Anees Abdullateef

Step by step how to create Disruptive Med Tech Butterfly Network Ultrasound scanner 1. Find urgent problem like ultrasound scanner 2. Make it much smaller and cheaper: (minimum: screen, data storage) 3. Instead of selling the device as for Per Per use payments 4. Use cloud to store data and count how many time device was used 5. Use mobile/web app to provide extra analytics for subscription You can find more about Butterfly Network Ultrasound scanner use on our blog and video https://lnkd.in/dSDQhpHJ #MedTechInnovation #IoTDevices #ProductDevelopment #DisruptiveTech #HealthTech #WizzDev #IFA_Berlin

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Dr. Isaac Kohane, a renowned expert in biomedical informatics and a pioneer in integrating electronic health records (EHRs) with artificial intelligence (AI), will be honored at PMWC 2025 (Feb. 5-7). His groundbreaking work has paved the way for personalized medicine and transformed healthcare delivery. On Sep. 4, 2024, a group in the Harvard Department of Biomedical Informatics, which Dr. Kohane chairs, together with collaborators, published a groundbreaking AI model for cancer diagnosis in Nature, which outperforms current methods in cancer prognosis and diagnosis. The model, trained on over 60,000 pathology slides, is a major advancement in the field of AI-driven healthcare. More: https://shorturl.at/tv3Jo Dr. Kohane's achievements include: Developing the i2b2 toolkit, an open-source platform that integrates large biomedical datasets from EHRs and genomics to advance PM. These Living Laboratories have been pivotal in enabling large-scale studies, including COVID-19 research and chronic disease management. Creating the SMART-on-FHIR API simplifies how healthcare applications access EHR data, making it easier for providers, patients, and developers to leverage health information. Widely adopted & empowering patients through platforms like #AppleHealth, used by over 800 hospitals to provide programmatic access to EHR data, transforming patient data accessibility and driving innovations. At PMWC 2025 on Feb. 6th at the Santa Clara Convention Center, Dr. Kohane will deliver a keynote on the potential of AI in personalized medicine. Following his keynote, other important sessions will include "From Data to Decisions: Real-Time Patient Insights for Improved Care," chaired by Michael Pfeffer from Stanford Medicine, featuring Christopher Longhurst from UC San Diego Health, Tanya Townsend MSMI, CHCIO, CDH-E from Stanford Children’s, Kiran Mysore from Sutter Health, and Cherodeep Goswami from UW Health. Additionally, the session on "Data Privacy and Security Challenges to the Use of Health Data in AI" will be chaired by Deven McGraw from Ciitizen Health. To wrap up the track, David Reese from Amgen will present "Accelerating Drug Development with Real World Evidence and AI" Full interview: https://lnkd.in/gMUfkVbn See PMWC 2025 speakers: https://lnkd.in/dEc6Q3vS Join me in congratulating him on being honored for his contributions. Differentiated Therapeutics, Kenneth Mandl, Gil Omenn, David McCallie Jr ,Paul Avillach, MD, PhD, Brett Beaulieu-Jones, Nigam Shah, Peter Szolovits, Enrico Coiera, Kun-Hsing Yu, MacLean Nasrallah, Eliana Marostica, Thomas Denize, Junhan Zhao, Ph.D., M.S. Ruijiang Li MedAware, Curie.Bio, Rachel Badovinac Ramoni, Shai Shen-Orr, Holly Gilmer, Gunnar Rätsch, Samantha Finlayson. Sequence Bio, Courtney Morales Hofmann #AI #healthcare #personalizedmedicine #EHR #dataanalytics #PMWC25 #PrecisionMedicine #AI #DataScience #HealthcareInnovation #RealWorldEvidence

