390 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université Pierre-et-Marie-CurieFR16 papers
- University of PittsburghUS13 papers
- Centre National de la Recherche ScientifiqueFR9 papers
- Carnegie Mellon UniversityUS7 papers
- InsermFR4 papers
- Institut national de recherche en sciences et technologies du numériqueFR4 papers
- Sorbonne UniversitéFR4 papers
- The University of Texas Southwestern Medical CenterUS4 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS3 papers
- Harvard UniversityUS3 papers
- Institut de Mathématiques de Jussieu-Paris Rive GaucheFR3 papers
- Massachusetts General HospitalUS3 papers
40 papers
Conditional anomaly detection methods for patient-management alert systems
Michal Valko, Gregory Cooper, Amy Seybert +3
Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly det…
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…
Efficient Frame Extraction: A Novel Approach Through Frame Similarity and Surgical Tool Tracking for Video Segmentation
Huu Phong Nguyen, Shekhar Madhav Khairnar, Sofia Garces Palacios +6
The interest in leveraging Artificial Intelligence (AI) for surgical procedures to automate analysis has witnessed a significant surge in recent years. One of the primary tools for…
Generative AI Is Not Ready for Clinical Use in Patient Education for Lower Back Pain Patients, Even With Retrieval-Augmented Generation
Yi-Fei Zhao, Allyn Bove, David Thompson +6
Low back pain (LBP) is a leading cause of disability globally. Following the onset of LBP and subsequent treatment, adequate patient education is crucial for improving functionalit…
ECG-SMART-NET: A Deep Learning Architecture for Precise ECG Diagnosis of Occlusion Myocardial Infarction
Nathan T. Riek, Murat Akcakaya, Zeineb Bouzid +10
Objective: In this paper we develop and evaluate ECG-SMART-NET for occlusion myocardial infarction (OMI) identification. OMI is a severe form of heart attack characterized by compl…
Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine
Qiao Jin, Fangyuan Chen, Yiliang Zhou +15
Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily…
A Multimodal Sensing Ring for Quantification of Scratch Intensity
Akhil Padmanabha, Sonal Choudhary, Carmel Majidi +1
An objective measurement of chronic itch is necessary for improvements in patient care for numerous medical conditions. While wearables have shown promise for scratch detection, th…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
Counterfactual Phenotyping with Censored Time-to-Events
Chirag Nagpal, Mononito Goswami, Keith Dufendach +1
Estimation of treatment efficacy of real-world clinical interventions involves working with continuous outcomes such as time-to-death, re-hospitalization, or a composite event that…
Dense Pixel-Labeling for Reverse-Transfer and Diagnostic Learning on Lung Ultrasound for COVID-19 and Pneumonia Detection
Gautam Rajendrakumar Gare, Andrew Schoenling, Vipin Philip +4
We propose using a pre-trained segmentation model to perform diagnostic classification in order to achieve better generalization and interpretability, terming the technique reverse…
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
Knowledge-Guided Multiview Deep Curriculum Learning for Elbow Fracture Classification
Jun Luo, Gene Kitamura, Dooman Arefan +3
Elbow fracture diagnosis often requires patients to take both frontal and lateral views of elbow X-ray radiographs. In this paper, we propose a multiview deep learning method for a…
Interpretable Network Representation Learning with Principal Component Analysis
James D. Wilson, Jihui Lee
We consider the problem of interpretable network representation learning for samples of network-valued data. We propose the Principal Component Analysis for Networks (PCAN) algorit…
Fine-Tuning and Training of DenseNet for Histopathology Image Representation Using TCGA Diagnostic Slides
Abtin Riasatian, Morteza Babaie, Danial Maleki +19
Feature vectors provided by pre-trained deep artificial neural networks have become a dominant source for image representation in recent literature. Their contribution to the perfo…
Adaptive Bayesian Spectral Analysis of High-dimensional Nonstationary Time Series
Zeda Li, Ori Rosen, Fabio Ferrarelli +1
This article introduces a nonparametric approach to spectral analysis of a high-dimensional multivariate nonstationary time series. The procedure is based on a novel frequency-doma…
Assessment of central serous chorioretinopathy (CSC) depicted on color fundus photographs using deep Learning
Yi Zhen, Hang Chen, Xu Zhang +4
To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology. We collected a…
State-Dependent Modulation of Locomotion by GABAergic Spinal Sensory Neurons
Kevin Fidelin, Lydia Djenoune, Caleb Stokes +5
The cerebrospinal fluid (CSF) constitutes an interface through which chemical cues can reach and modulate the activity of neurons located at the epithelial boundary within the enti…
Prediction of optimal catalysts for a given chemical reaction
Herve Toulhoat, Pascal Raybaud
We reveal a correlation between the M-X bond energy descriptor EMX for the optimal catalyst in a family of stoichiometry MiXj, and an intensive quantity defined as the standard ent…
When Conventional machine learning meets neuromorphic engineering: Deep Temporal Networks (DTNets) a machine learning frawmework allowing to operate on Events and Frames and implantable on Tensor Flow Like Hardware
Marco Macanovic, Fabian Chersi, Felix Rutard +2
We introduce in this paper the principle of Deep Temporal Networks that allow to add time to convolutional networks by allowing deep integration principles not only using spatial i…
Sequential Wnt Agonist then Antagonist Treatment Accelerates Tissue Repair and Minimizes Fibrosis
Xiao-Jun Tian, Dong Zhou, Haiyan Fu +5
Tissue fibrosis compromises organ function and occurs as a potential long-term outcome in response to acute tissue injuries. Currently, lack of mechanistic understanding prevents e…
Learn to segment single cells with deep distance estimator and deep cell detector
Weikang Wang, David A. Taft, Yi-Jiun Chen +5
Single cell segmentation is critical and challenging in live cell imaging data analysis. Traditional image processing methods and tools require time-consuming and labor-intensive e…
DIMM-SC: A Dirichlet mixture model for clustering droplet-based single cell transcriptomic data
Zhe Sun, Ting Wang, Ke Deng +5
Motivation: Single cell transcriptome sequencing (scRNA-Seq) has become a revolutionary tool to study cellular and molecular processes at single cell resolution. Among existing tec…
Surrogate-based artifact removal from single-channel EEG
Mario Chavez, Fanny Grosselin, Aurore Bussalb +2
The recent emergence and success of electroencephalography (EEG) in low-cost portable devices, has opened the door to a new generation of applications processing a small number of…
Non dégénérescence et singularités des métriques d'Einstein asymptotiquement hyperboliques en dimension 4
Olivier Biquard
We prove that desingularizations of non degenerate Poincaré-Einstein metrics with A1 singularities remain non degenerate. In principle this enables a recursive procedure to desingu…