The Jaide Health platform provides AI-assisted language support for routine verbal exchanges and written translations commonly used throughout the healthcare process. These include intake-related communications, discharge information, and other administrative interactions where language barriers can create delays for patients and healthcare staff. According to AMN, human interpreters will continue to be used when conversations require greater clinical accuracy, empathy, and patient-safety considerations. The acquisition is intended to address communication gaps that often arise outside physician consultations and acute-care settings.

“This is an important strategic move in AMN’s ongoing mission to improve access to care for all,” said Cary Grace, President and CEO of AMN Healthcare. “By expanding language support across more moments in the healthcare journey, we can help health systems deliver a more seamless experience for patients and care teams while continuing to rely on the critical expertise of our qualified interpreters when it matters most.”

The Jaide Health solution is already in use with clients operating across multiple healthcare environments, where it has been applied to patient communications and workflow support. AMN stated that the technology has demonstrated value in real-world healthcare settings and will now become part of its broader language services offering. As part of the transaction, the Jaide Health team will join AMN Healthcare.

“We believe we’ve built one of the strongest solutions in the market, and joining AMN Language Services lets us reach more patients through AMN’s scale and clinical-quality standards,” said Joe Corkery, MD, CEO and co-founder of Jaide Health. “AMN was our first choice because of our shared commitment to quality. Together, we can pair smart AI assistance with the high standards of AMN’s human interpreting to provide LEP patients with a voice outside of clinical encounters, which we know leads to better outcomes and experiences.”

Financial terms of the deal were not disclosed. The AMN Healthcare Acquires Jaide Health transaction expands language support capabilities across the patient journey, while the AMN Healthcare Acquires Jaide Health announcement also reinforces the continued importance of human interpreters in healthcare communications.

The Argos system operates through a patient’s existing arterial line and uses a single reusable cable to connect with a radial blood pressure transducer. According to the companies, the monitor requires no calibration and features a multi-touch screen interface that can be operational within minutes. Training can be completed in less than five minutes, while the system eliminates the need for expensive disposable accessories. The expansion follows Medtronic’s continued efforts to enhance its Acute Care & Monitoring portfolio through additional patient-monitoring technologies.

A key feature of the Argos platform is its Multi-Beat Analysis (MBA) algorithm, developed by researchers at the Massachusetts Institute of Technology (MIT) and Michigan State University. Rather than evaluating one heartbeat at a time, MBA analyzes multiple heartbeats from the blood pressure signal, enabling direct modelling of a patient’s vascular resistance. Medtronic states that the system delivers accurate hemodynamic information across 10 parameters and maintains performance during variations in vasomotor tone, low cardiac output conditions and arrhythmias.

Commenting on the expansion, Marc DeMartini, Western Europe commercial VP of the ACM business at Medtronic, said: “Our focus is on helping clinicians navigate complexity with greater clarity. The Argos cardiac output monitor adds meaningful haemodynamic insight to our Acute Care & Monitoring portfolio and complements established technologies such as INVOS cerebral oximetry, supporting a more comprehensive view of patient status across perioperative and critical care environments. By bringing this technology to Western Europe, we are reinforcing our commitment to partner with healthcare systems as they work to deliver high-quality care in an increasingly resource-constrained environment.”

Marc Zemel, CEO of Retia Medical, added: “Medtronic is an ideal partner for Retia Medical as we expand access to the Argos cardiac output monitor in Western Europe. With a robust portfolio, deep customer relationships, and leadership in advancing acute care and monitoring technologies, Medtronic is uniquely positioned to help bring the benefits of our innovative solution to clinicians and patients across Western Europe. We look forward to working together to help to set a new standard in hemodynamic monitoring.” The Medtronic Distribution Deal marks the latest step in expanding the availability of the Argos platform in the region.

The updated LEAF Platform features a redesigned wearable sensor that is smaller, more comfortable, and easier for patients to use at home. The system enables care teams to remotely monitor patient progress by collecting data on physical activity and rehabilitation adherence during the recovery period. The platform is intended to give clinicians meaningful, real-time visibility into how patients are recovering after procedures such as total knee and total hip replacements.

