Quantitative Imaging for Interstitial Lung Disease.
Quantitative imaging enhances ILD diagnosis and treatment, utilizing CT and emerging MRI techniques. ππ«
December 5, 2025
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Discover the newest research about AI innovations in π€ Machine Learning.
Are we entering a new era of artificial intelligence (AI)-supported decision-making in dentistry?
Exploring AI’s role in dentistry: potential impacts on decision-making and patient outcomes. π€π¦·
December 4, 2025
Foundation model based prediction of lung cancer survival using temporal changes in dual time point CT scans.
Lung cancer survival prediction enhanced by dual time point CT scans. π Study shows improved accuracy using foundation models. π©Ί
December 4, 2025
Maternal lipidomic signatures of preterm and small-for-gestational-age newborn infants in low- and middle-income countries.
Maternal lipid levels impact preterm and SGA births. Key findings: triglyceride imbalances, AUC 0.69 for preterm prediction. ππΆ
December 4, 2025
Immunological risk factors for recurrent implantation failure using a deep learning model: a multicenter retrospective cohort study.
Deep learning predicts live births in recurrent implantation failure with 87.4% accuracy. Key factors: age, Th1/Th2 ratio, BMI. ππ€°
December 3, 2025
Evaluating EEG-to-text models through noise-based performance analysis.
EEG-to-text models show potential but may memorize patterns instead of learning. Rigorous evaluation needed! π§ π
December 3, 2025
Mapping war trauma: A machine learning approach to predict mental health impacts in Ukraine.
Machine learning predicts mental health impacts in Ukraine’s war, revealing key drivers of PTSD and anxiety. ππ§
December 3, 2025
Identifying Key Variances in Clinical Pathways Associated With Prolonged Hospital Stays Using Machine Learning and ePath Real-World Data: Model Development and Validation Study.
Machine learning identifies clinical variances linked to prolonged hospital stays, enhancing patient management. ππ₯
December 2, 2025
Radiographic diagnosis of periodontitis using artificial intelligence: a meta-analysis comparing binary and staging classifications across imaging modalities.
AI in Periodontitis Diagnosis: Sensitivity 87.2% π, Accuracy 88.9% π¦·βA Meta-Analysis Review of Imaging Modalities.
December 2, 2025
Personalized fitness recommendations using machine learning for optimized national health strategy.
Personalized fitness via machine learning: XGBoost shows 0.789 MeanIoU, enhancing public health strategies. ππ€
December 1, 2025