--- title: "AI in Diagnostics & Medical Imaging" description: "AI agents for diagnostics: radiology AI, pathology imaging, oncology research support. Human-in-the-loop AI. HIPAA & MDR compliant." lang: en json-ld: | [ { "@context": "https://schema.org", "@graph": [ { "@type": "Organization", "@id": "https://alicelabs.ai/#organization", "name": "Alice Labs", "alternateName": [ "Alice Labs AB", "AliceLabs" ], "legalName": "Alice Labs AB", "identifier": "559443-5470", "foundingLocation": { "@type": "Place", "name": "Stockholm, Sweden" }, "url": "https://alicelabs.ai", "logo": { "@type": "ImageObject", "@id": "https://alicelabs.ai/#logo", "url": "https://alicelabs.ai/images/alice-logo.png", "contentUrl": "https://alicelabs.ai/images/alice-logo.png", "width": 2000, "height": 2027, "caption": "Alice Labs" }, "image": { "@id": "https://alicelabs.ai/#logo" }, "description": "Alice Labs är en svensk AI-byrå som hjälper företag implementera AI - från strategi till skalning.", "slogan": "From AI strategy to measurable results.", "foundingDate": "2023", "email": "hej@alicelabs.ai", "telephone": "+46734157476", "address": { "@type": "PostalAddress", "streetAddress": "Hammarbybacken 27", "addressLocality": "Stockholm", "postalCode": "120 30", "addressCountry": "SE" }, "contactPoint": [ { "@type": "ContactPoint", "contactType": "customer service", "email": "hej@alicelabs.ai", "telephone": "+46734157476", "areaServed": [ "SE", "EU" ], "availableLanguage": [ "Swedish", "English" ] } ], "areaServed": [ { "@type": "Country", "name": "Sweden" }, { "@type": "Place", "name": "Europe" } ], "knowsAbout": [ "AI strategy", "AI implementation", "AI agents", "AI automation", "Generative AI", "AI governance", "AI training", "Machine learning", "Large language models", "RAG", "AI consulting", "Digital transformation", "AI search optimization", "LLMO", "AI for enterprise" ], "founder": [ { "@id": "https://alicelabs.ai/#linus" }, { "@id": "https://alicelabs.ai/#eric" } ], "sameAs": [ "https://www.linkedin.com/company/alicelabsai", "https://www.trustpilot.com/review/alicelabs.ai", "https://www.wikidata.org/wiki/Q140369570" ] }, { "@type": "Person", "@id": "https://alicelabs.ai/#linus", "name": "Linus Ingemarsson", "givenName": "Linus", "familyName": "Ingemarsson", "jobTitle": "Co-Founder", "description": "Co-founder of Alice Labs. 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AI agents augment radiologists by pre-reading studies, flagging critical findings, and prioritizing worklists. The radiologist always makes the final interpretation. Our AI reduces workload and catches findings that might be missed during high-volume reading sessions." } }, { "@type": "Question", "name": "How accurate is AI in medical imaging?", "acceptedAnswer": { "@type": "Answer", "text": "Accuracy depends on the modality and pathology. For specific use cases like mammography screening, lung nodule detection, and fracture identification, AI models achieve sensitivity and specificity comparable to or exceeding expert radiologists — but always as a second reader, never as a standalone diagnostic tool." } }, { "@type": "Question", "name": "What imaging modalities does Alice Labs support?", "acceptedAnswer": { "@type": "Answer", "text": "Our AI agents work across CT, MRI, X-ray, mammography, ultrasound, and whole-slide imaging (digital pathology). We deploy modality-specific models optimized for each imaging type, with the ability to correlate findings across multimodal studies." } }, { "@type": "Question", "name": "How does AI work in digital pathology?", "acceptedAnswer": { "@type": "Answer", "text": "AI agents analyze whole-slide images at cellular resolution: identifying mitotic figures, quantifying biomarkers (Ki-67, PD-L1, HER2), detecting tumor margins, and grading specimens. This augments pathologists' diagnostic accuracy and reduces turnaround time for complex cases by 30-50%." } }, { "@type": "Question", "name": "What is the regulatory status of AI diagnostic tools?", "acceptedAnswer": { "@type": "Answer", "text": "We implement AI as clinical decision support — not as an autonomous diagnostic device. This means clinician oversight is mandatory for all findings. For deployments requiring CE marking (MDR) or FDA clearance, we design systems