According to Smith+Nephew, the next-generation system includes improvements in sensor design and connectivity, making it more practical for widespread clinical use. The company indicated that the LEAF Platform is part of its broader digital and robotics strategy, which is focused on delivering connected care solutions that bridge the gap between surgical procedures and long-term patient outcomes. Remote patient monitoring through wearable sensor technology has increasingly become a priority for healthcare providers seeking to manage patient recovery more efficiently while reducing unnecessary clinical visits.

Smith+Nephew stated that the LEAF Platform launch aligns with growing demand among healthcare systems for scalable digital tools that extend the reach of clinical care teams. The platform is designed to integrate into existing care workflows, allowing providers to act on recovery data without disrupting established protocols. With the next-generation LEAF Platform now available, Smith+Nephew reinforces its position in the expanding remote patient monitoring market, where wearable sensor adoption continues to gain traction across orthopaedic and rehabilitation settings.

The integrated solution brings together real-time MRI capabilities with MR-conditional interventional tools and structured clinical workflows. It builds on a partnership formalised in September 2025, when the two companies aligned their expertise—pairing Siemens Healthineers’ imaging technologies with Cook Medical’s procedural specialisation. The system incorporates devices specifically developed for MRI environments alongside the Magnetom Free.XL platform, creating a unified framework for interventional imaging and treatment delivery.

Within the suite, multiple components are integrated to streamline clinical use and expand procedural capabilities:

• Advanced imaging technology designed for real-time guidance during interventions
• Purpose-built interventional devices tailored for MRI compatibility
• Suite planning support and clinical education resources
• Integration with SIR VIRTEX, a clinical data registry and analytics platform
• Continuous data feedback to enhance procedural learning and outcomes

The companies state that this MRI Suite launch enables physicians to perform procedures that benefit from enhanced soft-tissue visibility while avoiding radiation exposure. Applications include oncology and soft-tissue interventions, with use cases spanning biopsies, ablations, and procedures in pediatric and cardiac care. According to Peter Polverini III, VP of Cook Medical’s iMRI division, “The iMRI Suite is more than a technology; it’s a fundamental shift in how we approach intervention. By bringing together advanced imaging, purpose-built devices, and integrated workflows, we are enabling physicians to see more, treat with greater precision, and ultimately deliver better outcomes without exposing patients or care teams to radiation.”

Pete Yonkman, president of Cook Medical and Cook Group, added: “MRI offers unique advantages for image-guided intervention, particularly for procedures involving soft tissue. Through our collaboration with Siemens Healthineers and leading clinicians, we are working to advance the development of radiation-free interventional approaches.” Andreas Schneck, head of Magnetic Resonance at Siemens Healthineers, said: “At Siemens Healthineers, it is our goal to elevate health globally. Magnetom Free.XL is designed to unlock the full potential of MR in the interventional suite, expanding the imaging toolbox by matching the right modality to the right patient at the right time.”

At the operational level, the BD® Pyxis™ Pro Dispensing Solution is engineered to improve how medications are stored, accessed, and managed within hospital environments. Its modular, stackable design allows for increased storage capacity within the same physical footprint, accommodating both refrigerated and ambient medications. This approach supports healthcare systems in adapting to shifting patient needs while maintaining consistent medication availability. Enhanced security features such as RFID badge scanning, wireless barcode scanners, and illuminated bins aim to strengthen controlled substance management and simplify medication retrieval processes. In this context, the AI medication dispensing system is positioned as a tool to reduce inefficiencies and disruptions across clinical workflows.

The expansion also includes plans to extend the AI-enabled BD Incada™ Analytics platform already established in the United States to European hospitals and health systems next year. Built on Amazon Web Services’ (AWS) on-demand cloud computing infrastructure, the BD Incada™ Platform integrates advanced AI capabilities, including natural language search in analytics. The system is designed to scale alongside the data generated by nearly three million connected BD devices, offering clinicians enterprise-wide visibility into medication inventory through customizable dashboards. These capabilities support pattern identification, improved medication availability, reduced waste, and enhanced labor efficiency.

