AI System Identifies Early Osteoporosis Indicators from X-Ray Images
AI system detects early osteoporosis signs from X-ray images, improving diagnosis and screening efficiency. 🦴📸
July 19, 2025
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Discover the newest research about AI innovations in 🤖 Machine Learning.
An academic evaluation of ChatGpt’s ability and accuracy in creating patient education resources for rare cardiovascular diseases.
ChatGPT’s accuracy in rare cardiovascular disease education is limited; expert review shows redundancy and incomplete answers. 📉💔
July 19, 2025
Concerns Over AI Chatbots as Alternatives to Therapists
AI chatbots may not be safe substitutes for therapists, showing inadequate responses and potential harm in mental health support. 🧠⚠️
July 19, 2025
The human touch in AI: optimizing language learning through self-determination theory and teacher scaffolding.
AI in language learning boosts motivation and proficiency, especially with teacher support. Key findings from a recent study! 📚🤖
July 19, 2025
Numan Raises $60 Million to Expand Digital Health Services
Numan secures $60 million to enhance digital health services, focusing on female health and expanding patient care. 💰👩⚕️
July 18, 2025
CD79A and GADD45A as novel immune-related biomarkers for respiratory syncytial virus severity in children: an integrated machine learning analysis and clinical validation.
New biomarkers CD79A & GADD45A linked to RSV severity in children. Machine learning reveals critical immune insights. 📊🦠
July 18, 2025
Deep learning-based detection of depression by fusing auditory, visual and textual clues.
AI detects depression with 99.9% accuracy using audio, visual, and text clues. Promising for early intervention! 🤖📊
July 18, 2025
PREDAC-FluB: predicting antigenic clusters of seasonal influenza B viruses with protein language model embedding based convolutional neural network.
PREDAC-FluB: A Deep Learning Approach to Predict Antigenic Clusters in Influenza B Viruses 🦠📊
July 18, 2025
Machine learning based characterization of high risk carriers of HTLV-1-associated myelopathy (HAM).
Machine learning identifies high-risk HTLV-1 carriers for HAM, predicting 76.47% as likely to develop symptoms. 📊🔍
July 17, 2025
Machine learning to forecast rituximab responses for paediatric immune thrombocytopenia: Forging a path towards personalized medical care.
Machine learning predicts rituximab responses in pediatric ITP, enhancing personalized treatment strategies. 📊🤖
July 16, 2025