Significantly improve the speed and quality of Radiology reporting by reducing unnecessary dictation, particularly for ultrasound and DEXA. Imorgon transfers modality measurements into Powerscribe/Fluency/RadAI merge fields/tokens, eliminating manual entry errors.
Imorgon's specialized services offer the following advantages:
- All measurements are always transferred (usually DICOM SR)
- Electronic worksheets capture findings and insert them into Powerscribe/Fluency/RadAI (rather than dictating from a worksheet)
- Worksheets with priors, calculators, and clinical decision support (TI-RADS, O-RADS, etc)
- Integrate into Epic or other EHRs
- Vendor neutral
- Support to ensure everything continues working
Significant improvement in the overhead of reporting with a quick ROI.
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DoctorConnect stands as a reputable innovator in patient engagement solutions, having dedicated over 25 years to enhancing the healthcare landscape. We assist medical practices, regardless of size, in optimizing communication, automating everyday tasks, and elevating the patient experience. From independent doctors to extensive health organizations, numerous providers across the country depend on our adaptable tools to lighten administrative workloads, minimize missed appointments, and boost revenue streams.
Our platform is crafted to align with real-world healthcare needs—offering scalability, user-friendliness, and seamless integration with a multitude of EMR and Practice Management (PM) systems. Whether your goal is to update appointment scheduling, automate patient reminders, or gather meaningful feedback, DoctorConnect delivers a comprehensive solution that caters to your specific workflow.
Focusing on adaptability and tangible outcomes, we enable clinics to conserve time, improve patient satisfaction, and enhance operational efficiency while ensuring that current systems remain undisturbed. Our commitment to innovation continues to propel us as a partner in the ongoing evolution of healthcare delivery.
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Fluency for Imaging
Fluency for Imaging is an AI-powered radiology reporting platform developed by Jacobian to support faster, more accurate diagnostic reporting in medical imaging workflows. Radiology departments face increasing workloads and complex reporting requirements, which often lead to documentation inefficiencies and cognitive overload for clinicians. Fluency for Imaging addresses these challenges by combining advanced speech recognition technology, AI-driven automation, and structured reporting capabilities into a unified reporting environment. Radiologists can dictate reports using natural speech while the platform automatically organizes the narrative into structured clinical documentation. The system integrates directly with PACS platforms to transfer measurement data, imaging findings, and AI-generated insights directly into the report, eliminating manual transcription and reducing the potential for errors. Fluency for Imaging also incorporates large language model–based ambient reporting features that can listen to dictations, understand clinical context, and generate structured impressions automatically. Built-in guideline support and intelligent nudging help ensure reports follow established medical standards such as BI-RADS, PI-RADS, and TNM classifications. The platform also enables ontology-based coding using clinical standards including RadLex, SNOMED CT, and ICD-10, transforming unstructured text into structured, data-rich reports suitable for analytics, research, and clinical decision support. Multimedia reporting features allow radiologists to include annotated images, tables, and visual diagrams to improve report clarity for referring physicians. Additionally, Fluency for Imaging supports interoperability through standards such as HL7, FHIR, and FHIRcast, enabling seamless communication between imaging systems, hospital information systems, and analytics platforms.
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WRDensity
WRDensity aids radiologists in assessing breast density, fostering uniformity in evaluations throughout their practices. Its main goal is to enhance early detection while ensuring that patients enjoy greater reassurance through improved consistency, confidence, and overall care quality. Created using cutting-edge deep learning methodologies, WRDensity has meticulously analyzed over 600,000 images from the renowned Mallinckrodt Institute of Radiology, which is celebrated for its groundbreaking contributions to the field. This powerful deep learning model is particularly adept at delivering accurate breast density classifications. Moreover, its batching and sorting capabilities can enhance user productivity by up to 20%. By incorporating WRDensity into the radiologist's current workstation, vital information regarding tissue density becomes easily accessible within a pertinent context, thereby further refining the diagnostic procedure. In conclusion, this advancement not only streamlines workflows but also plays a crucial role in enhancing patient outcomes, making it a valuable tool in modern radiology.
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