arXiv q-bio.QM Quantitative Methods
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[2026-01-20 Tue (UTC), no new articles found for q-bioQM Quantitative Methods]
January 20, 2026 at 6:56 AM
[2026-01-20 Tue (UTC), no new articles found for q-bioQM Quantitative Methods]
Reposted by arXiv q-bio.QM Quantitative Methods
Miriam K. Wolff, Peter Calhoun, Eleonora Maria Aiello, Yao Qin, Sam F. Royston: MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management https://arxiv.org/abs/2601.11505 https://arxiv.org/pdf/2601.11505 https://arxiv.org/html/2601.11505
January 19, 2026 at 6:33 AM
Miriam K. Wolff, Peter Calhoun, Eleonora Maria Aiello, Yao Qin, Sam F. Royston: MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management https://arxiv.org/abs/2601.11505 https://arxiv.org/pdf/2601.11505 https://arxiv.org/html/2601.11505
Reposted by arXiv q-bio.QM Quantitative Methods
Anderson, Chaudhari, Chowdhury, Jomsky, Irimia, Initiative: Graph Neural Network Reveals the Local Cortical Morphology of Brain Aging in Normal Cognition and Alzheimers Disease https://arxiv.org/abs/2601.10912 https://arxiv.org/pdf/2601.10912 https://arxiv.org/html/2601.10912
January 19, 2026 at 6:50 AM
Anderson, Chaudhari, Chowdhury, Jomsky, Irimia, Initiative: Graph Neural Network Reveals the Local Cortical Morphology of Brain Aging in Normal Cognition and Alzheimers Disease https://arxiv.org/abs/2601.10912 https://arxiv.org/pdf/2601.10912 https://arxiv.org/html/2601.10912
Ruben Taieb, Ren\'e Bruno, Pascal Chanu, Jin Yan Jin, S\'ebastien Benzekry: Mechanistic Learning for Survival Prediction in NSCLC Using Routine Blood Biomarkers and Tumor Kinetics https://arxiv.org/abs/2601.11148 https://arxiv.org/pdf/2601.11148 https://arxiv.org/html/2601.11148
January 19, 2026 at 6:51 AM
Ruben Taieb, Ren\'e Bruno, Pascal Chanu, Jin Yan Jin, S\'ebastien Benzekry: Mechanistic Learning for Survival Prediction in NSCLC Using Routine Blood Biomarkers and Tumor Kinetics https://arxiv.org/abs/2601.11148 https://arxiv.org/pdf/2601.11148 https://arxiv.org/html/2601.11148
Mohammad Reza Yousefi, Hajar Ismail Al-Tamimi, Amin Dehghani: Depression Detection Based on Electroencephalography Using a Hybrid Deep Neural Network CNN-GRU and MRMR Feature Selection https://arxiv.org/abs/2601.10959 https://arxiv.org/pdf/2601.10959 https://arxiv.org/html/2601.10959
January 19, 2026 at 6:50 AM
Mohammad Reza Yousefi, Hajar Ismail Al-Tamimi, Amin Dehghani: Depression Detection Based on Electroencephalography Using a Hybrid Deep Neural Network CNN-GRU and MRMR Feature Selection https://arxiv.org/abs/2601.10959 https://arxiv.org/pdf/2601.10959 https://arxiv.org/html/2601.10959
[2026-01-19 Mon (UTC), 2 new articles found for q-bioQM Quantitative Methods]
January 19, 2026 at 6:50 AM
[2026-01-19 Mon (UTC), 2 new articles found for q-bioQM Quantitative Methods]
Reposted by arXiv q-bio.QM Quantitative Methods
Raffaella Fiamma Cabini, et al.: Cell Behavior Video Classification Challenge, a benchmark for computer vision methods in time-lapse microscopy https://arxiv.org/abs/2601.10250 https://arxiv.org/pdf/2601.10250 https://arxiv.org/html/2601.10250
