14.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Columbia UniversityUS16 papers
- Harvard UniversityUS13 papers
- Stanford UniversityUS12 papers
- Cornell UniversityUS11 papers
- National Institutes of HealthUS7 papers
- New York UniversityUS7 papers
- University of California, San FranciscoUS7 papers
- Emory UniversityUS6 papers
- Georgia Institute of TechnologyUS6 papers
- Hebrew University of JerusalemIL6 papers
- Imperial College LondonGB6 papers
- Mayo ClinicUS6 papers
127 papers
Advancing Risk Gene Discovery Across the Allele Frequency Spectrum
Madison Caballero, Behrang Mahjani
The discovery of genetic risk factors has transformed human genetics, yet the pace of new gene identification has slowed despite the exponential expansion of sequencing and biobank…
Stresses and fluid flow in lamina cribrosa through anisotropic poroelasticty
Riccardo Cavuoto, Sofia Damian, Luca Deseri +5
To investigate the mechanical correlations between intraocular pressure (IOP) variations and glaucoma, this study presents a linear transversely isotropic poroelastic model of the…
Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography
Maxime Descoteaux, Kurt G. Schilling, Dogu Baran Aydogan +44
In the spirit of the historic Millennium Prize Problems that heralded a new era for mathematics, the newly formed International Society for Tractography (IST) has launched the Mill…
Generalization of Ramanujan's formula for sums of half-integer powers of consecutive integers via formal Bernoulli series
Max A. Alekseyev, Rafael Gonzalez, Keryn Loor +2
Faulhaber's formula expresses the sum of the first positive integers, each raised to an integer power , as a polynomial in of degree . Ramanujan expressed thi…
A Network-Guided Penalized Regression with Application to Proteomics Data
Seungjun Ahn, Eun Jeong Oh
Network theory has proven invaluable in unraveling complex protein interactions. Previous studies have employed statistical methods rooted in network theory, including the Gaussian…
Vision Language Models versus Machine Learning Models Performance on Polyp Detection and Classification in Colonoscopy Images
Mohammad Amin Khalafi, Seyed Amir Ahmad Safavi-Naini, Ameneh Salehi +13
Introduction: This study provides a comprehensive performance assessment of vision-language models (VLMs) against established convolutional neural networks (CNNs) and classic machi…
Self-Reported Confidence of Large Language Models in Gastroenterology: Analysis of Commercial, Open-Source, and Quantized Models
Nariman Naderi, Seyed Amir Ahmad Safavi-Naini, Thomas Savage +4
This study evaluated self-reported response certainty across several large language models (GPT, Claude, Llama, Phi, Mistral, Gemini, Gemma, and Qwen) using 300 gastroenterology bo…
Leveraging Two-Phase Data for Improved Prediction of Survival Outcomes with Application to Nasopharyngeal Cancer
Eun Jeong Oh, Seungjun Ahn, Tristan Tham +1
Accurate survival predicting models are essential for improving targeted cancer therapies and clinical care among cancer patients. In this article, we investigate and develop a met…
A Multi-Omics Framework for Survival Mediation Analysis of High-Dimensional Proteogenomic Data
Seungjun Ahn, Weijia Fu, Maaike van Gerwen +2
Survival analysis plays a crucial role in understanding time-to-event (survival) outcomes such as disease progression. Despite recent advancements in causal mediation frameworks fo…
A Method for Imaging the Ischemic Penumbra with MRI using IVIM
Mira M. Liu, Niloufar Saadat, Steven P. Roth +5
This work examines the hypothesis that intravoxel incoherent motion MRI (IVIM) can quantify local cerebral blood flow (qCBF), infarct volume, and define the ischemic penumbra for d…
Impact of normal lung volume choices on radiation pneumonitis risk prediction in locally advanced NSCLC radiotherapy
Alyssa Gadsby, Tian Liu, Robert Samstein +4
This study is to evaluate the impact of lung volume choices on predicting radiation pneumonitis (RP) risk in patients with locally advanced NSCLC undergoing radiotherapy. Dosimetri…
Environment Scan of Generative AI Infrastructure for Clinical and Translational Science
Betina Idnay, Zihan Xu, William G. Adams +54
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 instituti…
Vision-Language and Large Language Model Performance in Gastroenterology: GPT, Claude, Llama, Phi, Mistral, Gemma, and Quantized Models
Seyed Amir Ahmad Safavi-Naini, Shuhaib Ali, Omer Shahab +15
Background and Aims: This study evaluates the medical reasoning performance of large language models (LLMs) and vision language models (VLMs) in gastroenterology. Methods: We used…
Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data
Mohammadreza Ghaffarzadeh-Esfahani, Mahdi Ghaffarzadeh-Esfahani, Arian Salahi-Niri +39
This study compared the performance of classical feature-based machine learning models (CMLs) and large language models (LLMs) in predicting COVID-19 mortality using high-dimension…
Hierarchical Bayesian estimation of motor-evoked potential recruitment curves yields accurate and robust estimates
Vishweshwar Tyagi, Lynda M. Murray, Ahmet S. Asan +5
Electromagnetic stimulation probes and modulates the neural systems that control movement. Key to understanding their effects is the muscle recruitment curve, which maps evoked pot…
X-ray2CTPA: Leveraging Diffusion Models to Enhance Pulmonary Embolism Classification
Noa Cahan, Eyal Klang, Galit Aviram +4
Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detai…
Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study
Sudeshna Das, Yao Ge, Yuting Guo +19
The increasing use of social media to share lived and living experiences of substance use presents a unique opportunity to obtain information on side effects, use patterns, and opi…
Extracting Social Support and Social Isolation Information from Clinical Psychiatry Notes: Comparing a Rule-based NLP System and a Large Language Model
Braja Gopal Patra, Lauren A. Lepow, Praneet Kasi Reddy Jagadeesh Kumar +16
Background: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), indivi…
COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modeling
Baihan Lin, Djallel Bouneffouf, Yulia Landa +3
The therapeutic working alliance is a critical predictor of psychotherapy success. Traditionally, working alliance assessment relies on questionnaires completed by both therapists…
VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification
Zelong Liu, Andrew Tieu, Nikhil Patel +9
Artificial Intelligence (AI) has the potential to revolutionize diagnosis and segmentation in medical imaging. However, development and clinical implementation face multiple challe…
MRAnnotator: multi-Anatomy and many-Sequence MRI segmentation of 44 structures
Alexander Zhou, Zelong Liu, Andrew Tieu +16
In this retrospective study, we annotated 44 structures on two datasets: an internal dataset of 1,518 MRI sequences from 843 patients at the Mount Sinai Health System, and an exter…
Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables
Mariyam Khan, Adriaan-Alexander Ludl, Sean Bankier +2
Multivariate Mendelian randomization (MVMR) is a statistical technique that uses sets of genetic instruments to estimate the direct causal effects of multiple exposures on an outco…
Structural-Based Uncertainty in Deep Learning Across Anatomical Scales: Analysis in White Matter Lesion Segmentation
Nataliia Molchanova, Vatsal Raina, Andrey Malinin +7
This paper explores uncertainty quantification (UQ) as an indicator of the trustworthiness of automated deep-learning (DL) tools in the context of white matter lesion (WML) segment…
Boosting advice and knowledge sharing among healthcare professionals
A. Fronzetti Colladon, F. Grippa, C. Broccatelli +6
Purpose: This study investigates the dynamics of knowledge sharing in healthcare, exploring some of the factors that are more likely to influence the evolution of idea sharing and…