To address regional requirements, BD will utilize the AWS European Sovereign Cloud, enabling EU healthcare systems to meet digital sovereignty standards while maintaining performance, security, and scalability. “BD’s innovations in medication management are setting a new standard for unified, data-driven healthcare operations,” said Esteban Rossi, vice president and general manager for Medication Management Solutions, EMEA at BD. “Delivering the BD® Pyxis™ Pro Dispensing Solution and BD® Incada™ Platform directly to European hospitals empowers our customers to strengthen medication availability, improve efficiency and enhance patient care.” The Pyxis™ Pro Dispensing Solution is expected to be deployed across Europe in the coming months, with support for 15 languages.

At the heart of smart manufacturing transforming medtech production is the data-driven approach. In a traditional manufacturing environment, data was often siloed, and problems were often only identified after a batch of products had already been completed. In a smart factory, every machine, sensor, and tool is connected to a central digital nervous system. This allows for real-time monitoring of the entire production process, from the temperature of a cleanroom to the precise force applied by a robotic assembly arm. This level of visibility is the essence of industry 4.0 healthcare, as it enables a proactive, predictive model where issues are identified and resolved before they ever lead to a defective product. This not only reduces waste and lowers costs but also significantly enhances the safety and reliability of the medical devices that reach the patient.

The Power of Digital Twins in MedTech Production

A cornerstone of smart manufacturing transforming medtech production is the use of digital twins. A digital twin is a virtual replica of a physical asset, whether it is a single machine, a production line, or an entire manufacturing facility. By creating these virtual models, medtech companies can simulate and optimize their production processes in a risk-free digital environment. For example, before a new surgical instrument goes into production, engineers can use a digital twin to test how different materials or manufacturing methods will affect its final quality and performance. This capability is a game-changer for digital twins production, as it drastically reduces the time and cost associated with prototyping and scaling up new innovations.

Furthermore, digital twins allow for a level of flexibility that is essential in the modern medtech landscape. As the industry moves toward more personalized and patient-specific devices, the ability to rapidly reconfigure a production line is a critical advantage. In a smart factory, a digital twin can be used to plan a seamless transition from one product variant to another, ensuring that the physical machines are updated with minimal downtime. This is particularly vital for the production of custom orthopedic implants or patient-specific surgical guides, where every unit is unique. By leveraging the power of smart manufacturing transforming medtech production, companies can now produce batches of one with the same efficiency and quality as mass-produced goods.

AI-Driven Quality Control and Predictive Maintenance

One of the most transformative aspects of smart manufacturing transforming medtech production is the integration of artificial intelligence into the quality control process. In traditional manufacturing, quality control often relies on manual inspections or statistical sampling, which can miss subtle defects. In contrast, an AI-driven system can use high-speed cameras and advanced image recognition to inspect every single unit on a production line in real-time. These AI systems can detect microscopic cracks, surface imperfections, or dimensional deviations that would be invisible to the human eye. This level of AI manufacturing healthcare is setting a new standard for precision and safety in the industry, ensuring that every device that leaves the factory is perfect.

Beyond quality control, AI is also revolutionizing the maintenance of manufacturing equipment. Predictive maintenance uses machine learning algorithms to analyze data from sensors on a machine to predict when it is likely to fail. This allows the manufacturer to perform maintenance during a planned shutdown, rather than waiting for a catastrophic failure that could halt production for days. For a medtech company, this reliability is essential, as even a short disruption in the supply of critical devices like heart valves or insulin pumps can have serious consequences for patient health. By integrating smart manufacturing transforming medtech production into their operations, companies are building a more resilient and dependable production ecosystem.

