“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.”

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

“The study demonstrates the feasibility of anatomically realistic $μ$FE simulations at this scale, with models containing over $8\times10^{8}$ DOFs.”

“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).”

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“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.”

“BSFfast provides precomputed, tabulated effective BSF cross sections for a wide class of phenomenologically relevant models, including highly excited bound states and, where applicable, the full network of radiative bound-to-bound transitions.”

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“LAM3C achieves higher performance than the previous self-supervised methods on indoor semantic and instance segmentation.”

“The real constraint that drives the design: By Spring 2026, large institutions are preparing to archive or remove non-accessible content rather than remediate it at scale.”

“Reasoning models process 44.5% fewer bytes than standard models while maintaining equivalent correctness.”

“The paper focuses on unsupervised anomaly detection, a method that doesn't require labeled data.”

“BertsWin achieves a 5.8x acceleration in semantic convergence and a 15-fold reduction in training epochs compared to standard ViT-MAE baselines.”

“LLM から BigQuery を「自然言語で気軽に叩ける」ようになると、意図せず大量スキャンが発生し、BigQuery 利用料が膨れ上がるリスクがあります。”

“Our approach leverages an intermediate spherical coordinate space to bridge anatomical surface topology with volumetric anatomy, enabling consistent and anatomically accurate alignment.”

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“The research uses multimodal LLMs to construct historical datasets.”

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“The article focuses on a specific medical application of AI, likely involving image analysis and potentially machine learning techniques.”

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“The study focuses on using PDE modeling for immunotherapy response prediction in Glioblastoma patients.”

“The article presents results from the MICCAI 2024 challenge.”

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“The study focuses on self-supervised learning for improving MRI resolution.”

“The research focuses on unsupervised parallel MRI reconstruction.”

“The article likely discusses the dataset's size, composition, and potential applications in medical AI.”

“The research focuses on using Physics-Informed Diffusion Models for MRI.”

“The article focuses on MRI-based multiclass (4-class) Alzheimer's Disease Classification.”

“The article focuses on a specific application (dual-spectral CT) and a novel architecture (ResDynUNet++) for image reconstruction.”

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“The article's context indicates the research focuses on coronary artery segmentation from CCTA scans.”

“The research focuses on integrating LLMs and VLMs.”

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“SIP is a dataset of disaggregated construction-phase 3D scans for semantic segmentation and scene understanding.”

“The article's context revolves around the 3DTeethLand challenge focusing on detecting dental landmarks.”

“The paper likely details the specific architecture of the diffusion model, the implicit neural representation used, and the regularization techniques employed. It would also include experimental results demonstrating the effectiveness of the proposed method compared to existing techniques.”

“Lung cancer screening via computed tomography (CT), which provides a detailed 3D image of the lungs, has been shown to reduce mortality in high-risk populations by at least 20% by detecting potential signs of cancers earlier.”

“We discuss the company’s work building products for interpreting head CT scans and chest x-rays.”