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𝗜’𝘃𝗲 𝘀𝗽𝗼𝗸𝗲𝗻 𝘄𝗶𝘁𝗵 𝟱𝟬+ 𝗖𝗠𝗜𝗢𝘀, 𝗖𝗜𝗢𝘀 𝗮𝗻𝗱 𝗖𝗗𝗢𝘀 𝗶𝗻 𝘁𝗵𝗲 𝗽𝗮𝘀𝘁 𝟭𝟮 𝗺𝗼𝗻𝘁𝗵𝘀 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜 𝗶𝗻 𝗛𝗲𝗮𝗹𝘁𝗵 𝗦𝘆𝘀𝘁𝗲𝗺𝘀. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 𝟭𝟬 𝗺𝗼𝘀𝘁 𝗰𝗼𝗺𝗺𝗼𝗻 𝗶𝗱𝗲𝗮𝘀 𝗮𝗻𝗱 𝗹𝗲𝘀𝘀𝗼𝗻𝘀 𝗹𝗲𝗮𝗿𝗻𝗲𝗱: 1. AI for backend, administrative workflows is low-risk and low hanging fruit. AI for direct patient care is higher-risk and needs more thoughtfulness when trying. The closer we get to the patient, the higher the risk, and the more thoughtful (and thus slower) we must be. 2. For clinical care, clinicians are most open to AI as a co-pilot. Similar to having a medical trainee with you at all times, and the physician still has to sign off on things. 3. While various AI co-pilots may enhance patient care and clinician well-being, the data shows many don’t necessarily save time. 4. Autonomous AI agents that own end-to-end clinical care are much further away. Technologists underestimate the clinical complexity of many clinical scenarios, the risk/benefit trade offs are not yet well-studied and the liability implications are unclear. 5. AI medical scribes and drafting patient portal messages are by far the two most common Generative AI use cases being tested and implemented right now. 6. Adoption of AI Scribes by clinicians has been mixed - it’s game changing for some, but it’s not been for everyone. The value isn’t increased patient throughput, but rather improved clinician well-being. 7. Generative AI for drafting patient portal messages also has had mixed results on adoption - also not for everyone. 8. The current AI roadmap is primarily driven by the EHR as lots of the opportunities for improvement are reducing the administrative burdens… created by the EHR in the first place. 9. AI prediction models are only useful if the insights are actionable, fit the clinical workflow, and align with drivers for adoption. Which means many AI models make great research publications but never actually get implemented at scale. 10. AI adoption is not special - it requires the same equation for success as any Health Tech: Success = Tech (AI) + Process + People 𝗡𝗼𝘄 𝘁𝗵𝗲𝘀𝗲 𝗮𝗿𝗲 𝗰𝗼𝗻𝘀𝗲𝗻𝘀𝘂𝘀 𝘃𝗶𝗲𝘄𝘀... 𝗯𝘂𝘁 𝘁𝗵𝗮𝘁 𝗱𝗼𝗲𝘀𝗻’𝘁 𝗺𝗮𝗸𝗲 𝘁𝗵𝗲𝗺 𝗿𝗶𝗴𝗵𝘁 🙂 𝗜’𝗺 𝗰𝘂𝗿𝗶𝗼𝘂𝘀: 𝘄𝗵𝗶𝗰𝗵 𝗼𝗳 𝘁𝗵𝗲𝘀𝗲 𝗱𝗼 𝘆𝗼𝘂 𝗱𝗶𝘀𝗮𝗴𝗿𝗲𝗲 𝘄𝗶𝘁𝗵? #digitalhealth #healthcareinnovation

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Consistent evidence of Aquablation safety and efficacy in BPH

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🚨 Why Do Tech and specifically Healthtech Companies Fail in the Middle East? 🚨 Bringing MedTech to the Middle East is a massive opportunity, but many companies miss the mark. Here are the 3 key reasons: 1️⃣ Lack of Market Research: Many assume the Middle East is an "easy access" market, but they fail to study local healthcare trends, regulatory challenges, and patient needs. Without this, success is elusive. 2️⃣ Not Tailoring to Local Needs: Copy-pasting global solutions won’t work. Healthtech companies must tailor their offerings to fit local cultural and healthcare dynamics to truly succeed. 3️⃣ Strategic Partnerships: Too many pick the wrong partners or overlook the established key players. Building the right alliances is crucial to navigate the market and gain traction. Want to strategically bring your MedTech to the Middle East? Contact me at https://lnkd.in/d95Qs2eD to book an appointment. #HealthTech #MedTech #MiddleEast #Innovation #StrategicPartnerships #MarketEntry #HealthcareInnovation #DigitalHealth #HealthTechTrends #MedTechGrowth #MiddleEastBusiness #HealthcareStartups #MarketResearch #BusinessStrategy #GlobalHealth #MedicalTechnology #TechInHealthcare #StrategicAlliances #PartnershipsMatter #EmergingMarkets #TailoredSolutions #HealthcareTransformation #HealthcarePartnerships #InnovationStrategy #BusinessExpansion #MiddleEastTech #MedTechSolutions

