AI-powered SaaS products to serve the needs of the healthcare sector. With the launch of our new division, Health GenAI, we are focusing on commercializing at least three generative AI solutions for the healthcare market and on complementing CERVAI™, our generative AI brain health platform.”

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As part of its Health GenAI division, the Company recently announced the launch of its first commercial product, FormGPT.io a generative AI data collection and analysis solution for the healthcare market, which was born from the development experience and features of CERVAI™. FormGPT.io allows licensed medical professionals, hospitals, and life science to create customized forms and surveys with the support of ChatGPT and collect relevant patient data, obtain pre-and-post-visit and treatment feedback, monitor patient progress, and analyze results for decision-making. FormGPT.io empowers licensed professionals and clinical researchers to easily and quickly develop forms and surveys that complement their workflow and specific patient and research objectives. In addition, FormGPT.io aims to improve user services, workflow, patient outcomes and engagement. The Company is making its minimal viable product version of FormGPT.io available to the public with a 7-day free trial.

DiagnaMed Holdings Corp, a generative AI healthcare solutions company, is focused on the development and commercialization of CERVAI™, a proprietary brain health AI platform, and Health GenAI, a suite of generative AI SaaS products for the healthcare market.

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Security issues, data breaches, and patient privacy are very common yet major concerns in the healthcare sector. Blockchain, a type of Distribution Ledger Technology (DLT) has the potential to combat most of the data storage and data sharing problems in the healthcare industry today. From protecting health data and upholding patient information to ensuring that the patient is placed at the center of the ecosystem, Blockchain is transforming the way the healthcare system works.

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What is Blockchain? 

First things first, let’s understand what Blockchain technology is. Blockchain is a shared database or ledger that enables data storage and sharing in a decentralized manner.

The National Institute of Standards and Technology (NIST) defined Blockchain as,

tamper evident and tamper resistant digital ledgers implemented in a distributed fashion (i.e., without a central repository) and usually without a central authority (i.e., a bank, company, or government). At their basic level, they enable a community of users to record transactions in a shared ledger within that community, such that under normal operation of the blockchain network no transaction can be changed once published.

How does Blockchain technology help? 

• Data transparency
• Extremely difficult to hack
• Protects medical data
• Easy data access
• Easy exchange of data
• Data sharing with only authorized personnel

EHRS and Data Exchange 

In 2016, the Office of the National Coordinator (ONC) announced an open challenge inviting white paper several authors to submit their entries exploring Blockchain’s potential in addressing the security and privacy of data. Called the Blockchain Challenge, ONC offered cash prizes (in thousands) to decipher Electronic Health Record (HER)-related challenges. Out of 70 entries, 15 were selected.

When it comes to clinical decision-making, a lot rides on care coordination and the ease with which the data is connected to patients. One of the winners, Beth Israel Deaconess Medical Center categorically mentioned that EHRs were not an apt fit for lifetime medical record management.

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Instead, the authors suggested MedRec, a Blockchain-based system that not only enables patients to allow changes in their EHRs but also allows access to new providers and enables data sharing between providers.

How Blockchain secures healthcare records  

With the ever-increasing amounts of data and data breaches, one of the biggest challenges the healthcare industry faces today is data security. Protecting health data is the top priority for all healthcare providers. The biggest advantage of Blockchain is that it uses immutable ledgers to update information on all networks simultaneously. Unlike a central repository system, in Blockchain the data cannot be updated or tampered with.

Another way Blockchain is equipped to ease the data breach pain is through its data blocks which are continuously attached or connected to all the blocks in the network. This includes the blocks which come that are created before and after using the unique signature. When data within a certain block requires updating, a new block is automatically added rather than editing and updating the existing block. This brilliant technology ensures each data (which is added as well as updated) entry is transparent with a proper time stamp.

As Blockchain uses decentralized consensus, it is rather extremely difficult and time-consuming to alter one whole blockchain as this would require consensus from all the parties involved. In one odd case when a bad actor does try to exploit this agreement, they will not only have to gain control over most of the nodes in the network but also alter the data for the whole blockchain they are targeting.

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How do Fog Computing and Healthcare Internet Of Things work together?

One of the factors that majorly impact how patient-generated health data (PGHD) data is collected, analyzed, and utilized is the Healthcare Internet Of Things (IoT). Patient data is created by a variety of devices such as blood glucose monitors, Mhealth apps, and home scales.

While the data has enormous potential, with its sheer volume, PGHD data can often be unstandardized. To use PGHD optimally, the data must be clear, crisp, and instant. These features enable real-time analytics, which can be especially useful in preventing patient harm or death. Usually, several organizations depend on cloud computing devices for real-time analytics which enables the data to be uploaded to the cloud from the device. The relevant information is filtered and fed into an analytics engine and presented to clinicians. The shortcoming here is that the process can be time-consuming and hence, not an ideal choice during the time of an emergency. This is where fog computing devices come to the rescue. Fog computing enables IoT devices to conduct their analytics by adding just a layer between the device and the cloud perfect for large analytics.

