This week’s Artificial Intelligence and Digital Health update highlights regulatory clearances, platform partnerships, imaging AI advances, cardiovascular tools, and expanding clinical evidence across care delivery, diagnostics, and research infrastructure.
In Today’s Newsletter
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🖼️ RadNet buys Gleamer to expand radiology AI [1] [EU • 04 Mar 2026]
Context: RadNet plans to merge Gleamer with DeepHealth, its AI imaging subsidiary, adding products in cancer, MS lesions, fractures, chest imaging, and lung CT.
Key point: RadNet agreed to pay €215 million upfront, plus up to €15 million in milestones, to acquire Gleamer and broaden its radiology AI footprint in Europe and beyond.
Implication: Signals pipeline investment and modality expansion.
🧪 LG CNS pushes AI deeper into pharma and digital health [2] [South Korea • 05 Mar 2026]
https://www.chosun.com/english/industry-en/2026/03/05/VWGQD3VYUJARVNEQVREM75OJ6E/
Context: LG CNS cited work on an AI-based clinical trial design platform, federated learning for sensitive data, and APQR automation with Chong Kun Dang.
Key point: LG CNS said it invested 10 billion won in CHA Biotech and is building AI infrastructure across drug development, quality operations, and connected healthcare.
Implication: Access programs may expand screening, initiation, and follow-up at scale.
🇩🇰 Denmark showcases digital health vendors in Scotland [3] [UK • 05 Mar 2026]
Context: The delegation includes Digirehab, Pontem Data Group, Cortrium, Radiobotics, and Netcompany, positioned around NHS Scotland priorities.
Key point: Denmark is using the FutureScot event to promote cross-border digital health collaboration and vendor engagement with Scottish stakeholders.
Implication: Signals pipeline investment and modality expansion.
🌾 Sanford Health expands AI and virtual care in rural delivery [4] [US • 06 Mar 2026]
Context: Sanford Health described a virtual care center, clinician training for digital care, and use of agentic tools for scheduling and workflow support.
Key point: Sanford said virtual care now spans 80 specialties and reported $40 million in patient travel-cost savings last year, with AI embedded across its strategy.
Implication: Could streamline initiation and adherence via remote prescribing and logistics.
👕 Wearable AI T-shirt flagged as emerging heart-risk tool [5] [06 Mar 2026]
Context: The article attributes the underlying report to Fox News and describes an AI-enabled garment for continuous biometric monitoring outside clinic settings.
Key point: The source describes an AI-powered T-shirt designed to analyze cardiac-related biometric signals and flag hidden heart risks (clinical validation not specified in the source summary).
Implication: Could inform practice and payer discussions, interpretation depends on study design and confounding control.
🫀 Eko reports NHS gains for AI-enabled stethoscopes [6] [UK • 06 Mar 2026]
Context: TRICORDER involved 205 NHS general practices, 1.5 million patients, and nearly 1,000 primary care clinicians, according to Eko.
Key point: Eko said AI-assisted stethoscope exams increased detection of heart failure, atrial fibrillation, and valvular heart disease versus standard practice over 12 months.
Implication: May influence prescriber choice and payer reviews pending full data.
✅ eMurmur wins FDA clearance for murmur-detection AI [7] [US • 06 Mar 2026]
https://www.mpo-mag.com/breaking-news/fda-clears-ai-powered-heart-murmur-detection-software/
Context: The software is described as open-platform and accessible either through standalone software or API integration into third-party systems.
Key point: FDA cleared eMurmur Heart AI to identify primary heart sounds and detect the presence and absence of abnormal heart murmurs from digital stethoscope recordings.
Implication: Could streamline initiation and adherence via remote prescribing and logistics.
💊 GAIA and Daiichi Sankyo Europe partner on cardiovascular DTx [8] [EU • 06 Mar 2026]
Context: The partnership centers on lipodia, a digital therapeutic for adults with hypercholesterolemia, initially in Germany.
Key point: GAIA granted Daiichi Sankyo Europe exclusive commercialization rights for lipodia in Germany, with possible expansion to other European markets.
Implication: Signals pipeline investment and modality expansion.