January 16, 2026 at 6:36 AM
Raffaella Fiamma Cabini, et al.: Cell Behavior Video Classification Challenge, a benchmark for computer vision methods in time-lapse microscopy https://arxiv.org/abs/2601.10250 https://arxiv.org/pdf/2601.10250 https://arxiv.org/html/2601.10250
Reposted by arXiv q-bio.QM Quantitative Methods
Mohammad Abbadi: Comparative Evaluation of Deep Learning-Based and WHO-Informed Approaches for Sperm Morphology Assessment https://arxiv.org/abs/2601.10070 https://arxiv.org/pdf/2601.10070 https://arxiv.org/html/2601.10070
January 16, 2026 at 6:33 AM
Mohammad Abbadi: Comparative Evaluation of Deep Learning-Based and WHO-Informed Approaches for Sperm Morphology Assessment https://arxiv.org/abs/2601.10070 https://arxiv.org/pdf/2601.10070 https://arxiv.org/html/2601.10070
Malinzi, Eladdadi, Ouifki, Eftimie, Madzvamuse, Byrne: A Predictive Model for Synergistic Oncolytic Virotherapy: Unveiling the Ping-Pong Mechanism and Optimal Timing of Combined Vesicular Sto... https://arxiv.org/abs/2601.10405 https://arxiv.org/pdf/2601.10405 https://arxiv.org/html/2601.10405
January 16, 2026 at 6:51 AM
Malinzi, Eladdadi, Ouifki, Eftimie, Madzvamuse, Byrne: A Predictive Model for Synergistic Oncolytic Virotherapy: Unveiling the Ping-Pong Mechanism and Optimal Timing of Combined Vesicular Sto... https://arxiv.org/abs/2601.10405 https://arxiv.org/pdf/2601.10405 https://arxiv.org/html/2601.10405
Li, Wei, Xiao, Lai, Liu, Lv, Ouyang: Robust and Generalizable Atrial Fibrillation Detection from ECG Using Time-Frequency Fusion and Supervised Contrastive Learning https://arxiv.org/abs/2601.10202 https://arxiv.org/pdf/2601.10202 https://arxiv.org/html/2601.10202
January 16, 2026 at 6:51 AM
Li, Wei, Xiao, Lai, Liu, Lv, Ouyang: Robust and Generalizable Atrial Fibrillation Detection from ECG Using Time-Frequency Fusion and Supervised Contrastive Learning https://arxiv.org/abs/2601.10202 https://arxiv.org/pdf/2601.10202 https://arxiv.org/html/2601.10202
[2026-01-16 Fri (UTC), 2 new articles found for q-bioQM Quantitative Methods]
January 16, 2026 at 6:51 AM
[2026-01-16 Fri (UTC), 2 new articles found for q-bioQM Quantitative Methods]
Reposted by arXiv q-bio.QM Quantitative Methods
Prashant C. Raju: Geometric Stability: The Missing Axis of Representations https://arxiv.org/abs/2601.09173 https://arxiv.org/pdf/2601.09173 https://arxiv.org/html/2601.09173
January 15, 2026 at 6:33 AM
Prashant C. Raju: Geometric Stability: The Missing Axis of Representations https://arxiv.org/abs/2601.09173 https://arxiv.org/pdf/2601.09173 https://arxiv.org/html/2601.09173
Reposted by arXiv q-bio.QM Quantitative Methods
Andrea Toloba, Klaus Langohr, Guadalupe G\'omez Melis: Semiparametric estimation of GLMs with interval-censored covariates via an augmented Turnbull estimator https://arxiv.org/abs/2601.08996 https://arxiv.org/pdf/2601.08996 https://arxiv.org/html/2601.08996
January 15, 2026 at 6:53 AM
