“EfficientNet-B0 outperformed DenseNet121, achieving an accuracy of 84.6%, F1-score of 0.8899, and MCC of 0.6849.”

“These findings strongly support a human-in-the-loop (HITL) workflow in which the on-premise LLM serves as a collaborative tool, not a full replacement.”

“MedGemma 1.5, small multimodal model for real clinical data MedGemma […]”

“AI misses nearly one-third of breast cancers, study finds”

“A tool for spotting pancreatic cancer in routine CT scans has had promising results, one example of how China is racing to apply A.I. to medicine's tough problems.”

“The article quotes Wang Chen, the founder, stating that they believe financial investment is an important testing ground for AI technology.”

“The paper derives the counting DRM, the effective area, and the flash effective area from the counting DRF.”

“ProDM significantly improves CAC scoring accuracy, spatial lesion fidelity, and risk stratification performance compared with several baselines.”

“The method achieves improved performance over state-of-the-art reconstruction methods, without task-specific supervised training or fine-tuning.”

“The paper establishes error bounds for the reconstructed solution and the source term without requiring classical source conditions, and derives an expected convergence rate for the source error in a weaker topology.”

“The optimal pipeline (ANOVA feature selection with a support vector machine) achieved a mean validation accuracy of 0.79.”

“GPT-4 excels in clarity (4.88/5) but exhibits lower scores for natural writing flow (2.81/5), indicating that current systems achieve clinical accuracy but remain stylistically distinguishable from radiologist-authored text.”

“USF-MAE achieved the highest performance across all evaluation metrics, with 90.57% accuracy, 91.15% precision, 90.57% recall, and 90.71% F1-score.”

“Nuclei located in neurogenic regions consistently exhibited significantly higher phase values (optical path difference) compared to nuclei elsewhere, suggesting cell-type-specific biophysical signatures.”

“itePGDK outperformed these methods in these metrics. Particularly in short duration frames, itePGDK presents less bias and less artifacts in fast kinetics organs uptake compared with DeepKernel.”

“Virtual-Eyes improves RAD-DINO slice-level AUC from 0.576 to 0.610 and patient-level AUC from 0.646 to 0.683 (mean pooling) and from 0.619 to 0.735 (max pooling), with improved calibration (Brier score 0.188 to 0.112).”

“The measured values of $τ_{ ext{oPs}}$ in polycarbonate using both isotopes matches well with the certified reference values.”

“PGMP framework outperforms state-of-the-art methods on unseen anatomy, setting new benchmarks in efficiency and diagnostic reliability.”

“BATISNet outperforms existing methods in tooth integrity segmentation, providing more reliable and detailed data support for practical clinical applications.”

“The article's context, from ArXiv, suggests it's a research paper.”

“The method achieved superior performance compared to state-of-the-art methods on BraTS2020, with average Dice scores of 87.55, 79.36, and 62.67 for WT, TC, and ET, respectively, across fifteen missing modality combinations.”

“sCTs achieved 99% structural similarity and a Frechet inception distance of 1.01 relative to real CTs. Skull segmentation attained an average Dice coefficient of 85% across seven cranial bones, and sutures achieved 80% Dice.”

“The model reaching 96.23% accuracy, 95.58% F1-score and 94.83% specificity.”

“PathFound integrates pathological visual foundation models, vision-language models, and reasoning models trained with reinforcement learning to perform proactive information acquisition and diagnosis refinement.”

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“SOFTooth achieves state-of-the-art overall accuracy and mean IoU, with clear gains on cases involving third molars, demonstrating that rich 2D semantics can be effectively transferred to 3D tooth instance segmentation without 2D fine-tuning.”

“MedGemma-4b-it model, fine-tuned using Low-Rank Adaptation (LoRA), demonstrated superior diagnostic capability by achieving a mean test accuracy of 80.37% compared to 69.58% for the untuned GPT-4.”

“The paper demonstrates that the topology of a submanifold can be recovered with high confidence by sampling a sufficiently large number of random points.”

“The paper proposes a novel approach called Enhanced Image Representations (EIR) for generating accurate chest X-ray reports.”

“The paper introduces the first specialized dataset for weak signal feature learning, containing 13,158 spectral samples, and proposes a dual-view representation and a PDVFN model.”

“The MoraNet preserved better structural details with lower RMSE and higher SSIM values at acceleration factor of 4, and meanwhile took ten-fold faster inference time.”

“The GNN-TF model outperforms state-of-the-art methods, delivering superior predictive accuracy for predicting future tobacco usage.”

“PathoSyn provides a mathematically principled pipeline for generating high-fidelity patient-specific synthetic datasets, facilitating the development of robust diagnostic algorithms in low-data regimes.”

“GRPO recovers in-distribution performance but degrades cross-dataset transferability.”

“Lung masking should be treated as a controllable spatial prior selected to match the backbone and clinical objective, rather than applied uniformly.”

“The system delivers interpretable, real-time predictions via Explainable AI (XAI) visualizations, supporting transparent clinical decision-making.”

“The title itself provides the core concept: using spatial awareness and symmetric alignment to improve text-guided medical image segmentation.”

“Lamps' superior robustness, transferability, and clinical potential when compared to 10 baseline models.”

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“SwinCCIR effectively overcomes problems of conventional CC imaging, which are expected to be implemented in practical applications.”

“USF-MAE outperformed the DenseNet-169 baseline on all evaluation metrics.”

“The method achieves superior reconstruction quality and faster processing compared to other algorithms.”

“INTERACT-CMIL achieves consistent improvements over CNN and foundation-model (FM) baselines, with relative macro F1 gains up to 55.1% (WHO4) and 25.0% (vertical spread).”

“Modified 3D Inception architectures achieved the best overall performance, with a root mean squared error (RMSE) of 6.79%.”

“The paper reports high Dice Similarity Coefficients (DSC) for whole tumor (WT), enhancing tumor (ET), and tumor core (TC) across multiple BraTS datasets, indicating improved segmentation accuracy.”

“(No specific quote available from the provided information)”

“FluenceFormer with Swin UNETR achieves the strongest performance among the evaluated models and improves over existing benchmark CNN and single-stage methods, reducing Energy Error to 4.5% and yielding statistically significant gains in structural fidelity (p < 0.05).”

“DeFloMat achieves state-of-the-art accuracy ($43.32\% ext{ } AP_{10:50}$) in only $3$ inference steps, which represents a $1.4 imes$ performance improvement over DiffusionDet's maximum converged performance ($31.03\% ext{ } AP_{10:50}$ at $4$ steps).”

“The paper introduces a multi-view latent representation learning framework based on variational autoencoders (VAE) to integrate complementary radiomic features derived from post-contrast T1-weighted (T1Gd) and Fluid-Attenuated Inversion Recovery (FLAIR) magnetic resonance imaging (MRI).”

“TissueXplorer showed smaller dose distribution differences from the ground truth plan than the conventional stoichiometric calibration method.”