🧲 Philips gets FDA nod for SmartHeart cardiac MR planning [9] [US • 06 Mar 2026]
Context: Philips said SmartHeart automates 14 standard and advanced cardiac MR views in under 30 seconds and was trained on more than 1,200 datasets.
Key point: FDA cleared Philips SmartHeart, an AI-powered cardiac MR planning workflow tool intended to reduce operator burden and support consistent imaging.
Implication: May influence prescriber choice and payer reviews pending full data.
🎗️ iMerit, Segmed, and Advocate Health release open breast AI dataset [10] [US • 07 Mar 2026]
Context: The dataset includes 3D mammography studies from 558 female patients, with biopsy-confirmed outcomes and annotations reviewed by U.S. board-certified specialists.
Key point: iMerit, Segmed, and Advocate Health released an open-source annotated breast tomosynthesis dataset to support AI-based breast cancer research.
Implication: Could inform practice and payer discussions, interpretation depends on study design and confounding control.
🔊 HKU unveils AI-powered ultrasound MetaLens [11] [Hong Kong • 05 Mar 2026]
https://www.miragenews.com/hku-unveils-ai-metalens-to-revolutionize-1631453/
Context: HKU’s “SonoMeta” is positioned as a probe-mounted accessory intended to improve ultrasound penetration through rib structures in thoracic imaging.
Key point: HKU researchers said their AI-powered MetaLens improved ultrasound visualization through the ribcage in principle validation, simulation modeling, and preclinical experiments.
Implication: May influence prescriber choice and payer reviews pending full data.
🧬 AI links CCDC3 pathway to colorectal cancer liver metastasis [12] [07 Mar 2026]
https://www.nature.com/articles/s41746-026-02457-0
Context: The npj Digital Medicine study integrated single-cell RNA sequencing, WGCNA, NMF, and AI-based bio-knowledge graph analysis with experimental validation.
Key point: Researchers identified a CCDC3/CXCR3/STAT3/CDT1 axis associated with chromosomal instability and metastatic progression in colorectal cancer liver metastases.
Implication: May influence prescriber choice and payer reviews pending full data.
🧬 RCT-Twin-GAN models how trial effects may translate to real-world populations [13] [07 Mar 2026]
https://www.nature.com/articles/s41746-026-02464-1
Context: The study used SPRINT and ACCORD Blood Pressure Trial data plus EHR cohorts to generate digital twins conditioned on different patient populations.
Key point: Researchers reported that RCT-Twin-GAN reproduced divergent treatment effects across trial populations and simulated how results may shift in real-world cohorts.
Implication: Could inform practice and payer discussions, interpretation depends on study design and confounding control.
💬 AI chatbot linked to stronger HIV PrEP initiation and persistence [14] [US • 07 Mar 2026]
https://www.nature.com/articles/s41746-026-02519-3
Context: This retrospective cohort study evaluated an AI chatbot used for PrEP support across AIDS Healthcare Foundation clinics in the United States.
Key point: Chatbot engagement was associated with higher PrEP initiation, follow-up attendance, and appointment adherence among eligible adults.
Implication: Access programs may expand screening, initiation, and follow-up at scale.
💷 Diagnostic AI buyers prefer transparent hybrid pricing [15] [Germany • 06 Mar 2026]
https://www.nature.com/articles/s41746-026-02501-z
Context: The study interviewed 17 healthcare decision makers across hospital, outpatient, laboratory, and industry settings.
Key point: Participants favored transparent, predictable pricing for diagnostic AI, often combining a base fee with clinically legible variable components.
Implication: Could inform practice and payer discussions, interpretation depends on study design and confounding control.
🧠 MedVersa shows generalist imaging AI performance in NEJM AI [16] [05 Mar 2026]
https://ai.nejm.org/doi/full/10.1056/AIoa2500595
Context: MedVersa was trained on large multimodal imaging datasets and evaluated across report generation, segmentation, detection, and VQA tasks.
Key point: The study reported that a single generalist multimodal model matched or exceeded specialist systems across several imaging tasks and improved radiologist workflow measures.
Implication: May influence prescriber choice and payer reviews pending full data.
🚪 ESSENCE studies AI symptom assessment in a digital front door [17] [Portugal • 05 Mar 2026]
https://ai.nejm.org/doi/full/10.1056/AIoa2500833
Context: The real-world quality-improvement study was embedded in Portugal’s CUF private healthcare network and tracked intent, behavior, and appropriateness of care.