Andrea Toloba, Klaus Langohr, Guadalupe G\'omez Melis: Semiparametric estimation of GLMs with interval-censored covariates via an augmented Turnbull estimator https://arxiv.org/abs/2601.08996 https://arxiv.org/pdf/2601.08996 https://arxiv.org/html/2601.08996
Reposted by arXiv q-bio.QM Quantitative Methods
Adrita Das, Peiran Jiang, Dantong Zhu, Barnabas Poczos, Jose Lugo-Martinez: Breaking the Bottlenecks: Scalable Diffusion Models for 3D Molecular Generation https://arxiv.org/abs/2601.08963 https://arxiv.org/pdf/2601.08963 https://arxiv.org/html/2601.08963
January 15, 2026 at 6:33 AM
Adrita Das, Peiran Jiang, Dantong Zhu, Barnabas Poczos, Jose Lugo-Martinez: Breaking the Bottlenecks: Scalable Diffusion Models for 3D Molecular Generation https://arxiv.org/abs/2601.08963 https://arxiv.org/pdf/2601.08963 https://arxiv.org/html/2601.08963
[2026-01-15 Thu (UTC), no new articles found for q-bioQM Quantitative Methods]
January 15, 2026 at 6:51 AM
[2026-01-15 Thu (UTC), no new articles found for q-bioQM Quantitative Methods]
Reposted by arXiv q-bio.QM Quantitative Methods
Maayan Yesharim, R. G. Bina Perl, Uri Roll, Sarig Gafny, Eli Geffen, Yoav Ram: Near-perfect photo-ID of the Hula painted frog with zero-shot deep local-feature matching https://arxiv.org/abs/2601.08798 https://arxiv.org/pdf/2601.08798 https://arxiv.org/html/2601.08798
January 14, 2026 at 6:32 AM
Maayan Yesharim, R. G. Bina Perl, Uri Roll, Sarig Gafny, Eli Geffen, Yoav Ram: Near-perfect photo-ID of the Hula painted frog with zero-shot deep local-feature matching https://arxiv.org/abs/2601.08798 https://arxiv.org/pdf/2601.08798 https://arxiv.org/html/2601.08798
Tammar Truzman, Matthew A. Lambon Ralph, Ajay D. Halai: Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions https://arxiv.org/abs/2601.08701 https://arxiv.org/pdf/2601.08701 https://arxiv.org/html/2601.08701
January 14, 2026 at 6:52 AM
Tammar Truzman, Matthew A. Lambon Ralph, Ajay D. Halai: Automated Lesion Segmentation of Stroke MRI Using nnU-Net: A Comprehensive External Validation Across Acute and Chronic Lesions https://arxiv.org/abs/2601.08701 https://arxiv.org/pdf/2601.08701 https://arxiv.org/html/2601.08701
Zhengye Pan, Jianwei Zuo, Jiajia Luo: Disentangling History and Propagation Dependencies in Cross-Subject Knee Contact Stress Prediction Using a Shared MeshGraphNet Backbone https://arxiv.org/abs/2601.08318 https://arxiv.org/pdf/2601.08318 https://arxiv.org/html/2601.08318
January 14, 2026 at 6:52 AM
Zhengye Pan, Jianwei Zuo, Jiajia Luo: Disentangling History and Propagation Dependencies in Cross-Subject Knee Contact Stress Prediction Using a Shared MeshGraphNet Backbone https://arxiv.org/abs/2601.08318 https://arxiv.org/pdf/2601.08318 https://arxiv.org/html/2601.08318
Black, Maas, Wu, Maheshwari, Kolev, Weiss, Jolley: An open-source computational framework for immersed fluid-structure interaction modeling using FEBio and MFEM https://arxiv.org/abs/2601.08266 https://arxiv.org/pdf/2601.08266 https://arxiv.org/html/2601.08266
January 14, 2026 at 6:52 AM
Black, Maas, Wu, Maheshwari, Kolev, Weiss, Jolley: An open-source computational framework for immersed fluid-structure interaction modeling using FEBio and MFEM https://arxiv.org/abs/2601.08266 https://arxiv.org/pdf/2601.08266 https://arxiv.org/html/2601.08266
