Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph | Paper Citation Record

Observation b4d9557f-1bc1-4a92-937d-7dda081afda6 · outbound

This paper cites Programming cellular alignment in engineered cardiac tissue via bioprinting anisotropic organ building blocks.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Programming cellular alignment in engineered cardiac tissue via bioprinting anisotropic organ building blocks

Reference 1

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This paper cites Decoding rejuvenating effects of mechanical loading on skeletal aging using in vivo µct imaging and deep learning.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Decoding rejuvenating effects of mechanical loading on skeletal aging using in vivo µct imaging and deep learning

Reference 2

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This paper cites Sarcomere alignment is regulated by myocyte shape.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Sarcomere alignment is regulated by myocyte shape

Reference 3

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This paper cites Measurement and analysis of sarcomere length in rat cardiomyocytes in situ and in vitro.American Journal of Physiology-Heart and Circulatory Physiology, 298(5):H1616–H1625, 2010.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Measurement and analysis of sarcomere length in rat cardiomyocytes in situ and in vitro.American Journal of Physiology-Heart and Circulatory Physiology, 298(5):H1616–H1625, 2010

Reference 4

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This paper cites Automated image analysis system for studying cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Automated image analysis system for studying cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes

Reference 5

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This paper cites Automated sarcomere structure analysis for studying cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Automated sarcomere structure analysis for studying cardiotoxicity in human pluripotent stem cell-derived cardiomyocytes

Reference 6

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This paper cites Cellprofiler: image analysis software for identifying and quantifying cell phenotypes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Cellprofiler: image analysis software for identifying and quantifying cell phenotypes

Reference 7

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This paper cites Deep learning for cardiac image segmentation: a review.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Deep learning for cardiac image segmentation: a review

Reference 8

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This paper cites A simple framework for contrastive learning of visual representations.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A simple framework for contrastive learning of visual representations

Reference 9

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This paper cites Multimodal object detection via probabilistic ensembling.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Multimodal object detection via probabilistic ensembling

Reference 10

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Observation 66571397-869a-4d96-80d8-77e795501d36 · outbound

This paper cites Multiscale characteri- zation of heart failure.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Multiscale characteri- zation of heart failure

Reference 11

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Observation 3aa1215b-35bb-49d8-b3f0-e621e758b3f3 · outbound

This paper cites Cardiac sarcomere mechanics in health and disease.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Cardiac sarcomere mechanics in health and disease

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:03.223357Z

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Observation 16a645a5-7c69-4079-8d09-4f41d19ae05d · outbound

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

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Imagenet: A large-scale hierarchical image database

Reference 13

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This paper cites Machine learning identifies remodeling patterns in human lung extracellular matrix.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Machine learning identifies remodeling patterns in human lung extracellular matrix

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:03.206395Z

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This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A density-based algorithm for discovering clusters in large spatial databases with noise

Reference 15

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Observation bcf01f74-40d0-4589-bd6c-0817a3a6b9d0 · outbound

This paper cites Induced pluripotent stem cell-derived cardiomyocyte in vitro models: benchmarking progress and ongoing challenges.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Induced pluripotent stem cell-derived cardiomyocyte in vitro models: benchmarking progress and ongoing challenges

Reference 16

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This paper cites Serial dependence in visual perception.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Serial dependence in visual perception

Reference 17

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This paper cites ExKMC: Expanding Explainable $k$-Means Clustering.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph ExKMC: Expanding Explainable $k$-Means Clustering

Reference 18

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Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Unresolved cited work

Reference 19

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This paper cites Cell states beyond transcriptomics: Integrating structural organization and gene expression in hipsc-derived cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Cell states beyond transcriptomics: Integrating structural organization and gene expression in hipsc-derived cardiomyocytes

Reference 20

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This paper cites Self-organization of muscle cell structure and function.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Self-organization of muscle cell structure and function

Reference 21

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This paper cites Statistical and structural approaches to texture.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Statistical and structural approaches to texture

Reference 22

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This paper cites A data-driven computational model for engineered cardiac microtissues.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A data-driven computational model for engineered cardiac microtissues