aligned with those regulatory pathways and provide the documentation needed for submission." } }, { "@type": "Question", "name": "How does Alice Labs handle bias in diagnostic AI?", "acceptedAnswer": { "@type": "Answer", "text": "We implement rigorous bias testing across patient demographics (age, sex, ethnicity), imaging equipment types, and clinical settings. Models are validated on diverse datasets and continuously monitored for performance drift across population subgroups. Bias reports are included in every model deployment." } }, { "@type": "Question", "name": "Can AI prioritize critical findings in radiology?", "acceptedAnswer": { "@type": "Answer", "text": "Yes. AI agents triage incoming studies and flag critical findings (stroke, PE, pneumothorax, fractures) within seconds of image acquisition. This enables radiologists to read urgent cases first, reducing time-to-diagnosis for critical conditions from hours to minutes." } }, { "@type": "Question", "name": "How does AI integrate with PACS systems?", "acceptedAnswer": { "@type": "Answer", "text": "We connect via DICOM and HL7/FHIR interfaces to major PACS platforms (Sectra, Agfa, Philips, GE). AI pre-reads are delivered directly into the radiologist's reading workflow — no separate application needed. Results appear as structured findings in the standard reporting interface." } }, { "@type": "Question", "name": "What is the ROI of AI in diagnostic imaging?", "acceptedAnswer": { "@type": "Answer", "text": "Typical outcomes: 40-60% reduction in diagnostic turnaround time, 15-25% improvement in critical finding detection rates, 30% reduction in repeat studies, and measurable increase in radiologist throughput without sacrificing quality." } }, { "@type": "Question", "name": "Can AI support oncology research and treatment planning?", "acceptedAnswer": { "@type": "Answer", "text": "Yes. AI agents analyze tumor characteristics, track longitudinal changes, quantify treatment response (RECIST criteria), and correlate imaging with genomic and clinical data. This supports both clinical treatment decisions and research protocol adherence." } }, { "@type": "Question", "name": "What is AI-powered diagnostics and medical imaging outsourcing?", "acceptedAnswer": { "@type": "Answer", "text": "AI-powered diagnostics outsourcing means delegating specific reading, triage, or quantification tasks to a vendor-run AI stack (models, DICOM pipeline, MLOps) while your radiologists retain final sign-off. Alice Labs deploys within 30-90 days, integrates with existing PACS (Sectra, Agfa, Philips, GE), and typically cuts turnaround time 40-60% on triaged worklists. The FDA now lists over 1,000 authorized AI/ML-enabled medical devices, roughly 76% in radiology, so the regulatory pathway is well-defined." } }, { "@type": "Question", "name": "How does medical imaging support diagnostic agents?", "acceptedAnswer": { "@type": "Answer", "text": "Diagnostic AI agents ingest DICOM studies from PACS, run modality-specific vision models (CT, MRI, X-ray, mammography, ultrasound, whole-slide), and return structured findings — bounding boxes, measurements, confidence scores, heatmaps — back into the radiologist's report template via HL7/FHIR. The imaging layer handles pixel normalization, series selection, and de-identification. Alice Labs' pipeline delivers sub-second inference per study and logs every prediction for MDR post-market surveillance." } }, { "@type": "Question", "name": "What does AI imaging consulting from Alice Labs cover?", "acceptedAnswer": { "@type": "Answer", "text": "Our AI imaging consulting covers four phases: (1) use-case scoping against your worklist volumes and modality mix, (2) model selection or custom training on your institution's data, (3) PACS/RIS integration with DICOM and HL7/FHIR, and (4) validation, bias testing, and MDR/FDA-aligned documentation. Engagements run 30-90 days and include a written radiology AI quality assurance plan covering drift monitoring, subgroup performance, and clinician override rates." } } ] } ] } ] --- ![Background for AI Diagnostics](/images/bakgrund.jpg) [Alice Labs](/en/) Services [ What we do ](/#welcome)[ About Alice ](/#who-we-are)[ Case ](/en/case)[ Insights ](/en/insights)[ Contact ](/#email-form)[sv](/industri/sjukvarden) [Home](/en)[Industries](/en/industries) [Healthcare & Life Sciences](/en/industries/healthcare-life-sciences) AI in Diagnostics & Imaging AI for Diagnostics # AI Agents That Augment Diagnostic Precision Alice Labs builds AI agents that augment — never replace — diagnostic radiologists and pathologists. Our computer vision models pre-read imaging studies in seconds, flag critical findings, quantify measurements, and prioritize worklists — reducing diagnostic turnaround by 40-60% while maintaining full clinician oversight. Built for HIPAA, GDPR, and MDR requirements. Book a Discovery Call Built for HIPAA & MDR Human-in-the-Loop 30-90 Day Delivery Last updated 2026-07-15 Have a project in mind? Get a response within 24 hours — no obligation. Contact us ### Part of the team that delivers An experienced team with broad AI and tech backgrounds from leading companies ![Linus Ingemarsson, Co-founder & AI Consultant](/images/team-portrait-1.jpg) Linus Co-founder & AI Consultant ![Alice, CEO & Co-founder](/images/team-portrait-2.jpg) Alice CEO & Co-founder ![Jens, AI Consultant](/images/team-portrait-3.jpg) Jens AI Consultant ![Eric, Co-founder & AI Consultant](/images/team-portrait-4.jpg) Eric Co-founder & AI Consultant ![Lisa, Project Lead & Implementation](/images/team-portrait-5.jpg) Lisa Project Lead & Implementation ## Why enterprises pick Alice Labs Production-grade AI delivery, EU-native, senior team 100+ AI implementations shipped across Europe 85% Of clients see ROI within 12 months EU-native AI Act & GDPR ready Stockholm-based, EU data residency Senior team Hands-on delivery Experienced practitioners Ready to talk? Tell us about your goals and we'll suggest the fastest path forward. Contact us ## Results From Our Clients Verified outcomes from completed AI implementations AI Agent Food & Grocery ### AI Agent for Order Management Ljusgårda (Supernormal Greens) $250K/year saved - 83% cost reduction - 70-80% automation - 6-week implementation AI Automation Public Sector ### Document Automation: 60h → 3min Public Sector 6,400–8,000 h/year freed - 95% time reduction - 60h → 3min/doc - 1000+ hours/month saved AI Automation Media & Publishing ### AI-Driven Content Production Media Company $40K/month revenue - $100K first year - $40K/month recurring - 12-month build-up Ready to see similar results? Book a free discovery call - we'll map your highest-impact AI opportunities. Book a Discovery Call 2026 signal · Last updated 2026-07-15 The FDA now lists **over 1,000 AI/ML-enabled medical devices** authorized for the U.S. market, with radiology accounting for approximately **76% of clearances** — the single largest specialty. Diagnostic imaging is the most mature AI regulatory pathway in medicine, and vendor selection now hinges on integration depth and post-market surveillance rather than model novelty. Source: [FDA — AI/ML-Enabled Medical Devices list](https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices). ## Top AI Use Cases in Diagnostics Where AI agents deliver the highest impact in diagnostic medicine ### 1\. Radiology AI & Worklist Prioritization Radiologists face growing study volumes — 15-25% annual increases — with no proportional staffing growth. AI agents pre-read CT, MRI, and X-ray studies in seconds, flag critical findings (stroke, PE, fractures), and reprioritize worklists so urgent cases are read first. Turnaround time for critical findings drops from hours to minutes. Key Deliverables: Critical finding detection Automated measurements Worklist prioritization Structured report pre-population ### 2\. Digital Pathology & Biomarker Quantification Manual pathology review is subjective, time-consuming, and prone to inter-observer variability. AI agents analyze whole-slide images at cellular resolution — counting mitotic figures, quantifying biomarkers (Ki-67, PD-L1, HER2), detecting tumor margins, and grading specimens with consistent, reproducible accuracy. Key Deliverables: Whole-slide image analysis Biomarker quantification Tumor grading assistance Quality assurance flagging ### 3\. Oncology Imaging & Treatment Response Tracking tumor response across multiple imaging timepoints requires precise measurements and longitudinal comparison. AI agents automate