Key point: The Ada Health integration was associated with reduced uncertainty, shifts toward primary care, and more appropriate observed care use in the evaluated cohort.
Implication: Could inform practice and payer discussions, interpretation depends on study design and confounding control.
🔬 PanCAM improves lymph node metastasis detection across cancers [18] [China • 05 Mar 2026]
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00143-8/fulltext
Context: The Lancet Digital Health study covered 9,256 patients, 69,502 whole-slide images, 33 cancer types, 17 hospitals, and prospective validation.
Key point: PanCAM showed high sensitivity for detecting lymph node metastasis across common and rare cancers and identified additional positive patients missed by pathologists.
Implication: May influence prescriber choice and payer reviews pending full data.
🎯 BRAIx turns mammography AI into a 4-year breast cancer risk score [19] [Australia/Sweden • 03 Mar 2026]
https://www.thelancet.com/journals/landig/article/PIIS2589-7500(26)00010-5/fulltext
Context: The population cohort study used BreastScreen Victoria data and external validation from Karolinska University Hospital.
Key point: BRAIx risk score predicted both current breast cancer detection and intermediate-term risk after an all-clear screen, with a high-risk upper tail.
Implication: Could inform practice and payer discussions, interpretation depends on study design and confounding control.
🧪 Merck and Mayo Clinic launch AI precision-medicine lab [20] [US • 04 Mar 2026]
https://www.2minutemedicine.com/merck-and-mayo-clinic-launch-ai-driven-precision-medicine-lab/
Context: The collaboration uses Mayo Clinic Platform Orchestrate and de-identified multimodal clinical data, including genomic and longitudinal records.
Key point: Merck and Mayo Clinic launched a strategic AI collaboration aimed at target identification and virtual-cell approaches for complex disease drug discovery.
Implication: Signals pipeline investment and modality expansion.
📄 Evinova signs AI clinical-trial deals with Astellas, BMS, and AstraZeneca [21] [03 Mar 2026]
Context: The deals cover AI use in study design optimization and document management, with shared operational data feeding benchmark development.
Key point: Evinova signed separate agreements with Astellas, Bristol Myers Squibb, and AstraZeneca to deploy its AI-native clinical development platform.
Implication: Signals pipeline investment and modality expansion.
🧬 Evo 2 opens a large genome model across domains of life [22] [04 Mar 2026]
Context: Evo 2 was described as an open-source large genome model trained on trillions of bases from bacteria, archaea, and eukaryotes.
Key point: The model reportedly learned features such as coding regions, splice sites, and regulatory elements, and was released with parameters, code, and training data.
Implication: Signals pipeline investment and modality expansion.
🌐 Google and Taiwan plan nationwide AI health network [23] [Taiwan • 05 Mar 2026]
https://www.digitimes.com/news/a20260305PD212/google-taiwan-google-taiwan-nhia-healthcare.html
Context: The DIGITIMES item is paywalled and offers limited public detail beyond the collaboration framing.
Key point: Google announced a nationwide collaboration with Taiwan’s Ministry of Health and Welfare to build what it described as a countrywide AI health network.
Implication: Signals pipeline investment and modality expansion.
Why it matters
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This week’s mix showed healthcare AI maturing across three layers at once, workflow tools, commercialization infrastructure, and higher-order clinical evidence [1][6][16][18].
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Cardiovascular care remains one of the most active deployment areas, with AI now touching screening, auscultation, imaging, wearables, and virtual access models [4][5][6][7][8][9].
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Health systems and pharma are converging around data platforms and operational AI, from Mayo–Merck and Evinova to LG CNS and national infrastructure efforts in Taiwan [2][20][21][23].
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Research momentum is broadening from narrow performance studies into transportability, risk prediction, prevention workflows, and pathology sensitivity at scale [13][14][17][18][19].
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Several items still require caution because they rely on company statements, event previews, or summaries without full endpoints, peer-reviewed validation, or reimbursement detail [3][5][8][21][23].
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FAQ
What does RadNet’s acquisition of Gleamer mean for the radiology AI market?