Reference 23

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This paper cites Right ventricular myocardial mechanics: Multi-modal deformation, microstructure, modeling, and comparison to the left ventricle.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Right ventricular myocardial mechanics: Multi-modal deformation, microstructure, modeling, and comparison to the left ventricle

Reference 24

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Observation bc02a867-5ff0-4b0c-ab99-aa1ca6e2fd57 · outbound

This paper cites Self-supervised deep learning encodes high-resolution features of protein subcellular localization.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Self-supervised deep learning encodes high-resolution features of protein subcellular localization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:03.105660Z

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Observation 0e93db18-3464-40eb-8b73-42702aa0e9a0 · outbound

This paper cites Structural immaturity of human ipsc-derived cardiomyocytes: in silico investigation of effects on function and disease modeling.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Structural immaturity of human ipsc-derived cardiomyocytes: in silico investigation of effects on function and disease modeling

Reference 26

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This paper cites A generalized laplacian of gaussian filter for blob detection and its applications.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A generalized laplacian of gaussian filter for blob detection and its applications

Reference 27

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This paper cites A guideline of selecting and reporting intraclass correlation coefficients for reliability research.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A guideline of selecting and reporting intraclass correlation coefficients for reliability research

Reference 28

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Observation 870b783b-bec0-4df3-8f03-dad0cddece6d · outbound

This paper cites SarcNet: A Novel AI-based Framework to Automatically Analyze and Score Sarcomere Organizations in Fluorescently Tagged hiPSC-CMs.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph SarcNet: A Novel AI-based Framework to Automatically Analyze and Score Sarcomere Organizations in Fluorescently Tagged hiPSC-CMs

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-08-09T22:50:02.692400Z

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This paper cites Rater effects on essay scoring: A multilevel analysis of severity drift, central tendency, and rater experience.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Rater effects on essay scoring: A multilevel analysis of severity drift, central tendency, and rater experience

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:03.064729Z

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Observation 122b7940-ea6b-416b-b61b-45015a6b0f43 · outbound

This paper cites A deep learning approach to estimate chemically-treated collagenous tissue nonlinear anisotropic stress-strain responses from microscopy images.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A deep learning approach to estimate chemically-treated collagenous tissue nonlinear anisotropic stress-strain responses from microscopy images

Reference 31

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Observation dee46289-225f-499a-8337-8f573a4cf976 · outbound

This paper cites Human induced pluripotent stem cell for modeling cardiovascular diseases.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Human induced pluripotent stem cell for modeling cardiovascular diseases

Reference 32

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Observation 3100af5f-ffae-45a8-889f-980485845847 · outbound

This paper cites Drug screening using a library of human induced pluripotent stem cell–derived cardiomyocytes reveals disease-specific patterns of cardiotoxicity.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Drug screening using a library of human induced pluripotent stem cell–derived cardiomyocytes reveals disease-specific patterns of cardiotoxicity

Reference 33

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Observation 787e8d7e-2ff1-4ab1-81bd-f89587a5c3aa · outbound

This paper cites A survey on deep learning in medical image analysis.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A survey on deep learning in medical image analysis

Reference 34

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This paper cites Least squares quantization in pcm.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Least squares quantization in pcm

Reference 35

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This paper cites Lorensen and Harvey E.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Lorensen and Harvey E

Reference 36

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Observation d3ea3677-ad65-4ae4-9261-4ac580bf1da7 · outbound

This paper cites The vertebrate muscle z-disc: sarcomere anchor for structure and signalling.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph The vertebrate muscle z-disc: sarcomere anchor for structure and signalling

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:03.009196Z

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Observation a8943896-6bbf-4741-b9f4-1a376528da4f · outbound

This paper cites Theory of edge detection.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Theory of edge detection

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.997865Z

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Observation a10b000f-88e3-4333-aacf-a594dd10a091 · outbound

This paper cites 2024 heart disease and stroke statistics: a report of us and global data from the american heart association.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph 2024 heart disease and stroke statistics: a report of us and global data from the american heart association

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.986414Z

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Observation 800ad9b9-9b41-43f8-9f89-b58eed649f6c · outbound

