Joshua Yao-Yu Lin
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View article: Property Enhancer – a data efficient multi-objective approach for functional antibody optimization
Property Enhancer – a data efficient multi-objective approach for functional antibody optimization Open
In-silico antibody lead optimization remains challenging due to scarce high-quality data, costly experimental validation, and the need to jointly optimize multiple developability properties. Discovery workflows often rely on high-throughpu…
View article: Targeted spiral ganglion neuron degeneration in parvalbumin-Cre neonatal mice
Targeted spiral ganglion neuron degeneration in parvalbumin-Cre neonatal mice Open
The spiral ganglion neurons (SGNs) are the primary afferent neurons in the cochlea; damage to the SGNs leads to irreversible hearing impairment. Mouse models that allow selective SGN degeneration while sparing other cell types in the cochl…
View article: DyAb: sequence-based antibody design and property prediction in a low-data regime
DyAb: sequence-based antibody design and property prediction in a low-data regime Open
Protein therapeutic design and property prediction are frequently hampered by data scarcity. Here we propose a new model, DyAb, that addresses these issues by leveraging a pair-wise representation to predict differences in protein properti…
View article: The effectiveness and safety of lifestyle medicine and integrative therapies in inflammatory arthritis: an umbrella review using a hierarchical evidence gathering approach
The effectiveness and safety of lifestyle medicine and integrative therapies in inflammatory arthritis: an umbrella review using a hierarchical evidence gathering approach Open
Objective An umbrella review was conducted to provide a comprehensive evaluation of the evidence on lifestyle medicine and integrative therapies for inflammatory arthritis. Methods Five electronic databases were searched for umbrella revie…
View article: LenSiam: Self-Supervised Learning on Strong Gravitational Lens Images
LenSiam: Self-Supervised Learning on Strong Gravitational Lens Images Open
Self-supervised learning has been known for learning good representations from data without the need for annotated labels. We explore the simple siamese (SimSiam) architecture for representation learning on strong gravitational lens images…
View article: Supplementary Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology
Supplementary Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology Open
Supplementary methods, figures and tables
View article: Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology
Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology Open
Purpose:Glioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted to examine GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical pl…
View article: Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology
Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology Open
Purpose:Glioblastoma (GBM) is one of the deadliest cancers with no cure. While conventional MRI has been widely adopted to examine GBM clinically, accurate neuroimaging assessment of tumor histopathology for improved diagnosis, surgical pl…
View article: Supplementary Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology
Supplementary Data from Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology Open
Supplementary methods, figures and tables
View article: SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers
SupSiam: Non-contrastive Auxiliary Loss for Learning from Molecular Conformers Open
We investigate Siamese networks for learning related embeddings for augmented samples of molecular conformers. We find that a non-contrastive (positive-pair only) auxiliary task aids in supervised training of Euclidean neural networks (E3N…
View article: AGNet: weighing black holes with deep learning
AGNet: weighing black holes with deep learning Open
Supermassive black holes (SMBHs) are commonly found at the centres of most massive galaxies. Measuring SMBH mass is crucial for understanding the origin and evolution of SMBHs. Traditional approaches, on the other hand, necessitate the col…
View article: Fully Automated Deep Learning-enabled Detection for Hepatic Steatosis on Computed Tomography: A Multicenter International Validation Study
Fully Automated Deep Learning-enabled Detection for Hepatic Steatosis on Computed Tomography: A Multicenter International Validation Study Open
Despite high global prevalence of hepatic steatosis, no automated diagnostics demonstrated generalizability in detecting steatosis on multiple international datasets. Traditionally, hepatic steatosis detection relies on clinicians selectin…
View article: Strong Gravitational Lensing Parameter Estimation with Vision Transformer
Strong Gravitational Lensing Parameter Estimation with Vision Transformer Open
Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant ($H_{0}$) tension. The commonly used Ma…
View article: 537 Laser-Assisted Drug Delivery in the Treatment of Hypertrophic and Keloid Scars: A Systematic Review
537 Laser-Assisted Drug Delivery in the Treatment of Hypertrophic and Keloid Scars: A Systematic Review Open
Introduction Hypertrophic scars (HTS) and keloids (K) cause significant morbidity and disfigurement. Care of HTS and keloids range from less invasive treatments, such as pressure garments and silicone products, to more invasive treatments,…
View article: 36 Common Data Elements (CDE) in Burn Care Documentation: A Single-center Retrospective Review
36 Common Data Elements (CDE) in Burn Care Documentation: A Single-center Retrospective Review Open
Introduction Thorough documentation is an important component of delivering quality patient care. Documentation of common data elements (CDE), defined as a precise question with a specified set of responses used across multiple databases o…
