Health Informatics

  1. A DISSYMMETRY IN THE FIGURES RELATED TO THE COVID-19 PANDEMIC IN THE WORLD: WHAT FACTORS EXPLAIN THE DIFFERENCE BETWEEN AFRICA AND THE REST OF THE WORLD?

    1. Cheikh Faye
    2. CheikhTidiane Wade
    3. Ibrahima Demba Dione

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  2. Going by the numbers : Learning and modeling COVID-19 disease dynamics

    1. Sayantani Basu
    2. Roy H. Campbell

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  3. A Novel Smart City Based Framework on Perspectives for application of Machine Learning in combatting COVID-19

    1. Absalom E. Ezugwu
    2. Ibrahim A.T. Hashem
    3. Olaide N. Oyelade
    4. Haruna Chiroma
    5. Mohammed A. Al-Garadi
    6. Idris N. Abdullahi
    7. Olumuyiwa Otegbeye
    8. Amit K. Shukla
    9. Mubarak Almutari

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  4. Causal Modeling of Twitter Activity during COVID-19

    1. Oguzhan Gencoglu
    2. Mathias Gruber

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  5. Forecasting Covid-19 Dynamics in Brazil: A Data Driven Approach

    1. Igor Gadelha Pereira
    2. Joris Michel Guerin
    3. Andouglas Gonçalves Silva Júnior
    4. Gabriel Santos Garcia
    5. Prisco Piscitelli
    6. Alessandro Miani
    7. Cosimo Distante
    8. Luiz Marcos Garcia Gonçalves

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  6. How well can we forecast the COVID-19 pandemic with curve fitting and recurrent neural networks?

    1. Zhuowen Zhao
    2. Kieran Nehil-Puleo
    3. Yangzhi Zhao

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  7. A citizen science initiative for open data and visualization of COVID-19 outbreak in Kerala, India

    1. Jijo Pulickiyil Ulahannan
    2. Nikhil Narayanan
    3. Nishad Thalhath
    4. Prem Prabhakaran
    5. Sreekanth Chaliyeduth
    6. Sooraj P Suresh
    7. Musfir Mohammed
    8. E Rajeevan
    9. Sindhu Joseph
    10. Akhil Balakrishnan
    11. Jeevan Uthaman
    12. Manoj Karingamadathil
    13. Sunil Thonikkuzhiyil Thomas
    14. Unnikrishnan Sureshkumar
    15. Shabeesh Balan
    16. Neetha Nanoth Vellichirammal
    17. the Collective for Open Data Distribution-Keralam (CODD-K) consortium

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  8. Interpretable Artificial Intelligence for COVID-19 Diagnosis from Chest CT Reveals Specificity of Ground-Glass Opacities

    1. Anmol Warman
    2. Pranav I. Warman
    3. Ayushman Sharma
    4. Puja Parikh
    5. Roshan Warman
    6. Narayan Viswanadhan
    7. Lu Chen
    8. Subhra Mohapatra
    9. Shyam S Mohapatra
    10. Guillermo Sapiro

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  9. Reliable and accurate diagnostics from highly multiplexed sequencing assays

    1. A. Sina Booeshaghi
    2. Nathan B. Lubock
    3. Aaron R. Cooper
    4. Scott W. Simpkins
    5. Joshua S. Bloom
    6. Jase Gehring
    7. Laura Luebbert
    8. Sri Kosuri
    9. Lior Pachter

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity

  10. Virtual Health Care for Community Management of Patients With COVID-19 in Australia: Observational Cohort Study

    1. Owen Rhys Hutchings
    2. Cassandra Dearing
    3. Dianna Jagers
    4. Miranda Jane Shaw
    5. Freya Raffan
    6. Aaron Jones
    7. Richard Taggart
    8. Tim Sinclair
    9. Teresa Anderson
    10. Angus Graham Ritchie

    Reviewed by ScreenIT

    1 evaluationAppears in 1 listLatest version Latest activity
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