This paper cites Transcriptome profiling of patient-specific human ipsc- cardiomyocytes predicts individual drug safety and efficacy responses in vitro.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Transcriptome profiling of patient-specific human ipsc- cardiomyocytes predicts individual drug safety and efficacy responses in vitro

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.975520Z

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Observation ea786a6e-12e1-4d28-9119-9e951bba12ef · outbound

This paper cites Sarcgraph: A python package for analyzing the contractile behavior of pluripotent stem cell-derived cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Sarcgraph: A python package for analyzing the contractile behavior of pluripotent stem cell-derived cardiomyocytes

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.964616Z

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Observation 55106c7f-59d2-4f9d-befe-a2e97ac9a84b · outbound

This paper cites Investigating deep learning model calibration for classification problems in mechanics.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Investigating deep learning model calibration for classification problems in mechanics

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.954747Z

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Observation 5834c343-556e-4fbc-8957-27e44fc91c2f · outbound

This paper cites Striated myocyte structural integrity: Automated analysis of sarcomeric z-discs.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Striated myocyte structural integrity: Automated analysis of sarcomeric z-discs

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.944254Z

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Observation 67810c2b-25b4-4d02-9589-29b78b328db9 · outbound

This paper cites Explainable k-means and k-medians clustering.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Explainable k-means and k-medians clustering

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.933551Z

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Observation f3108aca-50a4-4f71-a788-ec7da9c29b8c · outbound

This paper cites Algorithms for hierarchical clustering: an overview, ii.Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(6):e1219, 2017.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Algorithms for hierarchical clustering: an overview, ii.Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 7(6):e1219, 2017

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.923719Z

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Observation ad3990e2-f4da-447e-b142-86e94992e524 · outbound

This paper cites Derivation of human induced pluripotent stem cells for cardiovascular disease modeling.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Derivation of human induced pluripotent stem cells for cardiovascular disease modeling

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.913964Z

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Observation 6e778a00-edf9-4926-9275-60ac0b0e6968 · outbound

This paper cites Independent regulation of z-lines and m-lines during sarcomere assembly in cardiac myocytes revealed by the automatic image analysis software sarcapp.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Independent regulation of z-lines and m-lines during sarcomere assembly in cardiac myocytes revealed by the automatic image analysis software sarcapp

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.903691Z

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Observation a8a3334b-927e-4d32-bebd-5a84847d32af · outbound

This paper cites Sarcomere protein gene mutations in hypertrophic cardiomyopathy of the elderly.Circulation, 105(4):446–451, 2002.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Sarcomere protein gene mutations in hypertrophic cardiomyopathy of the elderly.Circulation, 105(4):446–451, 2002

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.892151Z

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Observation ecb55910-7cb4-4b38-837b-a301244cdc1c · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph DINOv2: Learning Robust Visual Features without Supervision

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T22:50:02.416520Z

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Observation 21efa139-783f-4596-959e-5a15a092f486 · outbound

This paper cites A threshold selection method from gray-level histograms.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A threshold selection method from gray-level histograms

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T22:50:02.420076Z

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Observation e8261208-8a63-4bbd-b49b-7bfac62754f9 · outbound

This paper cites Tracking single hipsc-derived cardiomyocyte contractile function using contrax an efficient pipeline for traction force measurement.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Tracking single hipsc-derived cardiomyocyte contractile function using contrax an efficient pipeline for traction force measurement

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.881685Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d8faa922-85a7-4b11-8be4-354ef01279e9 · outbound

This paper cites Sarcoptim for imagej: high-frequency online sarcomere length computing on stimulated cardiomyocytes.American Journal of Physiology-Cell Physiology, 311(2):C277–C283, 2016.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Sarcoptim for imagej: high-frequency online sarcomere length computing on stimulated cardiomyocytes.American Journal of Physiology-Cell Physiology, 311(2):C277–C283, 2016

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.870794Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 23469478-fd53-4bd9-81aa-a1a294d59675 · outbound

This paper cites Structural phenotyping of stem cell-derived cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Structural phenotyping of stem cell-derived cardiomyocytes

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.859543Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4ce05f87-da0e-4a67-ac8f-a9210cb7c03e · outbound

