output
20202026
most citedCOVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings

299 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

4 papers

q-bio.QM2026

Artificial Intelligence Can Match Domain Experts in Evidence Extraction and Critical Appraisal of Microbial Oncogenesis Research Publications

Kaela Kokkas, Hairong Wang, Richard Klein +11

Confirmed oncogenic microbes contribute significantly to cancer burden. Identifying novel microbial oncogenicity could yield strategies that will reduce disease burdens. However, r…

cs.SD2021★ 106 cited

COVID-19 Detection in Cough, Breath and Speech using Deep Transfer Learning and Bottleneck Features

Madhurananda Pahar, Marisa Klopper, Robin Warren +1

We present an experimental investigation into the effectiveness of transfer learning and bottleneck feature extraction in detecting COVID-19 from audio recordings of cough, breath…

cs.SD2020★ 299 cited

COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings

Madhurananda Pahar, Marisa Klopper, Robin Warren +1

We present a machine learning based COVID-19 cough classifier which can discriminate COVID-19 positive coughs from both COVID-19 negative and healthy coughs recorded on a smartphon…

cs.IR2020★ 16 cited

COVID-19Base: A knowledgebase to explore biomedical entities related to COVID-19

Junaed Younus Khan, Md. Tawkat Islam Khondaker, Iram Tazim Hoque +4

We are presenting COVID-19Base, a knowledgebase highlighting the biomedical entities related to COVID-19 disease based on literature mining. To develop COVID-19Base, we mine the in…