RadNet’s acquisition of Gleamer signals continued consolidation in radiology AI, where competitive advantage is shifting from single-point algorithms to broader imaging platforms. By adding Gleamer’s capabilities to DeepHealth, RadNet expands its reach across multiple use cases and strengthens its position in integrated, scalable clinical AI. For pharma, medtech, and investors, the deal matters because value is increasingly concentrating in platforms that combine modality breadth, workflow integration, and deployable clinical utility.
What is LG CNS building in pharma and digital health?
LG CNS is building AI infrastructure across trial design, quality operations, and connected healthcare, pointing to a deeper enterprise role for technology partners in life sciences. Strategically, this matters because AI adoption is moving beyond pilots and into operational layers that can shape how pharma develops, validates, and manages products. For pharma leaders, it signals that infrastructure providers may become increasingly important in enabling scalable transformation across R&D and commercial healthcare ecosystems.
What is Denmark showcasing in Scotland through FutureScot?
Denmark is showcasing a coordinated group of digital health vendors in Scotland, reflecting a market-entry strategy built around ecosystem credibility rather than single-product promotion. Strategically, this matters because cross-border healthcare innovation is often accelerated when vendors are positioned as part of a trusted national cluster. For digital health companies and investors, it highlights how public-private alignment can support international expansion and procurement relevance.
What is Sanford Health doing with AI and virtual care?
Sanford Health is scaling AI and virtual care across rural delivery, using technology to support scheduling, workflows, and specialty access at system level. Strategically, this matters because health systems are increasingly adopting AI where it solves workforce pressure, access gaps, and cost inefficiencies rather than where it offers novelty alone. For healthcare operators, Sanford provides a strong example of AI being tied to measurable delivery-model redesign.
What is the AI wearable T-shirt designed to detect?
The AI wearable T-shirt is designed to monitor cardiac-related biometric signals and flag hidden heart risks in a continuous, real-world setting. Strategically, this matters because cardiovascular monitoring is moving beyond episodic clinic-based assessment toward lower-friction, always-on detection models. For digital health players, the opportunity is significant, but long-term value will depend on validation, clinical credibility, and integration into care pathways.
What did Eko report about its AI-enabled stethoscopes?
Eko reported that its AI-enabled stethoscopes improved detection of heart failure, atrial fibrillation, and valvular disease in primary care settings. Strategically, this matters because frontline AI tools may gain traction faster when they fit naturally into existing clinician workflows and support earlier identification of high-burden conditions. For medtech and provider organizations, it reinforces the commercial potential of augmentation tools that do not require major infrastructure change.
What did the FDA clear for eMurmur Heart AI?
The FDA cleared eMurmur Heart AI to detect abnormal heart murmurs from digital stethoscope recordings, adding regulatory momentum to software-led cardiology screening tools. Strategically, this matters because clearance supports commercialization and increases the credibility of AI tools designed for broader frontline use. For digital diagnostics companies, it is another sign that accessible, device-linked software may become an important layer in earlier cardiovascular detection.
What is GAIA launching with Daiichi Sankyo Europe?
GAIA is launching lipodia, a digital therapeutic for hypercholesterolemia, with Daiichi Sankyo Europe holding commercialization rights in Germany. Strategically, this matters because digital therapeutics appear more viable when paired with established pharma infrastructure and a clear go-to-market model. For pharma and healthtech leaders, the partnership suggests that adoption may depend less on the technology alone and more on commercial execution and disease-area fit.
What did the FDA clear for Philips SmartHeart?
The FDA cleared Philips SmartHeart, an AI-powered cardiac MR planning tool designed to automate imaging workflows and reduce operator burden. Strategically, this matters because workflow AI often offers a clearer path to adoption than more disruptive tools, especially when it improves consistency and efficiency in complex imaging environments. For imaging companies, it underscores the continued value of operational AI in regulated clinical settings.
What dataset did iMerit, Segmed, and Advocate Health release?
iMerit, Segmed, and Advocate Health released an open annotated breast tomosynthesis dataset with biopsy-confirmed outcomes, creating a potentially valuable resource for model development and benchmarking. Strategically, this matters because high-quality open datasets can lower barriers to entry, accelerate iteration, and intensify competition in breast imaging AI. For startups and researchers, access to better data can materially improve both model quality and market readiness.