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Training departments in top Medtech companies are completely screwing their salespeople. Let’s face it, it’s product training not sales training. I can tell you who gets it… Medtronic, DePuy Synthes, and Pristine Surgical They believe Virtual Sales RX sales enablement training has dramatically helped their sales forces. Just ask them…… If you would like to learn more please connect with me in the comments.

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Training departments in top Medtech companies are completely screwing their salespeople. Let’s face it, it’s product training not sales training. I can tell you who gets it… Medtronic, DePuy Synthes, and Pristine Surgical They believe Virtual Sales RX sales enablement training has dramatically helped their sales forces. Just ask them…… If you would like to learn more please connect with me in the comments.

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Without strong clinician involvement in AI development, we risk missing a lifetime opportunity to create massive value for ourselves, our institutions, and our patients. This was the core message I shared with radiologists at the 2024 Moroccan Medical Expo on Friday👇 The AI development process in radiology and medicine is hungry for clinician expertise and input, yet many clinicians remain spectators. I believe we can do more and take a stronger lead in this transformation. By being more proactive and open to industry and startup collaborations, we can ensure the developed products meet our needs and deliver significant value to the healthcare system and patients. For this to happen, a fresh clinician mindset and setup are required, including: - Open-mindedness toward AI as a disruptive technology, toward startups that are leading AI tool development, and toward new business and industrial partnership models - Investments in our data and IT infrastructures to be ready for AI tool co-development - Robust state and institutional frameworks to enable productive and safe collaboration between healthcare institutions and the industry, especially regarding patient privacy and rights - Protected time for clinicians to collaborate with the industry and startups - Education for clinicians about technology, innovation, and business concepts to facilitate communication with the industry and better drive the AI transformation. This fresh mindset applies beyond radiology and can foster meaningful innovation in every segment of medicine, given the broad impact of AI. It was a pleasure to meet and exchange ideas with the Moroccan radiology community and to see that my message resonated with the audience and key opinion leaders. Looking forward to continuing the discussion online ! 🚀 #Radiology #AI #Mindset #Clinical #Leadership

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[SDOH Reverse Robinhood???] The following SDOH / MIPS perspective was generated by Google’s generative AI as result of a recent Google search: “MIPS and SDOH:” “The Medicare Merit-Based Incentive Payment System (MIPS) may penalize physicians for social factors outside of their control. This could include physicians who care for patients with increased social risk, such as those who are dually eligible for Medicare and Medicaid. For example, a 2020 study found that physicians with these patients had lower MIPS scores than other physicians. This could be because value-based payment designs often don't account for social determinants of health, which are associated with about 38% of the geographic variation in Medicare spending per beneficiary. This could also lead to the reverse Robin Hood effect, where resources are transferred from physicians caring for poorer patients to those caring for more affluent patients.” According to JAMA: Findings in a “cross-sectional observational study of 284 544 physicians, physicians with the highest proportion of patients dually eligible for Medicare and Medicaid had significantly lower MIPS scores compared with physicians with the lowest proportion (mean, 64.7 vs 75.9; range, 0-100; higher scores reflect better performance). Meaning Physicians with the highest proportion of socially disadvantaged patients had significantly lower MIPS scores, although further research is needed to understand the reasons underlying the differences in MIPS scores by levels of patient social risk.” Takeaway: Physicians (and Hospitals and Healthcare Systems) MIPS results may be in direct proportion to their investment (or lack thereof) and commitment to addressing patient social determinants of health. Your thoughts are welcomed. This is fastenating and underscores the trickledown affects of SDOH in clinical care performance, i.e., patient outcomes and quality of care. #SocialDeterminantsOfUs JAMA Ref: https://lnkd.in/eKDei5ZB Image Ref: https://lnkd.in/e5qM6b8k

