Here are the latest breakthroughs in health & AI (September 01, 2025 week)

🔹 Automated Mucormycosis Diagnosis from Paranasal CT Using ResNet50 and ConvNeXt Small.

Automated mucormycosis diagnosis via CT scans shows 100% accuracy with ConvNeXt Small model. 🤖🦠

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🔹 Kinematic Adaptive Frame Recognition (KAFR): A Novel Framework for Video Segmentation via Frame Similarity and Surgical Tool Tracking.

KAFR enhances surgical video analysis, achieving 10x frame reduction and 4.32% accuracy boost. 🤖📊

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🔹 Advances in the Application of Three-Dimensional Reconstruction in Thoracic Surgery: A Comprehensive Review.

“3D Reconstruction in Thoracic Surgery: Enhancing Precision & Outcomes 📊🔍”

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🔹 Application and ethical implication of generative artificial intelligence in medical education: a cross-sectional study among critical care academic physicians in China.

Exploring AI’s role in medical education: critical insights from Chinese physicians. 🤖📚 Ethical implications and applications analyzed.

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🔹 Effects of attractions and social attributes on peoples’ usage intention and media dependence towards chatbot: The mediating role of parasocial interaction and emotional support.

Exploring chatbot interactions: 1,553 users reveal emotional support’s impact on media dependence and usage intention. 🤖💬

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🔹 Visualizing nexus of porous architecture and reactive transport in heterogeneous catalysis by deep learning computer vision and transfer learning.

Deep learning reveals key factors in porous architecture affecting reactive transport in catalysis. 📊🔍 Significant findings from PubMed article.

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🔹 Population health management of human phenotype ontology.

Population health management integrates Human Phenotype Ontology for improved health outcomes. Key findings on AI, genomics, and ethical stewardship. 📊🌍

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🔹 Proof of concept for voice based MRI scanner control using large language models in real time guided interventions.

Voice-controlled MRI scanners show 93.3% task completion in real-time interventions, enhancing efficiency and communication. 🗣️🖥️

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🔹 Systematic benchmarking of 13 AI methods for predicting cyclic peptide membrane permeability.

Benchmarking 13 AI methods for cyclic peptide permeability reveals DMPNN’s superior performance. Key insights on molecular representation and model architecture. 📊🔬

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🔹 High-Precision Contactless Stereo Acoustic Monitoring in Polysomnographic Studies of Children.

High-Precision Acoustic Monitoring in Pediatric Sleep Studies: 91.16% Accuracy with Deep Learning 🎧📊

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🔹 A cross-language analysis of urolithiasis patient online materials: Assessment across 24 European languages.

Urolithiasis online materials are complex; 20% of patients struggle with comprehension. Simplification is crucial for better adherence. 📉💧

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🔹 Artificial intelligence in pediatric healthcare: bridging potential, clinical practice, and ethical considerations.

Exploring AI’s role in pediatric healthcare: potential benefits, clinical applications, and ethical challenges. 🤖👶📊

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🔹 The Evolving Landscape of Novel and Old Biomarkers in Localized High-Risk Prostate Cancer: State of the Art, Clinical Utility, and Limitations Toward Precision Oncology.

Exploring biomarkers in high-risk prostate cancer: 50-75% relapse rate post-treatment. Genomic profiling enhances precision oncology. 📊🔬

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🔹 Survival Prediction in Allogeneic Haematopoietic Stem Cell Transplant Recipients Using Pre- and Post-Transplant Factors and Computational Intelligence.

AI model predicts allo-HSCT survival with 93.26% accuracy using 7 key factors. Study includes 564 patients. 📊🩸

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🔹 ProMUS-NET: Artificial intelligence detects more prostate cancer than urologists on micro-ultrasonography.

AI surpasses urologists in prostate cancer detection on micro-ultrasonography: 73% vs 58% sensitivity. 📊🤖

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🔹 AI in Palliative Care: A Scoping Review of Foundational Gaps and Future Directions for Responsible Innovation.

AI in Palliative Care: 125 studies reveal gaps in validation, transparency, and ethical frameworks. Future research is crucial! 🤖💔

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🔹 Bronchiectasis in patients with chronic obstructive pulmonary disease: AI-based CT quantification using the bronchial tapering ratio.

AI quantifies bronchiectasis in COPD patients, linking scores to mortality and exacerbation risks. 📊💔

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🔹 Early embryo development: the current perspective in molecular evaluation and clinical status.

Exploring embryo development: molecular insights, AI advancements, and clinical challenges in ART. 🧬🤖

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🔹 Empowering the next generation: integrating artificial intelligence education into medical training.

Integrating AI in medical training enhances skills for future doctors. Key insights from Tan et al. (2025) reveal transformative potential. 🤖📚

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🔹 Actigraphy-based step analysis for the detection of depressed mood: An explainable machine learning approach.

Actigraphy data reveals AI’s potential in detecting depression: 0.679-0.833 AUROC accuracy across demographics. 📊🧠

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That’s a wrap for this week’s digest! Stay tuned for more health & AI updates. 🚀💡

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