Paper Citation Record · LEDGER

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction

As of 11 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 4 inbound Pith citation observations for arXiv:2502.00631.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.00631 v2

Coverage vector

measured 37 of 37 reference resolution

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measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:33:21.483114Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-11T09:10:59.747054Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation f97ded1d-7618-4a47-99e2-f095cb72fb68 · outbound

This paper cites Bone health and osteoporosis,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Bone health and osteoporosis,

Reference 1

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Observation 630e7fdc-4a2a-476f-89e5-3141fb6bd9bc · outbound

This paper cites Deep learning for bone mineral density and t-score prediction from chest x-rays: A multicenter study,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Deep learning for bone mineral density and t-score prediction from chest x-rays: A multicenter study,

Reference 2

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Observation be496ab3-5d8c-48f3-ac00-87d5e5d91ccf · outbound

This paper cites Advancing osteoporosis diagnosis and fracture prediction: role of quantitative ct and future research directions,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Advancing osteoporosis diagnosis and fracture prediction: role of quantitative ct and future research directions,

Reference 3

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Observation b6630816-d53a-4c33-b98d-3185ce22b19a · outbound

This paper cites Efficient Learning With Sine-Activated Low-rank Matrices.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Efficient Learning With Sine-Activated Low-rank Matrices

Reference 4

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Observation c326ea45-2a83-4414-9511-80d476d8b63d · outbound

This paper cites Thin-thick adapter: Segmenting thin scans using thick annotations,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Thin-thick adapter: Segmenting thin scans using thick annotations,

Reference 5

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Observation 3162e6c5-d179-4d55-a16d-0963b5284949 · outbound

This paper cites Bhsd: A 3d multi-class brain hemorrhage segmentation dataset,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Bhsd: A 3d multi-class brain hemorrhage segmentation dataset,

Reference 6

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Observation a3a3fa95-ac7a-4914-bd6e-a43bbc5956e8 · outbound

This paper cites SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation

Reference 7

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Observation f55303f0-05f4-4cb6-965e-04d10eec7d69 · outbound

This paper cites ESA: Annotation-Efficient Active Learning for Semantic Segmentation.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction ESA: Annotation-Efficient Active Learning for Semantic Segmentation

Reference 8

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Observation e4876baa-efca-4dc5-aa53-28f138cd7736 · outbound

This paper cites Meddet: Generative adversarial distillation for efficient cervical disc herniation detection,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Meddet: Generative adversarial distillation for efficient cervical disc herniation detection,

Reference 9

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Observation 57360a3e-2d4f-4112-8763-de987401d717 · outbound

This paper cites MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction MSDet: Receptive Field Enhanced Multiscale Detection for Tiny Pulmonary Nodule

Reference 10

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Observation f3c5753f-0714-47fa-9c08-3035b0bb4e4a · outbound

This paper cites SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

Reference 11

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This paper cites GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction GAMED-Snake: Gradient-aware Adaptive Momentum Evolution Deep Snake Model for Multi-organ Segmentation

Reference 12

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Observation 856c2003-f1a0-403f-a3d7-b976bee6c834 · outbound

This paper cites Jointvit: Modeling oxygen saturation levels with joint supervision on long-tailed octa,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Jointvit: Modeling oxygen saturation levels with joint supervision on long-tailed octa,

Reference 13

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Observation 3b046c7c-7ebb-47fb-866c-71a85340a3fe · outbound

This paper cites MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training

Reference 14

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Observation 180cf6ee-2399-422e-9f15-40b06094dbcd · outbound

This paper cites Can rotational thromboelastometry rapidly identify theragnostic targets in isolated traumatic brain injury?,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Can rotational thromboelastometry rapidly identify theragnostic targets in isolated traumatic brain injury?,

Reference 15

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Observation 38884f2f-8657-48dc-8a7f-6bd0e7c8c521 · outbound

This paper cites A landmark-based approach for instability predic- tion in distal radius fractures,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction A landmark-based approach for instability predic- tion in distal radius fractures,

Reference 16

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Observation e364111e-b08d-4238-968b-20fab7aac35a · outbound

This paper cites Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Medical Artificial Intelligence for Early Detection of Lung Cancer: A Survey

Reference 17

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Observation 08298bfc-4e87-4c32-bf2b-f84487b56a62 · outbound

This paper cites ProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction ProjectedEx: Enhancing Generation in Explainable AI for Prostate Cancer