Koyo Fujisaki, Osei Horikoshi, Yukitoshi Nagahara, Kengo Morohashi: Network Pharmacology Framework Characterizes Polypharmacological Properties of Dietary Flavonoids: Integration of Computati... https://arxiv.org/abs/2601.08147 https://arxiv.org/pdf/2601.08147 https://arxiv.org/html/2601.08147
January 14, 2026 at 6:52 AM
Koyo Fujisaki, Osei Horikoshi, Yukitoshi Nagahara, Kengo Morohashi: Network Pharmacology Framework Characterizes Polypharmacological Properties of Dietary Flavonoids: Integration of Computati... https://arxiv.org/abs/2601.08147 https://arxiv.org/pdf/2601.08147 https://arxiv.org/html/2601.08147
Le, Vinh, Nguyen, Li, Le, Huynh, Raj, Yang, Xu, Le: Imaging-anchored Multiomics in Cardiovascular Disease: Integrating Cardiac Imaging, Bulk, Single-cell, and Spatial Transcriptomics https://arxiv.org/abs/2601.07871 https://arxiv.org/pdf/2601.07871 https://arxiv.org/html/2601.07871
January 14, 2026 at 6:52 AM
Le, Vinh, Nguyen, Li, Le, Huynh, Raj, Yang, Xu, Le: Imaging-anchored Multiomics in Cardiovascular Disease: Integrating Cardiac Imaging, Bulk, Single-cell, and Spatial Transcriptomics https://arxiv.org/abs/2601.07871 https://arxiv.org/pdf/2601.07871 https://arxiv.org/html/2601.07871
Arturo Tozzi: From local defects to shear-organized biofilms in tonsillar crypts via computational simulations https://arxiv.org/abs/2601.07863 https://arxiv.org/pdf/2601.07863 https://arxiv.org/html/2601.07863
January 14, 2026 at 6:52 AM
Arturo Tozzi: From local defects to shear-organized biofilms in tonsillar crypts via computational simulations https://arxiv.org/abs/2601.07863 https://arxiv.org/pdf/2601.07863 https://arxiv.org/html/2601.07863
[2026-01-14 Wed (UTC), 6 new articles found for q-bioQM Quantitative Methods]
January 14, 2026 at 6:52 AM
[2026-01-14 Wed (UTC), 6 new articles found for q-bioQM Quantitative Methods]
Reposted by arXiv q-bio.QM Quantitative Methods
Johanna M. M. Bayer, et al.: Charting the velocity of brain growth and development https://arxiv.org/abs/2601.07591 https://arxiv.org/pdf/2601.07591 https://arxiv.org/html/2601.07591
January 13, 2026 at 6:50 AM
Johanna M. M. Bayer, et al.: Charting the velocity of brain growth and development https://arxiv.org/abs/2601.07591 https://arxiv.org/pdf/2601.07591 https://arxiv.org/html/2601.07591
Reposted by arXiv q-bio.QM Quantitative Methods
Haomin Wu, Zhiwei Nie, Hongyu Zhang, Zhixiang Ren: Pseudodata-guided Invariant Representation Learning Boosts the Out-of-Distribution Generalization in Enzymatic Kinetic Parameter Prediction https://arxiv.org/abs/2601.07261 https://arxiv.org/pdf/2601.07261 https://arxiv.org/html/2601.07261
January 13, 2026 at 6:34 AM
Haomin Wu, Zhiwei Nie, Hongyu Zhang, Zhixiang Ren: Pseudodata-guided Invariant Representation Learning Boosts the Out-of-Distribution Generalization in Enzymatic Kinetic Parameter Prediction https://arxiv.org/abs/2601.07261 https://arxiv.org/pdf/2601.07261 https://arxiv.org/html/2601.07261