The Role of Machine Learning Approaches in Pediatric Oncology: A Systematic Review.
Machine learning shows promise in pediatric oncology, enhancing diagnosis and treatment. Review highlights current advancements and challenges. 🤖🎗️
[Implementation and evaluation of a solution for automated documentation of the doctor-patient dialogue (ADAPI) in ophthalmology using the example of the IVI routine].
Automated documentation in ophthalmology enhances doctor-patient communication. 🤖👁️ Study shows potential for improved efficiency and care.
New Framework Enhances AI’s Ability to Analyze Genomic Data
New framework improves AI's analysis of genomic data, enhancing accuracy in cell annotations and biological research. 🧬🔬
Clinical Microbiology: where do we stand?
Clinical microbiology has evolved significantly, influenced by globalization and new technologies. Key advancements include molecular biology and AI. 🦠🔬
New AI Model Predicts Cancer Immunotherapy Success Using Blood Tests
New AI model SCORPIO predicts cancer immunotherapy success using routine blood tests. This tool aims to improve patient treatment decisions. 🩸💡
Enhancing Small-for-Gestational-Age Prediction: Multi-Country Validation of Nuchal Thickness, Estimated Fetal Weight, and Machine Learning Models.
New research highlights the role of nuchal thickness in predicting small-for-gestational-age infants. 📊🤰 Machine learning models show promise.
Insights from Children’s National Hospital’s Chief AI Officer
Children's National Hospital's Chief AI Officer discusses her role in integrating AI for improved patient care and operational efficiency. 🤖🏥
Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.
Exploring AI in language disorder detection 🤖📚: Recent advances enhance assessment efficiency for children’s language disorders.