View article: Ingredients of a Natural Oral Nutritional Supplement and Their Role in the Treatment of Osteoarthritis
Ingredients of a Natural Oral Nutritional Supplement and Their Role in the Treatment of Osteoarthritis Open
Osteoarthritis is a prevalent degenerative disease affecting a large portion of the world’s aging population. Currently, nonsteroidal anti-inflammatory drugs and acetaminophen are first-line medications for treating osteoarthritis patients…
View article: VLBInet: Radio Interferometry Data Classification for EHT with Neural Networks
VLBInet: Radio Interferometry Data Classification for EHT with Neural Networks Open
The Event Horizon Telescope (EHT) recently released the first horizon-scale images of the black hole in M87. Combined with other astronomical data, these images constrain the mass and spin of the hole as well as the accretion rate and magn…
View article: Galaxy Morphological Classification with Efficient Vision Transformer
Galaxy Morphological Classification with Efficient Vision Transformer Open
Quantifying the morphology of galaxies has been an important task in astrophysics to understand the formation and evolution of galaxies. In recent years, the data size has been dramatically increasing due to several on-going and upcoming s…
View article: AGNet: Weighing Black Holes with Deep Learning
AGNet: Weighing Black Holes with Deep Learning Open
Supermassive black holes (SMBHs) are ubiquitously found at the centers of most massive galaxies. Measuring SMBH mass is important for understanding the origin and evolution of SMBHs. However, traditional methods require spectroscopic data …
View article: A Deep-learning Approach for Live Anomaly Detection of Extragalactic Transients
A Deep-learning Approach for Live Anomaly Detection of Extragalactic Transients Open
There is a shortage of multiwavelength and spectroscopic follow-up capabilities given the number of transient and variable astrophysical events discovered through wide-field optical surveys such as the upcoming Vera C. Rubin Observatory an…
View article: Inferring Black Hole Properties from Astronomical Multivariate Time\n Series with Bayesian Attentive Neural Processes
Inferring Black Hole Properties from Astronomical Multivariate Time\n Series with Bayesian Attentive Neural Processes Open
Among the most extreme objects in the Universe, active galactic nuclei (AGN)\nare luminous centers of galaxies where a black hole feeds on surrounding\nmatter. The variability patterns of the light emitted by an AGN contain\ninformation ab…
View article: Deep neural network analysis employing diffusion basis spectrum imaging metrics as classifiers improves prostate cancer detection and grading
Deep neural network analysis employing diffusion basis spectrum imaging metrics as classifiers improves prostate cancer detection and grading Open
Structural and cellular complexity of prostatic histopathology limits the accuracy of noninvasive detection and grading of prostate cancer (PCa). We addressed this limitation by employing a novel diffusion basis spectrum imaging (DBSI) to …
View article: Diffusion histology imaging differentiates distinct pediatric brain tumor histology
Diffusion histology imaging differentiates distinct pediatric brain tumor histology Open
High-grade pediatric brain tumors exhibit the highest cancer mortality rates in children. While conventional MRI has been widely adopted for examining pediatric high-grade brain tumors clinically, accurate neuroimaging detection and differ…
View article: deeplenstronomy: A dataset simulation package for strong gravitational lensing
deeplenstronomy: A dataset simulation package for strong gravitational lensing Open
Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more example systems to train the algorithms than have presently be…
View article: Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains Open
We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, "Large-Scale Gravitational Lens Modeling wit…
View article: Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant - Datasets, Trained Models, BNN Samples, and MCMC Chains Open
We publish the training/validation/test datasets, trained model weights, configuration files, Bayesian neural network samples, and MCMC chains used to produce the figures in the LSST DESC paper, "Large-Scale Gravitational Lens Modeling wit…
View article: AGNet: Weighing Black Holes with Machine Learning
AGNet: Weighing Black Holes with Machine Learning Open
Supermassive black holes (SMBHs) are ubiquitously found at the centers of most galaxies. Measuring SMBH mass is important for understanding the origin and evolution of SMBHs. However, traditional methods require spectral data which is expe…
View article: Learning Principle of Least Action with Reinforcement Learning
Learning Principle of Least Action with Reinforcement Learning Open
Nature provides a way to understand physics with reinforcement learning since nature favors the economical way for an object to propagate. In the case of classical mechanics, nature favors the object to move along the path according to the…
View article: Hunting for Dark Matter Subhalos in Strong Gravitational Lensing with Neural Networks
Hunting for Dark Matter Subhalos in Strong Gravitational Lensing with Neural Networks Open
Dark matter substructures are interesting since they can reveal the properties of dark matter. Collisionless N-body simulations of cold dark matter show more substructures compared with the population of dwarf galaxy satellites observed in…
View article: Anomaly Detection for Multivariate Time Series of Exotic Supernovae
Anomaly Detection for Multivariate Time Series of Exotic Supernovae Open
Supernovae mark the explosive deaths of stars and enrich the cosmos with heavy elements. Future telescopes will discover thousands of new supernovae nightly, creating a need to flag astrophysically interesting events rapidly for followup s…