What is HKU’s AI-powered ultrasound MetaLens?
HKU’s AI-powered MetaLens is a probe-mounted ultrasound accessory designed to improve imaging through the ribcage in thoracic applications. Strategically, this matters because some of the most important advances in healthcare AI may come from combining software, hardware, and physics rather than relying on algorithms alone. For medtech innovators, it highlights how differentiated clinical performance can emerge from integrated system design.
What did researchers find about the CCDC3 pathway in colorectal cancer?
Researchers identified a CCDC3/CXCR3/STAT3/CDT1 axis linked to chromosomal instability and metastatic progression in colorectal cancer liver metastases. Strategically, this matters because AI-enabled biological analysis can help surface mechanistic insights that may later support target discovery or biomarker development. For pharma R&D teams, the relevance lies in whether such findings can be translated into tractable programs with therapeutic or diagnostic value.
What is RCT-Twin-GAN designed to model?
RCT-Twin-GAN is designed to model how treatment effects observed in trials may translate across different patient populations and real-world settings. Strategically, this matters because the gap between trial evidence and real-world applicability is increasingly important for regulators, payers, and commercial teams. For pharma and market access leaders, tools that improve external-validity interpretation could become highly useful in evidence planning and launch strategy.
What did the AI chatbot study show about HIV PrEP initiation?
The AI chatbot study found that engagement was associated with higher PrEP initiation, better follow-up attendance, and stronger adherence-related behaviors. Strategically, this matters because AI value in healthcare is not limited to diagnosis or discovery and can also appear in scalable patient activation and care continuity. For digital health and pharma teams, this points to meaningful opportunity in support tools that improve conversion and persistence across care journeys.
What pricing model do buyers prefer for diagnostic AI?
Buyers preferred transparent hybrid pricing that combines a predictable base fee with clear variable components tied to use or value. Strategically, this matters because procurement friction remains a major barrier in diagnostic AI, and commercial simplicity can directly influence adoption. For vendors, the message is that pricing design is not just a financial decision but part of the product’s overall market fit.
What is MedVersa in NEJM AI?
MedVersa is a generalist multimodal imaging model that reportedly matched or exceeded specialist systems across several tasks. Strategically, this matters because imaging AI may be moving toward broader foundation-style models that reduce fragmentation across use cases. For radiology AI companies and investors, the implication is that differentiation may increasingly depend on platform breadth, integration, and workflow value rather than narrow task-level performance alone.
What is the ESSENCE study evaluating with Ada Health?
The ESSENCE study is evaluating Ada Health’s symptom assessment tool within a digital front door model in Portugal’s CUF network. Strategically, this matters because AI-based navigation tools may help shape where patients enter the system and how efficiently care is routed. For providers and payers, these tools could become increasingly relevant where demand management, access optimization, and patient experience are strategic priorities.
What is PanCAM designed to detect?
PanCAM is designed to detect lymph node metastasis across multiple cancer types using pathology whole-slide images. Strategically, this matters because broad-use pathology AI may offer better scale economics and deployment potential than narrowly defined tools. For pathology and oncology stakeholders, cross-cancer utility can strengthen both the business case and the operational relevance of adoption.
What is the BRAIx breast cancer risk score?
BRAIx is an AI-derived mammography risk score designed to predict both current breast cancer detection and future risk after a negative screen. Strategically, this matters because imaging AI is starting to support risk stratification, not just abnormality detection, which could influence how screening programs are designed and personalized. For healthcare systems and innovators, this opens the door to more tailored surveillance models and population-level screening optimization.
What is the Merck and Mayo Clinic AI precision-medicine lab?
The Merck and Mayo Clinic AI precision-medicine lab is a strategic collaboration focused on target identification and virtual-cell approaches using multimodal clinical data. Strategically, this matters because pharma continues to seek an edge through combinations of proprietary data, academic expertise, and advanced AI methods. For the wider market, it reinforces the view that competitive advantage in drug discovery may increasingly come from data-rich partnerships rather than isolated internal capability.
What deals did Evinova sign with Astellas, BMS, and AstraZeneca?
