ArticleScientific reports2023
AI aided workflow for hip dysplasia screening using ultrasound in primary care clinics.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 3 syntheses or guidelines pooled it, 31 citations in OpenAlex.
- Artificial Intelligence to Detect Developmental Dysplasia of Hip: A Systematic Review.Journal of paediatrics and child health · 2025Pooled it
- Opportunities, challenges, and requirements for Artificial Intelligence (AI) implementation in Primary Health Care (PHC): a systematic review.BMC primary care · 2025Pooled it
- Availability of Evidence for Predictive Machine Learning Algorithms in Primary Care: A Systematic Review.JAMA network open · 2024Pooled it
- Artificial Intelligence-Assisted Wireless Handheld Ultrasound for Screening Developmental Dysplasia of the Hip in Infants.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2026Article
- Current applications and challenges of artificial intelligence applied to diagnostics in pediatric musculoskeletal imaging.Pediatric radiology · 2026Review
- Explainable Quality Assessment and Measurement from Real-World Hip Ultrasound Cine Sweeps.Bioengineering (Basel, Switzerland) · 2026Article
- Review
- Applications of Artificial Intelligence in Pediatric Orthopaedics.Indian journal of orthopaedics · 2026Review
- A modern radiologist's guide to artificial intelligence.Pediatric radiology · 2026Review
- Automated Neonatal Hip Ultrasound System for Diagnosing Developmental Dysplasia of Hips Using Assistive AI.Journal of imaging informatics in medicine · 2026Article
- Scaling Early Detection for Developmental Dysplasia of the Hip With Artificial Intelligence-Assisted Imaging.Cureus · 2026Review
- Deep learning algorithms for identifying developmental dysplasia of the hip based on sonographic images: a retrospective, prospective, multicenter study in China.EClinicalMedicine · 2025Article
- Artificial Intelligence Algorithm Supporting the Diagnosis of Developmental Dysplasia of the Hip: Automated Ultrasound Image Segmentation.Journal of clinical medicine · 2025Article
- Artificial intelligence in orthopedics: fundamentals, current applications, and future perspectives.Military Medical Research · 2025Review
- Integrating web-based and objective structured clinical examination training programs for nurses on ultrasound hip screening during neonatal and infant home visits: a case study.BMC medical education · 2025Article
- Machine learning-assisted classification of hip conditions in pediatric cerebral palsy patients using migration percentage measurements.Bone reports · 2025Article
- Current and Emerging Applications of Artificial Intelligence in Medical Imaging for Paediatric Hip Disorders-A Scoping Review.Children (Basel, Switzerland) · 2025Review
- Overcoming barriers in the use of artificial intelligence in point of care ultrasound.NPJ digital medicine · 2025Review
- Progress in the Application of Artificial Intelligence in Ultrasound-Assisted Medical Diagnosis.Bioengineering (Basel, Switzerland) · 2025Review
- Advances in Ultrasound-Guided Surgery and Artificial Intelligence Applications in Musculoskeletal Diseases.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Developmental dysplasia of the hip (DDH) is a common cause of premature osteoarthritis. This osteoarthritis can be prevented if DDH is detected by ultrasound and treated in infancy, but universal DDH screening is generally not cost-effective due to the need for experts to perform the scans. The purpose of our study was to evaluate the feasibility of having non-expert primary care clinic staff perform DDH ultrasound using handheld ultrasound with artificial intelligence (AI) decision support. We performed an implementation study evaluating the FDA-cleared MEDO-Hip AI app interpreting cine-sweep images obtained from handheld Philips Lumify probe to detect DDH. Initial scans were done by nurses or family physicians in 3 primary care clinics, trained by video, powerpoint slides and brief in-person. When the AI app recommended follow-up (FU), we first performed internal FU by a sonographer using the AI app; cases still considered abnormal by AI were referred to pediatric orthopedic clinic for assessment. We performed 369 scans in 306 infants. Internal FU rates were initially 40% for nurses and 20% for physicians, declining steeply to 14% after ~ 60 cases/site: 4% technical failure, 8% normal at sonographer FU using AI, and 2% confirmed DDH. Of 6 infants referred to pediatric orthopedic clinic, all were treated for DDH (100% specificity); 4 had no risk factors and may not have otherwise been identified. Real-time AI decision support and a simplified portable ultrasound protocol enabled lightly trained primary care clinic staff to perform hip dysplasia screening with FU and case detection rates similar to costly formal ultrasound screening, where the US scan is performed by a sonographer and interpreted by a radiologist/orthopedic surgeon. This highlights the potential utility of AI-supported portable ultrasound in primary care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.