Automated Medical Manufacturing and Collaborative Robotics

The physical manifestation of smart manufacturing transforming medtech production is the rise of automated medical manufacturing. We are seeing a new generation of cobots, or collaborative robots, that are designed to work safely alongside human operators. Unlike traditional industrial robots that are often caged for safety, cobots use advanced sensors to detect human presence and can be easily programmed to assist with delicate tasks like the assembly of micro-fluidic devices or the packaging of sterile instruments. This human-robot collaboration is a hallmark of industry 4.0 healthcare, as it combines the dexterity and problem-solving skills of a human with the precision and tireless endurance of a machine.

The automation of the manufacturing process also extends to the smart logistics within the factory. Autonomous mobile robots (AMRs) can navigate a facility to deliver raw materials to a production line or move finished goods to a warehouse. This reduces the need for manual material handling and ensures that the production process flows smoothly and efficiently. This holistic approach to smart manufacturing transforming medtech production creates a seamless environment where every movement is optimized for maximum value. This efficiency is particularly important in a global market where medtech companies are facing increasing pressure to lower costs while maintaining the highest standards of quality and innovation.

Sustainability and the Future of Smart MedTech

As we look toward the future, smart manufacturing transforming medtech production will also play a key role in making the industry more sustainable. By optimizing energy use, reducing material waste, and improving the efficiency of the supply chain, smart factories can significantly lower their environmental footprint. This is becoming a major priority for both manufacturers and healthcare providers, as the global community works toward a greener healthcare system. Furthermore, the ability to produce devices closer to the point of care through localized, smart manufacturing hubs will reduce the carbon emissions associated with long-distance shipping.

The ultimate goal of smart manufacturing transforming medtech production is to create a more responsive and patient-centric healthcare system. We are moving toward a world where a patient’s unique anatomical data can be sent directly from a hospital to a smart factory, where a custom device is designed, manufactured, and shipped within 24 hours. This level of speed and personalization will revolutionize the treatment of complex conditions, from rare genetic disorders to traumatic injuries. By continuing to invest in the technologies of Industry 4.0, the medtech industry is not just changing how it makes things it is changing what is possible for the human body. The transformation is already underway, and the result will be a healthier, more precise, and more resilient world for everyone.

The Photonova Spectra platform is engineered to deliver broad coverage alongside ultra-high definition (UHD) spatial and spectral imaging. According to GE HealthCare, the system enables faster acquisition speeds and supports detailed visualization of subtle tissue variations, small lesions and vascular structures. Unlike conventional CT systems that convert X-rays into light before measurement, photon-counting CT directly detects individual X-ray photons and measures their energy. This approach allows for improved spatial and spectral resolution, as well as enhanced tissue characterization. The company also highlighted that its Deep Silicon detector material strengthens spectral imaging performance, particularly in lesion characterization and treatment monitoring. GE HealthCare submitted Photonova Spectra for FDA clearance in November 2025, incorporating advanced AI applications into the platform.

As clinicians across the United States face rising volumes and increasing diagnostic complexity, technology must do more than capture images it must simplify decision-making and strengthen performance across the enterprise, said Catherine Estrampes, President & CEO, U.S. and Canada, GE HealthCare. Photonova Spectra is designed to deliver rich clinical insights in every scan and help alleviate cognitive burden for care teams. With the U.S. 510(k) clearance, we are proud to now bring this innovation to U.S. healthcare systems and the patients they serve.

Further technical capabilities of Photonova Spectra include 8-bin energy resolution enabled by Deep Silicon, supporting advanced material separation and characterization. This allows clinicians to distinguish materials such as iodine, calcium and fat with greater clarity. The system’s wide detector coverage and rapid rotation speed of 0.23 seconds contribute to fast acquisition and motion-free imaging. Additionally, Photonova Spectra captures both 8-bin spectral and ultra-high definition spatial data simultaneously without requiring specialized protocols, ensuring spectral data is available in every exam.