RECIST measurements, quantify volumetric changes, correlate imaging with genomic data, and flag progression earlier — enabling faster treatment adjustments. Key Deliverables: Automated RECIST measurements Volumetric tumor tracking Treatment response quantification Longitudinal comparison reports ## Built for Diagnostic Precision ### Built for HIPAA & MDR End-to-end encryption, PHI protection, and regulatory documentation aligned with CE marking and FDA pathways. ### Multi-Modal AI Models Specialized computer vision architectures for CT, MRI, X-ray, mammography, ultrasound, and whole-slide imaging. ### Sub-Second Inference Real-time AI pre-reads delivered to the reading worklist before the radiologist opens the study. ### PACS Integration Native DICOM connectivity with Sectra, Agfa, Philips, and GE PACS platforms. No workflow disruption. ### Explainable Results Heatmaps, attention overlays, and confidence scores for every AI finding — clinicians see why the AI flagged an area. ### Continuous Learning Models improve with your institution's data through federated learning — without patient data ever leaving your environment. Let's discuss your AI journey Our team will help you prioritize use cases and build a concrete roadmap. Book a Meeting ## Explore Other Industries Alice Labs delivers AI agents across every major industry vertical [ ### Finance, Banking & Insurance Explore ](/en/industries/finance-banking-insurance)[ ### AI in Banking Explore ](/en/industries/ai-in-banking)[ ### AI in Insurance Explore ](/en/industries/ai-in-insurance)[ ### AI in Wealth Management Explore ](/en/industries/ai-in-wealth-management)[ ### Healthcare & Life Sciences Explore ](/en/industries/healthcare-life-sciences)[ ### AI in Healthcare Explore ](/en/industries/healthcare) [View all industries](/en/industries) ### Our Core AI Services [AI Consulting](/en/ai-consulting)[AI Strategy](/en/ai-strategy)[AI Automation](/en/ai-automation)[AI Agents](/en/ai-agents)[AI Discovery](/en/ai-discovery)[AI Implementation](/en/ai-implementation-consultant) ## What Our Clients Say "We decided early on to embrace AI technology and needed a partner who could explore opportunities, propose solutions, lead change management, and build them. With Alice, we got everything in one place and have implemented multiple solutions that increased efficiency so significantly that an entire team could be reallocated." Andreas Wilhelmsson CEO & Co-founder Supernormal Greens / Ljusgårda "Alice Labs' AI training gave us all a real aha-moment, whether we were completely new to the field or experienced! The training contained a perfect balance between theory and practice. We have definitely become more efficient at work!" Åsa Nordin IT Manager Trollhättan Energi "The collaboration with Alice Labs has been easy, educational, and incredibly supportive. We engaged them to improve our processes and create more efficiency in the team, and the result truly exceeded expectations. Through their guidance, we've gained better structure, faster workflows, and more time for what actually creates results." Frida Partner Manager Bruce Studios "Fast, professional, and wonderful people. Find out for yourself <3" Johannes Hansen Founder Johannes Hansen AB ## Frequently Asked Questions ### Can AI replace radiologists? No — and that is explicitly not our approach. AI agents augment radiologists by pre-reading studies, flagging critical findings, and prioritizing worklists. The radiologist always makes the final interpretation. Our AI reduces workload and catches findings that might be missed during high-volume reading sessions. ### How accurate is AI in medical imaging? Accuracy depends on the modality and pathology. For specific use cases like mammography screening, lung nodule detection, and fracture identification, AI models achieve sensitivity and specificity comparable to or exceeding expert radiologists — but always as a second reader, never as a standalone diagnostic tool. ### What imaging modalities does Alice Labs support? Our AI agents work across CT, MRI, X-ray, mammography, ultrasound, and whole-slide imaging (digital pathology). We deploy modality-specific models optimized for each imaging type, with the ability to correlate findings across multimodal