With predefined user and authorized protocols, patient data can be shared via a distributed interface. This automatically results in faster data transmission without having to share a whole new record every time an organization makes a change. With Blockchain technology, users are enabled to view as well as modify information and are also equipped to view it in real-time.

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Avenda Health, an AI healthcare company creating the future of personalized prostate cancer care, announced its cancer management platform, iQuest, has received 510(k) clearance by the US Food and Drug Administration (FDA).

iQuest combines existing patient-specific diagnostic information and deep-learning algorithms to create a tailored map of where cancer is within the prostate that for the first time will allow for more personalized, effective and precise treatments. The platform enables a physician to make decisions that consider the cancer extent rather than treating the whole organ. This information supports physicians and patients with treatment selection, planning, guidance, and follow-up.

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“We are excited about the potential to unlock precision care in prostate cancer with iQuest, as it is a key enabling technology for focal therapy to be a reality for urologists and patients,” said Dr. Shyam Natarajan, co-founder and CEO of Avenda Health. “In order for a doctor to treat focally, they need to know where cancer is and the healthy tissue to avoid. This is vital information that iQuest now provides. This is a huge step forward in transforming the standard of care in prostate cancer and brings us that much closer to offering effective therapy that preserves quality of life to providers and patients across the U.S.”

One in eight men will develop prostate cancer in their lifetime. The current one-size-fits-all approach of treating the entire prostate‒because current MRI technology cannot identify the full extent of the tumor and cancer growth within the prostate‒results in nearly 50 percent of patients losing their sexual or urinary function. iQuest personalizes treatment options for the individual patient in order to preserve quality of life and prevent recurrence. Providing physicians with a 3D visualization of the cancer offers a better understanding of the extent of the disease to aid in treatment planning that can preserve quality of life while minimizing cancer left behind.

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iQuest was built upon a decade of research from hundreds of thousands of data points and validated in multiple clinical studies. In one study, urologists improved their sensitivity of identifying tumor extent by using iQuest from 37% to 97% and changed their treatment recommendation in 27% of cases, with the biggest change towards a more localized treatment. iQuest can be applied to multiple treatment options to guide a doctor’s intervention plan,  including FocalPoint—Avenda Health’s soft tissue laser ablation device—and other focal treatments, active surveillance, and decision-making for whole gland treatments including radical prostatectomy and radiation therapy.

“At the heart of what we do is the belief that patients should never have to choose between quality of life and cancer control,” said Dr. Brittany Berry-Pusey, co-founder and COO of Avenda Health. “By providing a personalized cancer map, iQuest opens the door for more precise treatments. This clearance will go a long way not only for our company but for the future of prostate cancer care.”

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Deep Bio, a company concentrating on SaMD (Software as a Medical Device) for digital pathology, offering clinically validated, AI-based DeepDx algorithms, and Indica Labs, a leading provider of computational pathology software and services, are excited to announce the successful integration of the DeepDx Prostate algorithm into the HALO AP platform from Indica Labs.

DeepDx Prostate is a CE-marked, AI-based image analysis algorithm that detects prostate cancer in core needle biopsies and grades their severity according to the Gleason scoring system. DeepDx Prostate is designed to alleviate the shortage of pathologists and their heavy workload, while reducing diagnostic subjectivity and variability. Validation testing of the DeepDx algorithm, published in Modern Pathology 2022, demonstrated 99% sensitivity and 97% specificity. The algorithm is also extensively tested in real clinical workflows, analyzing over 700,000 cores between 2019 and 2021.

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The HALO AP platform was developed by Indica Labs to address the specific needs of anatomic pathology labs by supporting a wide range of tissue-based workflows, including primary diagnosis, secondary consults, tumor boards, clinical trials, synoptic reporting, quantitative analytics, and AI. HALO AP incorporates state-of-the-art workflow management tools allowing users to easily integrate quantitative analytics and AI tools built using HALO, HALO AI and third-party algorithms, such as DeepDx. To simplify integration, a HALO AP analysis software development kit (SDK) including sample code is available to all algorithm developers. One of the key advantages of HALO AP is the ability to deliver AI algorithms in an automated, stepwise workflow that can be locked, secured, and audited to prevent tampering or misuse.

DeepDx Prostate analysis can be triggered directly in HALO AP by selecting the DeepDx workflow or run automatically via the HALO AP API. Analysis progress, all results, and visual markup images can be reviewed in HALO AP, removing the need to shift between systems.

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Steven Hashagen, CEO at Indica Labs commented, “As digital pathology continues to enable AI-based workflows, we’ve recognized that to increase efficiency, case management systems like HALO AP must support full integration of algorithms without sacrificing usability. The integration between DeepDx and HALO AP demonstrates how any algorithm vendor can leverage HALO AP to deliver clinically relevant results directly within the pathologists’ viewing software, eliminating the need for an AI-specific viewer.”

Sun Woo Kim, CEO at Deep Bio commented, “Deep Bio’s partnership with Indica Labs is a step closer to our vision and goal of providing diagnostic support tools for pathologists and oncologists, for timely and accurate diagnosis and prognosis, leading to better treatment decision-making. We believe DeepDx Prostate is a powerful addition to the robust clinical workflow afforded by HALO AP.”