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Thank you for highlighting this tremendous opportunity in the healthcare platforms space, Giorgia Pezzotta. The $1 trillion Total Addressable Market (TAM) underscores the vast potential these platforms hold in transforming the healthcare landscape. Healthcare platforms have a distinct advantage over traditional software companies due to their ability to facilitate seamless interactions and exchanges of information among diverse stakeholders, including patients, providers, payers, and regulators. This interconnectedness is crucial for addressing some of the most pressing challenges in healthcare today. Key factors contributing to the success of healthcare platforms include: 1. Enhanced Connectivity: Platforms enable better communication and data sharing among healthcare providers, patients, and other stakeholders. This connectivity is essential for coordinated care and improved patient outcomes. 2. Scalability and Flexibility: Unlike traditional software solutions, platforms can scale more easily to accommodate growing user bases and adapt to changing market needs. This scalability makes them more attractive to investors and partners. 3. Innovation and Integration: Platforms often incorporate cutting-edge technologies such as AI, machine learning, and big data analytics. These innovations drive efficiencies and provide actionable insights that improve clinical decision-making and operational processes. 4. Value Creation: By streamlining workflows, reducing administrative burdens, and improving patient engagement, healthcare platforms create significant value for all stakeholders. This value generation is reflected in larger deal sizes and higher exit rates for platform companies. 5. Addressing Healthcare Inefficiencies: Platforms can tackle inefficiencies in healthcare delivery, such as fragmented care, lack of interoperability, and high administrative costs. By addressing these issues, they contribute to a more efficient and effective healthcare system. The interaction map you mentioned provides a clear visualization of how these stakeholders interact within the healthcare ecosystem, highlighting the central role of platforms in facilitating these exchanges. To fully capitalize on this trillion-dollar opportunity, it is essential for healthcare organizations to invest in robust platform solutions that prioritize user experience, data security, and interoperability. By doing so, we can drive significant advancements in healthcare access, quality, and affordability. I look forward to exploring the detailed insights in the report and continuing the conversation on how we can leverage healthcare platforms to transform the industry. #DigitalHealth #Platforms #HealthcareInnovation #Interoperability #HealthcareTransformation #HealthTech #ValueCreation #ConnectedCare #eHealth

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🚀 Excited to showcase our UAE-specific customization in medical coding GPT! 🚀 Our latest enhancement integrates MOH codes seamlessly into coding workflows while ensuring insurance compliance for precise billing. Here’s a quick example: 💡 Salbutamol (Ventolin Nebules) receives the correct MOH code for documentation (F68-5480-05000-01) and is flagged as “Strike Off” for billing under Daman Basic—all automated to align with UAE insurance protocols. This customization minimizes errors, ensures compliance, and streamlines coding accuracy, helping healthcare providers and RCM teams focus on what matters. #UAEHealthcare #MedicalCoding #Automation #Compliance #Innovation For more details, send DM or an email to [email protected] De-identified clinical note added in the comment for a quick reference. #openai #hospitals #AutonomousCoding #AIMedicalCoding #HealthcareAI #RevenueCycleManagement #HealthTech #MedicalCoding #NaturalLanguageProcessing #HealthcareAutomation #RCMaI #rag #llms

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A regulation is nothing more than entranchment of error into a system. CON laws? Administrative regulatory bodies? Value systems decided in closed door sessions? Healthcare has so much entrenched error it has limited innovation. Is this by design? Wanna see the $2 imaging exam? The $.35 cancer drug…remove entrenched error.

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Check out the article from our founder & inventor, Ahmed Al-Ghoul MD MBA about his journey with artificial intelligence & creating CSI Dry Eye Software.

