AI in Healthcare

Best Radiology Software in 2026: A Category-by-Category Guide “Radiology software” is not one product. It is a stack of specialized tools that, together, move a medical image from the scanner to a signed report and then to the referring clinician. When people search for the best radiology software,... By Mircea Popa Sep 24, 2026

Orthopedic Imaging: Modalities, Clinical Uses, and In-Office Workflow Orthopedic imaging is the use of medical imaging to diagnose bone, joint, and soft-tissue conditions, plan orthopedic surgery, and assess how patients heal afterward. Five modalities do most of the work: X-ray, MRI, CT, musculoskeletal ultrasound, and DEXA. Fluoroscopy and... By Mircea Popa Jun 29, 2026

Radiology Voice Recognition Systems and Dictation Software: How the Reading Workflow Works in 2026 Radiology dictation software, voice recognition, and worklist management are three connected components of the radiologist’s daily reading workflow. Worklist management determines which studies the radiologist reads next and in what order. Voice recognition translates the radiologist’s dictation into structured text.... By Alexandru Artimon Jun 26, 2026

AI in Mammography: How It Works, FDA-Cleared Tools, and What Imaging Centers Need to Deploy It Artificial intelligence in mammography is the application of machine learning algorithms, primarily deep neural networks trained on large annotated mammographic image datasets, to assist with detecting breast cancer, assessing breast cancer risk, quantifying breast density, triaging screening worklists, and structuring... By Mircea Popa Jun 23, 2026

MRI Segmentation With AI: Multi-Organ Applications and Methods MRI segmentation with AI converts raw magnetic resonance imaging data into labeled maps of anatomy and pathology that clinicians and researchers can measure, monitor, and analyze quantitatively. The underlying technology is consistent across all clinical contexts: deep learning models, primarily... By Andrei Blaj Jun 1, 2026

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AI in Telemedicine: How It Is Used in Virtual Care, Remote Monitoring, and Teleradiology Artificial intelligence in telemedicine is the application of machine learning, natural language processing, and computer vision to support the remote delivery of clinical care. The scope is wider than the chatbot symptom checker that most general healthcare articles focus on.... By Alexandru Artimon May 11, 2026

Vendor Neutral Archive Benefits: What VNA Delivers vs What Vendors Claim The case for a vendor neutral archive is made the same way by every vendor that sells one. Eliminate vendor lock-in. Reduce storage costs. Enable cross-department access. Integrate images into the EHR. Prepare your archive for AI. All of these... By Alexandru Artimon Apr 13, 2026

Why Imaging Infrastructure Matters for AI Generalization in Radiology Artificial intelligence has shown impressive results in radiology research settings. From mammography to CT and MRI, AI models often achieve high accuracy when evaluated on curated datasets. Yet once deployed in real clinical environments, many of these same models struggle... By Mircea Popa Jan 21, 2026

AI Orchestration in PACS: Moving Beyond "Buzzwords" to Real Workflow AI orchestration in PACS is the workflow control layer that triggers inference, applies routing rules, selects models, and delivers AI results back into PACS worklists and reporting in a way clinicians actually use. This guide explains AI orchestration in PACS,... By Alexandru Artimon Jan 14, 2026

Does AI Really Deliver Economic Value in Radiology? What the Evidence Says Economic value from radiology AI is not guaranteed. A January 2026 systematic review found that only 21 studies out of 1,879 screened records (about 1%) actually quantified economic outcomes, and the results depended on task complexity, examination volume, and the... By Mircea Popa Jan 5, 2026

Agentic Document Processing: The Future of Intelligent Healthcare Workflows For years, healthcare automation relied on rules—if-then systems that could only handle predictable inputs. If a referral form matched a known template, it was processed; if not, it was flagged for human review. But the reality of healthcare data is... By Andrei Blaj Oct 29, 2025

How AI Document Extraction Accelerates Clinical Workflows Healthcare runs on documents — referrals, reports, authorizations, discharge summaries, and imaging requests. Each plays a critical role in diagnosis and care coordination, yet most are still processed manually.This administrative bottleneck delays treatment, increases clinician burnout, and slows down operational... By Andrei Blaj Oct 28, 2025