7.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Mayo Clinic in FloridaUS31 papers
- Mayo ClinicUS27 papers
- Arizona State UniversityUS16 papers
- WinnMedUS10 papers
- University of Illinois Urbana-ChampaignUS9 papers
- Emory UniversityUS8 papers
- University of PennsylvaniaUS8 papers
- Harvard UniversityUS7 papers
- Cornell UniversityUS6 papers
- National Institutes of HealthUS6 papers
- Yale UniversityUS6 papers
- Indiana University – Purdue University IndianapolisUS5 papers
11 papers · 1 filter
SafeImpute: Reliable Clinical Data Imputation via Conformal Selection
Xinrui He, Mengting Ai, Junting Wang +2
Clinical care often relies on key laboratory indicators, yet real-world patient visits are sparse and tests are ordered irregularly, leading to pervasive missingness. While many im…
Glycemic-Aware and Architecture-Agnostic Training Framework for Blood Glucose Forecasting in Type 1 Diabetes
Saman Khamesian, Asiful Arefeen, Maria Adela Grando +2
Managing Type 1 Diabetes (T1D) demands constant vigilance as individuals strive to regulate their blood glucose levels and avoid dysglycemia, including hyperglycemia and hypoglycem…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1168
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation
Xinrui He, Yikun Ban, Jiaru Zou +3
Missing data imputation is a critical challenge in various domains, such as healthcare and finance, where data completeness is vital for accurate analysis. Large language models (L…
Self-Supervised Learning and Opportunistic Inference for Continuous Monitoring of Freezing of Gait in Parkinson's Disease
Shovito Barua Soumma, Daniel Peterson, Shyamal Mehta +1
Parkinson's disease (PD) is a progressive neurological disorder that impacts the quality of life significantly, making in-home monitoring of motor symptoms such as Freezing of Gait…
From algorithms to action: improving patient care requires causality
Wouter A. C. van Amsterdam, Pim A. de Jong, Joost J. C. Verhoeff +2
In cancer research there is much interest in building and validating outcome predicting outcomes to support treatment decisions. However, because most outcome prediction models are…
Multimodal spatiotemporal graph neural networks for improved prediction of 30-day all-cause hospital readmission
Siyi Tang, Amara Tariq, Jared Dunnmon +5
Measures to predict 30-day readmission are considered an important quality factor for hospitals as accurate predictions can reduce the overall cost of care by identifying high risk…
Deep Q-learning of global optimizer of multiply model parameters for viscoelastic imaging
Hongmei Zhang, Kai Wang, Yan Zhou +4
Objective: Estimation of the global optima of multiple model parameters is valuable in imaging to form a reliable diagnostic image. Given non convexity of the objective function, i…
Regenerative Particle Thompson Sampling
Zeyu Zhou, Bruce Hajek, Nakjung Choi +1
This paper proposes regenerative particle Thompson sampling (RPTS), a flexible variation of Thompson sampling. Thompson sampling itself is a Bayesian heuristic for solving stochast…
Decentralized Federated Learning through Proxy Model Sharing
Shivam Kalra, Junfeng Wen, Jesse C. Cresswell +2
Institutions in highly regulated domains such as finance and healthcare often have restrictive rules around data sharing. Federated learning is a distributed learning framework tha…
Active, Continual Fine Tuning of Convolutional Neural Networks for Reducing Annotation Efforts
Zongwei Zhou, Jae Y. Shin, Suryakanth R. Gurudu +2
The splendid success of convolutional neural networks (CNNs) in computer vision is largely attributable to the availability of massive annotated datasets, such as ImageNet and Plac…