Reference 18

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This paper cites CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

Reference 19

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Observation 0b69927c-7ba4-4d9a-900e-c0bf47e65247 · outbound

This paper cites Totalsegmentator: robust segmentation of 104 anatomic structures in ct images,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Totalsegmentator: robust segmentation of 104 anatomic structures in ct images,

Reference 20

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Observation fafd0ab3-5331-48cc-85e2-fd6f0eeee4d4 · outbound

This paper cites Survey on deep learning with class imbalance,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Survey on deep learning with class imbalance,

Reference 21

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Observation d4e31741-2314-4006-9cd8-b8162a10e100 · outbound

This paper cites A deep learning approach to diabetes diagnosis,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction A deep learning approach to diabetes diagnosis,

Reference 22

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Observation da4546ca-199f-411a-bb71-49e2491bfe4b · outbound

This paper cites Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Automated bone mineral density prediction and fracture risk assessment using plain radiographs via deep learning,

Reference 23

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Observation 29d61d2f-7d69-475f-9a9c-e82c5dcd9291 · outbound

This paper cites Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network,

Reference 24

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Observation a9fa940f-3cc2-4fb2-aacb-f3ba3a7c1692 · outbound

This paper cites Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in frax underutilization,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Automated opportunistic osteoporotic fracture risk assessment using computed tomography scans to aid in frax underutilization,

Reference 25

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Observation ebdc4ecc-ed91-42f6-95bf-d9140c9b7c35 · outbound

This paper cites Deep learning for biomarker regression: application to osteoporosis and emphysema on chest ct scans,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Deep learning for biomarker regression: application to osteoporosis and emphysema on chest ct scans,

Reference 26

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Observation 96354f3b-7fec-44f5-b260-61b6d60c456a · outbound

This paper cites Opportunistic osteoporosis screening in multi-detector ct images using deep convolutional neural networks,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Opportunistic osteoporosis screening in multi-detector ct images using deep convolutional neural networks,

Reference 27

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This paper cites ReMix: Calibrated Resampling for Class Imbalance in Deep learning.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction ReMix: Calibrated Resampling for Class Imbalance in Deep learning

Reference 28

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This paper cites Class-balanced loss based on effective number of samples,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Class-balanced loss based on effective number of samples,

Reference 29

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Observation ffa631f9-0887-441e-a9f5-e70ae52f459d · outbound

This paper cites Long-tailed Recognition by Learning from Latent Categories.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Long-tailed Recognition by Learning from Latent Categories

Reference 30

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Observation 97c645de-bbba-4eec-9535-d467511f3451 · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 31

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This paper cites Learning multiple layers of features from tiny images,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Learning multiple layers of features from tiny images,

Reference 32

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This paper cites Imagenet: A large-scale hierarchical image database,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Imagenet: A large-scale hierarchical image database,

Reference 33

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This paper cites The Road Less Scheduled.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction The Road Less Scheduled

Reference 34

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This paper cites World Health Organization, 1994.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction World Health Organization, 1994

Reference 35

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This paper cites Segreg: Segmenting oars by registering mr images and ct annotations,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Segreg: Segmenting oars by registering mr images and ct annotations,

Reference 36

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Observation c2c73e4b-684c-46bb-84c7-5d2b528cedc1 · outbound

This paper cites Cer- vicothoracic volumetric bone mineral density assessed by opportunistic qct may be a reliable marker for osteoporosis in adults,.

MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction Cer- vicothoracic volumetric bone mineral density assessed by opportunistic qct may be a reliable marker for osteoporosis in adults,

Reference 37

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Pith citing papers

Observation f20ff4ca-29de-4203-9002-92966ce7b9db · inbound

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation cites this paper.

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction

Reference 32

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Observation 7d24c326-c83a-4d8b-8c39-9e26e1ea20d8 · inbound

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation cites this paper.

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction

Reference 27

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Observation 0df2f648-f6ae-4709-9ad5-6d100bc35406 · inbound

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation cites this paper.

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction

Reference 28

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Observation 625dc31c-35f6-456f-9c55-df9af2fb04f6 · inbound

EGAD: Entropy-Guided Adaptive Distillation for Token-Level Knowledge Transfer cites this paper.

EGAD: Entropy-Guided Adaptive Distillation for Token-Level Knowledge Transfer MedConv: Convolutions Beat Transformers on Long-Tailed Bone Density Prediction

Reference 28

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