studies. ### How does AI work in digital pathology? AI agents analyze whole-slide images at cellular resolution: identifying mitotic figures, quantifying biomarkers (Ki-67, PD-L1, HER2), detecting tumor margins, and grading specimens. This augments pathologists' diagnostic accuracy and reduces turnaround time for complex cases by 30-50%. ### What is the regulatory status of AI diagnostic tools? We implement AI as clinical decision support — not as an autonomous diagnostic device. This means clinician oversight is mandatory for all findings. For deployments requiring CE marking (MDR) or FDA clearance, we design systems aligned with those regulatory pathways and provide the documentation needed for submission. ### How does Alice Labs handle bias in diagnostic AI? We implement rigorous bias testing across patient demographics (age, sex, ethnicity), imaging equipment types, and clinical settings. Models are validated on diverse datasets and continuously monitored for performance drift across population subgroups. Bias reports are included in every model deployment. ### Can AI prioritize critical findings in radiology? Yes. AI agents triage incoming studies and flag critical findings (stroke, PE, pneumothorax, fractures) within seconds of image acquisition. This enables radiologists to read urgent cases first, reducing time-to-diagnosis for critical conditions from hours to minutes. ### How does AI integrate with PACS systems? We connect via DICOM and HL7/FHIR interfaces to major PACS platforms (Sectra, Agfa, Philips, GE). AI pre-reads are delivered directly into the radiologist's reading workflow — no separate application needed. Results appear as structured findings in the standard reporting interface. ### What is the ROI of AI in diagnostic imaging? Typical outcomes: 40-60% reduction in diagnostic turnaround time, 15-25% improvement in critical finding detection rates, 30% reduction in repeat studies, and measurable increase in radiologist throughput without sacrificing quality. ### Can AI support oncology research and treatment planning? Yes. AI agents analyze tumor characteristics, track longitudinal changes, quantify treatment response (RECIST criteria), and correlate imaging with genomic and clinical data. This supports both clinical treatment decisions and research protocol adherence. ### What is AI-powered diagnostics and medical imaging outsourcing? AI-powered diagnostics outsourcing means delegating specific reading, triage, or quantification tasks to a vendor-run AI stack (models, DICOM pipeline, MLOps) while your radiologists retain final sign-off. Alice Labs deploys within 30-90 days, integrates with existing PACS (Sectra, Agfa, Philips, GE), and typically cuts turnaround time 40-60% on triaged worklists. The FDA now lists over 1,000 authorized AI/ML-enabled medical devices, roughly 76% in radiology, so the regulatory pathway is well-defined. ### How does medical imaging support diagnostic agents? Diagnostic AI agents ingest DICOM studies from PACS, run modality-specific vision models (CT, MRI, X-ray, mammography, ultrasound, whole-slide), and return structured findings — bounding boxes, measurements, confidence scores, heatmaps — back into the radiologist's report template via HL7/FHIR. The imaging layer handles pixel normalization, series selection, and de-identification. Alice Labs' pipeline delivers sub-second inference per study and logs every prediction for MDR post-market surveillance. ### What does AI imaging consulting from Alice Labs cover? Our AI imaging consulting covers four phases: (1) use-case scoping against your worklist volumes and modality mix, (2) model selection or custom training on your institution's data, (3) PACS/RIS integration with DICOM and HL7/FHIR, and (4) validation, bias testing, and MDR/FDA-aligned documentation. Engagements run 30-90 days and include a written radiology AI quality assurance plan covering drift monitoring, subgroup performance, and clinician override rates. Have more questions? Let's talk. No commitment - just a conversation about what AI can do for your business. Book a Call ## Ready to Augment Your Diagnostic Capabilities? Tell us about your challenges. We'll respond within 24 hours. 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