Clinical event prediction and understanding with deep neural networks

Clinical event prediction and understanding with deep neural networks

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, June, 2017

Bibliographic Details
Main Author:	Suresh, Harini(Harini S.)
Other Authors:	Peter Szolovits.
Format:	Thesis
Language:	eng
Published:	Massachusetts Institute of Technology 2018
Subjects:	Electrical Engineering and Computer Science.
Online Access:	http://hdl.handle.net/1721.1/113169

Similar Items

Eye tracking for the iPhone using deep learning
by: Kannan, Harini D
Published: (2018)

Few-shot visual understanding with deep neural networks
by: Zhang, Chi
Published: (2022)

Deep graph neural networks for link prediction
by: Zheng, MingXi
Published: (2024)

Representation learning in multi-dimensional clinical timeseries for risk and event prediction
by: Ghassemi, Marzyeh
Published: (2017)

On foveation of deep neural networks
by: Srivastava, Sanjana.
Published: (2019)

A deep neural network approach to predicting clinical outcomes of neuroblastoma patients
by: Tranchevent, Léon-Charles, et al.
Published: (2021)

Attack on prediction confidence of deep learning neural networks
by: Ng, Garyl Xuan
Published: (2022)

A Framework for Understanding Sources of Harm throughout the Machine Learning Life Cycle
by: Suresh, Harini, et al.
Published: (2022)

Deep GRU neural networks for gold price prediction
by: Kuan, Soon Yee
Published: (2023)

Towards understanding residual neural networks
by: Zeng, Brandon.
Published: (2019)

Developing real-time traffic prediction with deep neural networks
by: Zhou, Tianchen
Published: (2023)

Deep neural networks are lazy : on the inductive bias of deep learning
by: Mansour, Tarek,M. Eng.Massachusetts Institute of Technology.
Published: (2019)

Stock trading prediction using deep learning neural networks
by: Ong, Hao Cong
Published: (2021)

Deep GRU neural networks for Apple stock price prediction
by: Ji, YiJun
Published: (2023)

Housing price prediction using deep neural networks
by: Yapary, Stephen
Published: (2021)

Comparing learned representations of deep neural networks
by: Miglani, Vivek N.
Published: (2019)

Enhancing adversarial robustness of deep neural networks
by: Zhang, Jeffrey,M. Eng.Massachusetts Institute of Technology.
Published: (2019)

Parameter prediction for Lorenz Attractor by using Deep Neural Network
by: Nurnajmin Qasrina Ann, Ayop Azmi, et al.
Published: (2020)

Future Glycemic Events Prediction Model Based On Artificial Neural Network
by: Syafrudin, Muhammad, et al.
Published: (2022)

Scene parsing with deep neural networks
by: Ding, Henghui
Published: (2020)

Robotic object pose estimation with deep neural networks
by: Wu, Jimmy, M. Eng. Massachusetts Institute of Technology
Published: (2018)

Generalization of deep neural networks to unseen attribute combinations
by: Henry, Timothy G.
Published: (2021)

Strongly-transferring memorized examples in deep neural networks
by: Venigalla, Abhinav S.
Published: (2019)

Foreign exchange prediction and trading using deep belief neural network
by: Muhammad Bin Mustaffa
Published: (2018)

Precious metal price prediction using deep neural networks
by: Leow, Sean Teng Hui
Published: (2021)

Precious metal price prediction using deep neural networks
by: Peng, Zhiling
Published: (2021)

An entropy-based approach to network attack classification with deep neural network
by: Do, Emily H.
Published: (2020)

Predicting blood pressure response to fluid bolus therapy in the ICU using attention-based stacked neural networks for clinical interpretability
by: Girkar, Uma M.
Published: (2019)

Stock trading & prediction using deep learning neural networks
by: Gowri, Kannan
Published: (2017)

Aircraft position prediction using neural networks
by: Doshi, Anuja
Published: (2006)

Deep neural networks for stock forecasting
by: Gao, Kexin
Published: (2022)

Stock trading and prediction using deep learning neural network
by: Cheam, Nicholas Yen Kait
Published: (2018)

Exploring the landscape of backdoor attacks on deep neural network models
by: Turner, Alexander M.,S.M.Massachusetts Institute of Technology.
Published: (2019)

Improved methodology for evaluating adversarial robustness in deep neural networks
by: Lee, Kyungmi,(Computer scientist)Massachusetts Institute of Technology.
Published: (2020)

Emergent patterns of task-specific neurons in deep neural networks
by: Dozier, Jamell(Jamell A.)
Published: (2021)

Deep learning for clinical mammography screening
by: Locascio, Nicholas (Nicholas J.)
Published: (2018)

Visualizing interpretations of deep neural networks
by: Tan, Ryan Kang Wei
Published: (2022)

Visualizing interpretations of deep neural networks
by: Ta, Quynh Nga
Published: (2023)

Foreign exchange prediction and trading using deep belief neural network
by: Huang, Melvin Jin Wei
Published: (2020)

Predicting drug responses from drug chemical features by using deep neural networks
by: Krithika Ramamoorthy
Published: (2021)