This paper cites Multi-imaging method to assay the contractile mechanical output of micropatterned human ipsc-derived cardiac myocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Multi-imaging method to assay the contractile mechanical output of micropatterned human ipsc-derived cardiac myocytes

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.849009Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 324a60fd-0c7f-47a3-a936-1c7aaa1de643 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph U-net: Convolutional networks for biomedical image segmentation

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T22:50:02.436619Z

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Observation 87b58bda-5571-4550-8ab6-cfad876ba7ca · outbound

This paper cites Modeling cardiovascular diseases with hipsc-derived cardiomyocytes in 2d and 3d cultures.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Modeling cardiovascular diseases with hipsc-derived cardiomyocytes in 2d and 3d cultures

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.831624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b06fecdf-bf30-49dd-9c85-2d32d45863a8 · outbound

This paper cites A survey of decision tree classifier methodology.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A survey of decision tree classifier methodology

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.821221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f911fc4e-5f60-4ca2-a756-4981bba112e9 · outbound

This paper cites Quality metrics for stem cell-derived cardiac myocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Quality metrics for stem cell-derived cardiac myocytes

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.810635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ab77ffec-5c89-452a-aaad-416bcc72d7f8 · outbound

This paper cites Induced pluripotent stem cell technology: a decade of progress.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Induced pluripotent stem cell technology: a decade of progress

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.801099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9eea360e-959c-4558-8ff7-315fdcbf8b1f · outbound

This paper cites Intraclass correlations: uses in assessing rater reliability.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Intraclass correlations: uses in assessing rater reliability

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.791526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ac97b7e1-0adb-4896-9ecd-20976860ca33 · outbound

This paper cites Harding, Neda Mohammadi, Valeria V Orlova, Milena Bellin, Christine L Mummery, and Berend J van Meer.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Harding, Neda Mohammadi, Valeria V Orlova, Milena Bellin, Christine L Mummery, and Berend J van Meer

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.781802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fab58a7c-9171-411e-abf5-57de87a83a41 · outbound

This paper cites High content analysis identifies unique morphological features of reprogrammed cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph High content analysis identifies unique morphological features of reprogrammed cardiomyocytes

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.772056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 02175a73-6628-4b4e-9484-c40dbad2b550 · outbound

This paper cites Efficientnetv2: Smaller models and faster training.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Efficientnetv2: Smaller models and faster training

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.761411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4bb4e069-b161-412d-81ab-22af7a065f98 · outbound

This paper cites Toepfer, Arun Sharma, Marcelo Cicconet, Amanda C.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Toepfer, Arun Sharma, Marcelo Cicconet, Amanda C

Reference 64

Resolution: verified exact; doi, observed 2026-08-09T22:50:02.519588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 33ad987c-a1b5-49bb-b28e-da6d20a686bc · outbound

This paper cites Schönberger, Juan Nunez-Iglesias, François Boulogne, Joshua D.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Schönberger, Juan Nunez-Iglesias, François Boulogne, Joshua D

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T22:50:02.468762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b52cfbcb-ba7f-4dd8-81aa-0b11452beb6f · outbound

This paper cites A survey on semi-supervised learning.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph A survey on semi-supervised learning

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.751054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d152ae1-ff95-464e-9ffb-d70639532bf4 · outbound

This paper cites Modelling inherited cardiac disease using human induced pluripotent stem cell-derived cardiomyocytes: progress, pitfalls, and potential.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Modelling inherited cardiac disease using human induced pluripotent stem cell-derived cardiomyocytes: progress, pitfalls, and potential

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.740300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6cc47a81-f6fb-429d-a672-0a0b503d7c94 · outbound

This paper cites S4l: Self-supervised semi-supervised learning.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph S4l: Self-supervised semi-supervised learning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.729810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1ec2c0d1-cc3d-4626-a413-a965cd0e4954 · outbound

This paper cites Sarc-graph: Automated segmentation, tracking, and analysis of sarcomeres in hipsc-derived cardiomyocytes.

Quantifying HiPSC-CM Structural Organization at Scale with Deep Learning-Enhanced SarcGraph Sarc-graph: Automated segmentation, tracking, and analysis of sarcomeres in hipsc-derived cardiomyocytes

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:50:02.719750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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