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Aidoc, the leading provider of AI healthcare solutions, announced a partnership with UofL Health, a fully integrated regional academic health system with more than 12,000 team members serving more than 1.5 million patients annually. UofL Health is the first academic health system in Kentucky to implement Aidoc’s AI solution. Choosing Aidoc as its AI partner, UofL Health will onboard the company’s AI Care Platform to upgrade its care delivery systems and optimize workflows designed to improve the outcome of patients.

This project coincides with the University of Louisville’s introduction of the Center for AI in Radiological Sciences (CAIRS), which was introduced in March and designed to foster collaboration between data and clinical teams. UofL Health will incorporate Aidoc’s AI algorithms from the AI Care Platform to improve care for all patients, using AI to prioritize cases that are positive within a radiologist’s worklist to ensure patients’ access to lifesaving treatments is expedited. UofL will be integrating Aidoc’s algorithms to identify and prioritize cases of brain bleeds (intracranial hemorrhage), lung blood clots (pulmonary embolism), incidental pulmonary embolism (iPE), cervical spine fractures, rib fractures and intra-abdominal free gas (IFG).

“At UofL Health, our patients are our top priority and we want to ensure that our physicians are equipped with the most updated tools to reduce turnaround time to reporting positive cases identified by the radiologist and ensure that patients are getting treated as quickly as possible,” says Dr. Sohail Contractor, a radiologist with UofL Health and Professor and Chairman, J.T. Ling, M.D. Endowed Chair of Radiology for the University of Louisville School of Medicine. “In Aidoc, we have found a partner who will empower us to deliver on our vision, with a clear and immediate ROI. During the training session, the solutions flagged a number of true positive cases. We are confident that the integration will continue to support our physicians and show a recognizable impact on our patients.”

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Aidoc’s AI Care Platform hosts 15 total FDA-cleared medical imaging AI solutions—9 developed at Aidoc and 6 through third-party vendors—and heart and vascular and neurology AI solutions which orchestrate physician collaboration to expedite care processes. The platform empowers health systems to apply the clinical benefits of artificial intelligence across the entire spectrum and set of facilities in a health system. In clinical research settings, Aidoc’s AI solutions have proven to help reduce patient length of stay in the emergency room; reduce the turnaround time to reporting positive cases for treatment; and empower physicians to collaborate and ensure patients who require surgical interventions are not missed and attended to by care teams. UofL Health joins the likes of nationally recognized health systems like Mayo Clinic, Cedars-Sinai and Mount Sinai in integrating Aidoc’s platform solutions.

“We were inspired by the team at UofL Health and its drive to ensure that their facilities are of the highest quality, providing the best care to their patients,” said Elad Walach, CEO and cofounder of Aidoc. “The project we’re undergoing with UofL Health is ambitious, underpinned by the belief that AI can make a deep impact only through meaningful collaboration between physicians and technology. UofL’s drive for care excellence, coupled with the ability of AI to transform a data-driven organization is what makes this partnership so successful.”

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HNAP accreditation ensures adherence to health data processing standards and compliance with security infrastructure and integrity requirements

Retrace, a leader in dental artificial intelligence and the first native-built AI healthcare clearinghouse providing digital infrastructure for US health care, announced it has achieved full accreditation with the Healthcare Network Accreditation Program (HNAP) for Electronic Health Networks (EHN) from the Electronic Healthcare Network Accreditation Commission. HNAP EHN accreditation recognizes excellence in health data processing and transactions and is intended for organizations whose electronic health networks perform claims clearinghouse or EDI gateway functions to ensure compliance with industry-established standards and HIPAA regulations.

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Through EHNAC’s comprehensive third-party review, Retrace was evaluated in areas of privacy measures, systems availability and security infrastructure. In addition, EHNAC reviewed the organization’s process of managing and transferring protected health information and determined that the organization meets or exceeds all EHNAC criteria and industry standards. Through completion of the rigorous accreditation process, the organization demonstrates to its constituents, adherence to strict standards and participation in the comprehensive, objective evaluation of its business.

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“Retrace holds itself to the highest standards and we are committed to protecting our doctors and their patients’ personal health information, ” said Dr. Ali Sadat, Founder and CEO of Retrace. “We are proud to be the first dental AI company to achieve this ‘seal of approval’ and firmly believe this accreditation demonstrates our commitment to data protection, privacy and security on behalf of our insurance and provider partners.”

“This is an important achievement for a company – it conveys Retrace has taken the necessary steps to ensure its stakeholders and customers that it is adhering to the latest standards in privacy, security and compliance. Regulatory concerns continue to be front and center on the minds of leadership in today’s healthcare ecosystem,” said Lee Barrett, executive director and CEO of EHNAC. “Attaining a Healthcare Network Accreditation provides a ‘seal of approval’ for Retrace, which has demonstrated a full commitment to ensuring the security and privacy of health data processing and transactions for their customers.”

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