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Machine Learning in Medicine

Circulation (New York, N.Y.), 2015-11, Vol.132 (20), p.1920-1930

Deo, Rahul C

2015

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Type 2 Innate Signals Stimulate Fibro/Adipogenic Progenitors to Facilitate Muscle Regeneration

Cell, 2013-04, Vol.153 (2), p.376-388

2013

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Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

Atmospheric research, 2015-02, Vol.153, p.512-525

2015

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Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

Atmospheric research, 2015-07, Vol.161-162, p.65-81

2015

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Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

Journal of hydrology (Amsterdam), 2016-11, Vol.542, p.603-614

2016

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A Rapid Method for Directed Gene Knockout for Screening in G0 Zebrafish

Developmental cell, 2018-07, Vol.46 (1), p.112-125.e4

2018

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Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks

Scientific reports, 2021-09, Vol.11 (1), p.17497-17497, Article 17497

2021

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Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction

Energies (Basel), 2019-06, Vol.12 (12), p.2407

2019

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Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery

Circulation Cardiovascular quality and outcomes, 2019-09, Vol.12 (9), p.e005289-e005289

2019

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Designing Deep-Based Learning Flood Forecast Model With ConvLSTM Hybrid Algorithm

IEEE access, 2021, Vol.9, p.50982-50993

2021

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Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China

Hydrological processes, 2017-02, Vol.31 (5), p.1100-1112

2017

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Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms

Nature communications, 2021-05, Vol.12 (1), p.2726-2726, Article 2726

2021

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A machine learning model for identifying patients at risk for wild-type transthyretin amyloid cardiomyopathy

Nature communications, 2021-05, Vol.12 (1), p.2725-2725, Article 2725

2021

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RNA Sequencing of Mouse Sinoatrial Node Reveals an Upstream Regulatory Role for Islet-1 in Cardiac Pacemaker Cells

Circulation research, 2015-02, Vol.116 (5), p.797-803

2015

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An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction

Journal of hydrology (Amsterdam), 2019-02, Vol.569, p.387-408

2019

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Multinational Federated Learning Approach to Train ECG and Echocardiogram Models for Hypertrophic Cardiomyopathy Detection

Circulation (New York, N.Y.), 2022-09, Vol.146 (10), p.755-769

2022

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The role of internal transcribed spacer 2 secondary structures in classifying mycoparasitic Ampelomyces

PloS one, 2021-06, Vol.16 (6), p.e0253772

2021

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Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data

Remote sensing (Basel, Switzerland), 2021-02, Vol.13 (4), p.554

2021

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Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results

Energies (Basel), 2022-02, Vol.15 (3), p.1061

2022

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Artificial intelligence-enabled prediction of chemotherapy-induced cardiotoxicity from baseline electrocardiograms

Nature communications, 2024-03, Vol.15 (1), p.2536-2536, Article 2536

2024

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Deep Learning Based Over-the-Air Training of Wireless Communication Systems without Feedback

Sensors (Basel, Switzerland), 2024-05, Vol.24 (10), p.2993

2024

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Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

Scientific reports, 2023-10, Vol.13 (1), p.18145-18145, Article 18145

2023

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Channel-Agnostic Training of Transmitter and Receiver for Wireless Communications

Sensors (Basel, Switzerland), 2023-12, Vol.23 (24), p.9848

2023

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Application of Deep Learning Models for Automated Identification of Parkinson’s Disease: A Review (2011–2021)

Sensors (Basel, Switzerland), 2021-10, Vol.21 (21), p.7034

2021

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Author Correction: Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

Scientific reports, 2023-12, Vol.13 (1), p.22522-22522, Article 22522

2023

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Machine Learning in Medicine

Type 2 Innate Signals Stimulate Fibro/Adipogenic Progenitors to Facilitate Muscle Regeneration

Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

A Rapid Method for Directed Gene Knockout for Screening in G0 Zebrafish

Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks

Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction

Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery

Designing Deep-Based Learning Flood Forecast Model With ConvLSTM Hybrid Algorithm

Identifying separate impacts of climate and land use/cover change on hydrological processes in upper stream of Heihe River, Northwest China

Artificial intelligence-enabled fully automated detection of cardiac amyloidosis using electrocardiograms and echocardiograms

A machine learning model for identifying patients at risk for wild-type transthyretin amyloid cardiomyopathy

RNA Sequencing of Mouse Sinoatrial Node Reveals an Upstream Regulatory Role for Islet-1 in Cardiac Pacemaker Cells

An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction

Multinational Federated Learning Approach to Train ECG and Echocardiogram Models for Hypertrophic Cardiomyopathy Detection

The role of internal transcribed spacer 2 secondary structures in classifying mycoparasitic Ampelomyces

Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data

Stacked LSTM Sequence-to-Sequence Autoencoder with Feature Selection for Daily Solar Radiation Prediction: A Review and New Modeling Results

Artificial intelligence-enabled prediction of chemotherapy-induced cardiotoxicity from baseline electrocardiograms

Deep Learning Based Over-the-Air Training of Wireless Communication Systems without Feedback

Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

Channel-Agnostic Training of Transmitter and Receiver for Wireless Communications

Application of Deep Learning Models for Automated Identification of Parkinson’s Disease: A Review (2011–2021)

Author Correction: Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef

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