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Back with another deep dive: AI Medical Coding 🏥 👩🏽‍💻 To put it mildly, medical coding is a huge pain point. It’s expensive, inefficient, and error-prone, not to mention challenging to staff with high team member turnover. Over the last five years, fully autonomous medical coding solutions have emerged, promising to address many of these pain points. The idea is simple (but not easy): take the medical chart, fully code it leveraging several types of AI (e.g., NLP, machine learning, and deep learning), and send it directly to billing without human involvement. Recently, the technology has progressed from handling straightforward encounters in high-volume specialties (e.g., radiology and pathology) to tackling more complex visits, such as emergency medicine. However some areas, like inpatient facility coding, remain out of reach. Evaluating solutions in this space can be tricky. Key criteria to consider include: ↳ Breadth of coverage across specialties and code types ↳ Coding accuracy and automation rates (but be sure to define automation clearly!) ↳ Support quality and responsiveness ↳ Coding auditability and transparency ↳ Pricing (obviously) Here's our working list of AI Medical Coding vendors. Anyone else we should add? • Aidéo Technologies • Arintra • CodaMetrix • CorroHealth • Fathom • Maverick Medical AI • Nym • Phare Health • RapidClaims.ai • Synaptec Health

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What's the best way to engage a healthcare customer? Get THEM talking. About what? About themselves. Specifically, what they would do in a specific situation or what their opinion is about a treatment or approach to a problem. Most med tech reps don't do this. Instead, they try to push their own opinions on a prospect (which is what you're doing when you only talk about how great your product is). HCPs don't care about your opinion. They care about theirs and those of their colleagues. So share what their colleagues think, and then ask them what they think. You'll learn a lot. And when you know a lot about your prospects, a great thing happens. You sell more. #MedicalSales #HealthcareSales #MedTech #PharmaSales #Hospital Sales

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When I first started exploring AI in healthcare, I thought benefit verification was a solved problem. Turns out, I was wrong. While a majority of benefit verifications are automated, there are still 4.8B verifications done manually every year. And it’s costing the medical industry an extra $9.8B [1] Here are 3 reasons why automating benefit verification is crucial for the future of healthcare. → 𝗦𝗽𝗲𝗲𝗱 - 𝗱𝗿𝗮𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆 𝗿𝗲𝗱𝘂𝗰𝗶𝗻𝗴 𝘄𝗮𝗶𝘁 𝘁𝗶𝗺𝗲𝘀 Picture this: It's January. New year, new insurance plans. Your staff is overwhelmed with benefit verifications for every patient. I've seen practices double their call center staff every January just to handle this influx. It's unsustainable. Meanwhile, your patients are waiting. They're postponing important procedures. Their conditions might be worsening. And there's a real risk they might seek care elsewhere if you make them wait too long. AI doesn't have these limitations. It can process verifications continuously, reducing wait times from days to minutes. → 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 - 𝗺𝗶𝗻𝗶𝗺𝗶𝘇𝗶𝗻𝗴 𝗰𝗼𝘀𝘁𝗹𝘆 𝗲𝗿𝗿𝗼𝗿𝘀 Imagine you've seen a patient multiple times without issue. Suddenly, a claim is denied. It turns out their company switched insurance providers, and you didn’t catch change in time. Now you're in a difficult position. The patient is frustrated, and you're facing a potential financial loss if you can't submit the claim within the required timeframe. Human error is inevitable, but AI offers consistency. It meticulously cross-references information and double-checks details. This significantly reduces these types of oversights. → 𝗖𝗼𝘀𝘁 𝗦𝗮𝘃𝗶𝗻𝗴𝘀 - 𝗯𝗲𝘆𝗼𝗻𝗱 𝘁𝗵𝗲 𝗼𝗯𝘃𝗶𝗼𝘂𝘀 When we talk about cost savings with AI, we're not just talking about boosting labor efficiency. Think about the hidden costs: - The time your highly trained staff spends on the phone – instead of patient care - The organizational complexity of managing a whole department just for verifications - The lost revenue from delayed or denied claims But the biggest cost? Physician burnout. Every minute a doctor spends dealing with administrative headaches is a minute they're not spending with patients. It's a minute that pushes them closer to throwing in the towel. AI can take this burden off providers' shoulders, letting them focus on patient care. Looking ahead: In five years, if you're not using AI for benefit verification, you'll be part of the $9.8B problem. And you’ll be at a serious competitive disadvantage. It's becoming less about efficiency and more about survival in a complex healthcare environment. — P.S. It's crucial to note that not all AI solutions are equal. You need a system that fits your organization’s particular needs. It should: - Integrate well with your existing tools and workflows - Learn from your historical data so it can hit the ground running - Deliver 50%+ ROI Do your due diligence before hiring a new AI solution.