GE HealthCare noted that the system has applications across neurology, oncology, musculoskeletal imaging, thoracic imaging and cardiology. It supports visualization of fine brain structures, characterization of lesions, detection of small fractures and bone marrow edema, and advanced cardiac and chest imaging. The platform also leverages Nvidia computing technology, enabling it to process up to 50 times more data than conventional CT systems. Ongoing collaborations with UW-Madison and Stanford Medicine are focused on exploring new clinical applications and imaging protocols. With regulatory approval in place, GE HealthCare is now preparing for commercial availability of Photonova Spectra in the U.S.

Photonova Spectra reflects years of intentional design and close collaboration with clinicians, researchers and collaborators across the globe, adds Jean-Luc Procaccini, president & CEO, Molecular Imaging and Computed Tomography, GE HealthCare. From the earliest stages to today, we remain focused on building a system that addresses the practical realities of clinical practice while opening pathways for scientific advancement. The result is a photon-counting platform engineered for the needs of today’s care teams, as well as the imaging challenges and research opportunities that will shape the future of CT.

At the core of the platform is its ability to generate a patient-specific, simulation-ready digital replica of the lungs. By embedding directly into CT imaging workflows, the system uses deep learning models to reconstruct a detailed 3D digital twin, offering clinicians an interactive view of anatomical structures such as airways, blood vessels, lung lobes, and lesions. This AI Lung Digital Twin Platform enables practitioners to simulate bronchoscopy and biopsy pathways, facilitating improved procedural planning within an immersive digital environment.

The platform is built on NVIDIA Physical AI infrastructure, incorporating NVIDIA Omniverse and OpenUSD for interactive visualization, NVIDIA TensorRT for optimized AI inference, and NVIDIA MONAI for advanced image segmentation. These components collectively support automated identification of critical lung structures, volumetric analysis, and navigation path planning. By transforming static CT scans into dynamic models, the system allows clinicians to better assess anatomical relationships, reduce pre-operative planning time, and improve procedural safety across complex interventions.

“By combining LTTS’ engineering expertise in medical imaging and digital health platforms with the power of NVIDIA’s Physical AI infrastructure, we are enabling a new generation of AI-powered biological digital twins for precision medicine,” observed Amit Chadha, CEO & Managing Director, L&T Technology Services. “These platforms can transform how clinicians visualize lung anatomy, plan interventions and deliver precision care. The impact will be visible across the global healthcare ecosystem in the years ahead.”

David Niewolny, Head of Business Development for Healthcare and Medical Technology, NVIDIA, said, “Digital twins are emerging as a powerful new tool for precision medicine. By leveraging NVIDIA Physical AI infrastructure, Omniverse, MONAI and TensorRT, LTTS is transforming CT data into interactive lung digital twins that allow clinicians to visualize anatomy in 3D, simulate procedures and plan clinical interventions with greater confidence.”

Rising global cases of respiratory diseases, including lung cancer and COPD, are accelerating the adoption of AI-driven digital twin technologies. These innovations are expected to shift clinical workflows away from conventional imaging interpretation toward predictive, simulation-led, and minimally invasive intervention planning, supporting more personalized and data-driven treatment strategies.

Under the agreement, Daiichi will obtain exclusive rights to the tool, known as lipodia, representing what could become the company’s first step in extending its cardiovascular portfolio into the digital health sector. The initial rollout of the partnership will focus on the German healthcare market, although the company intends to expand lipodia’s reach to “all major markets on the continent.” The digital solution works by integrating patient-specific, evidence-based behavioural health and psychotherapeutic strategies that guide users toward long-term lifestyle adjustments. Designed to complement pharmaceutical therapy, the system aims to encourage sustained behavioural change while helping reduce a patient’s risk of cardiovascular disease (CVD).

“Digital therapeutics represent an important next step in delivering holistic heart health,” said Oliver Appelhans, Daiichi’s head of EU speciality business. “By combining pharmaceuticals with evidence-based digital therapeutics, we can support patients beyond our medicines.” To support wider access to the therapy, GAIA intends to submit a reimbursement application for lipodia once results from its pivotal Phase III trial become available. Should the application receive approval, Germany’s public health insurers would reimburse the therapy through the country’s Digital Health Applications (DiGA) pathway.

