Zobrazeno 1 - 10
of 301
pro vyhledávání: '"Garé, P."'
Autor:
Shi, Jia, Gare, Gautam, Tian, Jinjin, Chai, Siqi, Lin, Zhiqiu, Vasudevan, Arun, Feng, Di, Ferroni, Francesco, Kong, Shu
We tackle the challenge of predicting models' Out-of-Distribution (OOD) performance using in-distribution (ID) measurements without requiring OOD data. Existing evaluations with "Effective Robustness", which use ID accuracy as an indicator of OOD acc
Externí odkaz:
http://arxiv.org/abs/2407.16067
Autor:
Gare, Gautam Rajendrakumar, Fox, Tom, Chansangavej, Beam, Krishnan, Amita, Rodriguez, Ricardo Luis, deBoisblanc, Bennett P, Ramanan, Deva Kannan, Galeotti, John Michael
Accurate and interpretable diagnostic models are crucial in the safety-critical field of medicine. We investigate the interpretability of our proposed biomarker-based lung ultrasound diagnostic pipeline to enhance clinicians' diagnostic capabilities.
Externí odkaz:
http://arxiv.org/abs/2402.12394
Autor:
Gare, Gautam Rajendrakumar, Fox, Tom, Lowery, Pete, Zamora, Kevin, Tran, Hai V., Hutchins, Laura, Montgomery, David, Krishnan, Amita, Ramanan, Deva Kannan, Rodriguez, Ricardo Luis, deBoisblanc, Bennett P, Galeotti, John Michael
Contemporary artificial neural networks (ANN) are trained end-to-end, jointly learning both features and classifiers for the task of interest. Though enormously effective, this paradigm imposes significant costs in assembling annotated task-specific
Externí odkaz:
http://arxiv.org/abs/2206.08398
Publikováno v:
BMC Oral Health, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background While efforts to improve the oral health of vulnerable populations have received little attention in general, the situation of children with disabilities in low- income countries (LICs) remains especially challenging. The present
Externí odkaz:
https://doaj.org/article/7af41bbc70e44a839c05a4a69cd2efc6
Autor:
Gare, Gautam Rajendrakumar, Schoenling, Andrew, Philip, Vipin, Tran, Hai V, deBoisblanc, Bennett P, Rodriguez, Ricardo Luis, Galeotti, John Michael
Publikováno v:
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 2021, pp. 1406-1410
We propose using a pre-trained segmentation model to perform diagnostic classification in order to achieve better generalization and interpretability, terming the technique reverse-transfer learning. We present an architecture to convert segmentation
Externí odkaz:
http://arxiv.org/abs/2201.10166
Autor:
Gare, Gautam Rajendrakumar, Chen, Wanwen, Hung, Alex Ling Yu, Chen, Edward, Tran, Hai V., Fox, Tom, Lowery, Pete, Zamora, Kevin, deBoisblanc, Bennett P, Rodriguez, Ricardo Luis, Galeotti, John Michael
Publikováno v:
LL-COVID19 2021. Lecture Notes in Computer Science, vol 12969. Springer, Cham
In this paper, we study the significance of the pleura and adipose tissue in lung ultrasound AI analysis. We highlight their more prominent appearance when using high-frequency linear (HFL) instead of curvilinear ultrasound probes, showing HFL reveal
Externí odkaz:
http://arxiv.org/abs/2201.07368
Autor:
Gare, Gautam Rajendrakumar, Tran, Hai V., deBoisblanc, Bennett P, Rodriguez, Ricardo Luis, Galeotti, John Michael
With the onset of the COVID-19 pandemic, ultrasound has emerged as an effective tool for bedside monitoring of patients. Due to this, a large amount of lung ultrasound scans have been made available which can be used for AI based diagnosis and analys
Externí odkaz:
http://arxiv.org/abs/2201.07357
Class labels used for machine learning are relatable to each other, with certain class labels being more similar to each other than others (e.g. images of cats and dogs are more similar to each other than those of cats and cars). Such similarity amon
Externí odkaz:
http://arxiv.org/abs/2103.13607
Autor:
Fernando de Souza Buzo, Lucas Martins Garé, Nayara Fernanda Siviero Garcia, Maura Santos Reis de Andrade Silva, Juliana Trindade Martins, Pedro Henrique Giova da Silva, Flávia Constantino Meireles, Leticia Zylmennith de Souza Sales, Amaia Nogales, Everlon Cid Rigobelo, Orivaldo Arf
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)
Abstract Phosphorus (P) is a plant macronutrient that is indispensable for maize (Zea mays L.) production. However, P is difficult to manage in weathered soils, and its fertilization practice has low efficiency because it becomes unavailable for abso
Externí odkaz:
https://doaj.org/article/1494b17e0857446c98bc9f4b29182fc9
Autor:
Gare, Gautam Rajendrakumar, Li, Jiayuan, Joshi, Rohan, Vaze, Mrunal Prashant, Magar, Rishikesh, Yousefpour, Michael, Rodriguez, Ricardo Luis, Galeotti, John Micheal
We present W-Net, a novel Convolution Neural Network (CNN) framework that employs raw ultrasound waveforms from each A-scan, typically referred to as ultrasound Radio Frequency (RF) data, in addition to the gray ultrasound image to semantically segme
Externí odkaz:
http://arxiv.org/abs/2008.12413