Evinova signed deals with Astellas, Bristol Myers Squibb, and AstraZeneca to apply its AI-native platform in clinical development workflows. Strategically, this matters because multiple agreements with major pharma companies strengthen the signal that AI trial operations is becoming an enterprise category rather than a limited pilot space. For competitors and investors, this suggests growing demand for platforms that can support efficiency, benchmarking, and process standardization in development.
What is Evo 2?
Evo 2 is an open-source large genome model trained across bacteria, archaea, and eukaryotes and released with code, parameters, and training data. Strategically, this matters because open biological foundation models can accelerate experimentation, reduce access barriers, and reshape competitive dynamics in AI-enabled biology. For biotech and pharma strategy teams, the longer-term implication is that open infrastructure may speed innovation even as it challenges proprietary advantage.
What is Google building with Taiwan’s Ministry of Health and Welfare?
Google is building what it describes as a nationwide AI health network with Taiwan’s Ministry of Health and Welfare, pointing to a larger infrastructure-level ambition in healthcare AI. Strategically, this matters because the market is moving beyond isolated applications toward system-wide platforms involving governments, health systems, and major technology players. For healthcare leaders, it signals that national-scale partnerships may become an increasingly important route for AI deployment and influence.
Entities/Keywords
RadNet, DeepHealth, Gleamer: radiology AI, imaging AI, diagnostics, Europe expansion
LG CNS, CHA Bio Group, Chong Kun Dang: federated learning, APQR, clinical trial platform, connected healthcare
FutureScot, Embassy of Denmark, Radiobotics, Cortrium, Netcompany: digital health, NHS Scotland, virtual care, musculoskeletal imaging
Sanford Health: rural health, virtual care, agentic AI, travel-cost reduction
AI T-shirt, wearable cardiac AI: remote monitoring, arrhythmia screening, preventive cardiology
Eko Health, TRICORDER, Imperial College London: AI stethoscope, heart failure, atrial fibrillation, valvular disease
eMurmur: murmur detection, digital auscultation, FDA 510(k), telehealth integration
GAIA, Daiichi Sankyo Europe, lipodia: digital therapeutic, hypercholesterolemia, cardiovascular prevention
Philips, SmartHeart: cardiac MR, workflow automation, breath holds, AI planning
iMerit, Segmed, Advocate Health: 3D mammography, DBT, open dataset, breast AI
HKU, SonoMeta: MetaLens, ultrasound, thoracic imaging, emergency care
CCDC3, CXCR3, STAT3, CDT1: colorectal cancer, liver metastasis, chromosomal instability
RCT-Twin-GAN, SPRINT, ACCORD: digital twin, external validity, RCT generalizability
Healthvana, AIDS Healthcare Foundation: HIV PrEP, chatbot, adherence, persistence
diagnostic AI pricing: procurement, reimbursement, hybrid pricing, clinical legibility
MedVersa: multimodal AI, radiology reporting, segmentation, VQA
Ada Health, CUF, ESSENCE: digital front door, symptom assessment, care navigation
PanCAM: pathology AI, lymph node metastasis, whole-slide image, pan-cancer
BRAIx AI Reader, BRAIx risk score: mammography AI, breast screening, risk stratification
Merck, Mayo Clinic Platform Orchestrate: precision medicine, multimodal data, virtual cells
Evinova, Astellas, Bristol Myers Squibb, AstraZeneca: clinical trials, AI-native platform, document management
Evo 2, OpenGenome2: large genome model, regulatory DNA, splice sites, open source
Google, Taiwan Ministry of Health and Welfare: AI health network, national infrastructure, healthcare AI
References
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https://www.chosun.com/english/industry-en/2026/03/05/VWGQD3VYUJARVNEQVREM75OJ6E/
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https://www.mpo-mag.com/breaking-news/fda-clears-ai-powered-heart-murmur-detection-software/
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https://www.miragenews.com/hku-unveils-ai-metalens-to-revolutionize-1631453/
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https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00143-8/fulltext
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https://www.thelancet.com/journals/landig/article/PIIS2589-7500(26)00010-5/fulltext
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https://www.2minutemedicine.com/merck-and-mayo-clinic-launch-ai-driven-precision-medicine-lab/
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https://www.digitimes.com/news/a20260305PD212/google-taiwan-google-taiwan-nhia-healthcare.html