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A Call to Surgeons Engaged with Healthcare Aggregators. As professionals, your expertise is being used by these aggregators, which is fine a far as the business model is concerned, but it is often at the cost of ethical standards. - You face the risk of operating on inadequately prepared patients. - You're pressured to perform surgeries on patients (leads) converted by telecallers, often without adequate information about the procedures required. - Medico-legal responsibility falls solely on you, as mentioned by the contracts you've signed with these entities. - The burden of ethical practice rests entirely on your shoulders, while for aggregators, you and patients are just the numbers. Consider the implications of such practices on your professional integrity and the well-being of your patients. #NHA National Health Authority (NHA) National Medical Commission Dr Basant Garg IAS

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🚨 LEAKED: What 1000+ Night Emergency Cases Taught Me About Healthcare's Future [The 3 AM insight that's making health tech companies uncomfortable] A thread exposing what Silicon Valley doesn't understand about healthcare transformation... SHOCKING REALITY: While managing critical emergencies, I discovered: • 82% of health tech solutions fail because they never saw a real patient • Only 3% of digital health leaders understand front-line healthcare • The missing 15% that could save billions in healthcare waste THE EMERGENCY ROOM TRUTH: (that no one's talking about) 5+ years of night shifts revealed: → Why most digital health solutions fail → What tech companies get wrong → The pattern that changes everything LEAKED STATISTICS: Managing 500+ patients showed: • 73% of crises were predictable • 82% needed better data integration • 91% could've been prevented THE CONTROVERSIAL TAKE: Most health tech companies are building: ❌ Complex AI solutions ❌ Fancy automation tools ❌ Expensive platforms But they're missing: ✅ Front-line insights ✅ Patient reality ✅ Clinical workflow understanding THE TRANSFORMATION: 2017: Managing hospital nights 2022: Leading digital innovation 2024: Building healthcare's future What changed? [The framework that's disrupting healthcare] EXPOSED: The night shift pattern that reveals: 1. Why patients really suffer 2. What data actually matters 3. How to truly transform care 🧵 BREAKING IT DOWN: Digital Health MS @Bournemouth taught me tech But Emergency Care taught me truth The missing piece? [Continuing in comments...] CONTROVERSIAL OPINION: The future of healthcare won't be built in: ❌ Silicon Valley offices ❌ Corporate boardrooms ❌ Innovation labs It will be built by those who: ✅ Handled real emergencies ✅ Saw actual patients ✅ Lived healthcare reality 🎯 Currently exploring opportunities with organizations who understand: → Real healthcare challenges → Patient-first innovation → Data-driven transformation → Clinical workflow optimization DM open for serious conversations about healthcare's future. #HealthTech #Innovation #DigitalHealth #Healthcare

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Unlock the Power of AI in Radiology with Teleradyx!! Teleradyx is revolutionizing the field of radiology in the US with our comprehensive AI annotation reports. Our team of expert radiologists and AI specialists provide accurate and efficient annotation services for: - _Tumor segmentation_ - _Organ segmentation_ - _Lesion detection_ - _Image enhancement_ - _Data labeling_ Our AI annotation reports enable: - _Improved diagnosis accuracy_ - _Enhanced patient outcomes_ - _Streamlined clinical workflows_ - _Accelerated research and development_ At Teleradyx, we offer: - _High-quality annotation services_ - _Rapid turnaround times_ - _Customized solutions_ - _Secure and HIPAA-compliant data handling_ _Partner with us to unlock the full potential of AI in radiology and transform patient care._ for Contact: 📩[email protected] or 📲+919058386806. #Teleradyx #AIinRadiology #AnnotationReports #Teleradiology #RadiologySolutions #USHealthcare #MedicalImaging #ArtificialIntelligence #HealthcareInnovation

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