The move reflects a broader trend in the pharmaceutical industry as companies explore how digital technologies can complement drug therapies. Although medications used to treat CVD have significantly improved outcomes, pharmacological treatments alone often do not address the behavioural changes needed for long-term prevention. Estimates suggest that around 80% of heart disease and stroke cases affecting European patients are preventable, highlighting the potential impact of early interventions and educational programmes designed to encourage sustained lifestyle changes. As a result, several pharmaceutical companies are evaluating ways to combine digital health tools and patient education platforms with existing therapies.

Activity in the cardiometabolic health segment illustrates this shift. Novo Nordisk has been exploring collaborations with digital health providers that could offer fitness and dietary guidance alongside treatment with its weight-loss medicine Wegovy (semaglutide). Meanwhile, Otsuka Pharmaceutical currently holds 16% of global revenue in regulator-approved digital health apps. Part of this position is supported by Rejoyn, an application developed with Click Therapeutics and launched in 2024 for patients with depression. The app works alongside the company’s pharmaceutical treatments for major depressive disorder (MDD), including Rexulti (brexpiprazole) and Abilify (aripiprazole).

According to recent analysis from GlobalData, regulator-approved applications are playing a central role in driving growth across the digital health segment, which remains “still in its early stages.” Regulators are also moving to facilitate wider adoption of these technologies. Both the US Food and Drug Administration (FDA) and the UK’s Medicines and Healthcare products Regulatory Authority (MHRA) have introduced policies aimed at encouraging the broader use of digital health tools throughout healthcare systems.

Through the integration, physicians will be able to use natural language queries to search for and retrieve up-to-date clinical data. According to the organizations, the system is built to support quality and safety standards while streamlining how doctors access relevant medical information during patient encounters.

Laura Wilt, Sutter Health’s chief digital officer, said the collaboration reflects a shared ambition to strengthen clinical support and reshape care delivery. She described the effort as part of a broader transformation agenda. “It’s how we’re transforming the way we serve patients, support care teams and improve outcomes,” she said. Wilt added that the organizations are aligned in their commitment to “reimagining healthcare for the better.”

The deployment builds on Sutter Health’s earlier investments in generative AI. Two years ago, the California health system began using generative AI tools with the goal of reducing clinician burnout and enhancing organizational sustainability. At that time, Dr. Albert Chan, Sutter Health’s chief health information officer, said in a statement that the generative AI platform enabled providers to “recharge.”

OpenEvidence, for its part, said the collaboration is intended to move the needle on healthcare sustainability and medical AI safety. Dr. Travis Zack, OpenEvidence’s chief medical officer, indicated that working with Sutter Health advances those objectives.

Clinical decision support has long been associated with improved patient outcomes and more efficient resource utilization. More recently, scientific research has examined whether emerging generative AI technologies can further strengthen performance. Last year, researchers at Mass General Brigham evaluated a hybrid strategy over the course of a yearlong study.

The team compared two large language models (LLMs) – OpenAI’s GPT-4 and Google’s Gemini 1.5 – against the health system’s diagnostic decision support system, DXplain. Findings showed that the established, homegrown platform surpassed the LLMs in diagnostic accuracy for patient cases. However, researchers concluded that combining AI capabilities with traditional decision support systems could yield stronger results.

In their report, the MGB researchers detailed how pairing DXplain with an LLM could enhance the clinical efficacy of both systems. “A hybrid approach that combines the parsing and expository linguistic capabilities of LLMs with the deterministic and explanatory capabilities of traditional DDSSs may produce synergistic benefits,” they said.

Sutter Health executives framed the OpenEvidence integration as part of a broader digital strategy. “Digital innovation plays a central role in our work to build a more connected, proactive and sustainable healthcare system,” Wilt said in the announcement. Dr. Ashley Beecy, Sutter Health’s chief AI officer, underscored the patient impact, stating, “Patients benefit when providers have the most current and relevant evidence incorporated into clinical decision-making,” she added.