Toğaçar, Mesut Ergen, Burhan Cömert, Zafer
Published in
Computers in Biology and Medicine
• Chest data obtained from patients infected with the new Coronavirus (COVID-19) were used. • It was detected with deep learning models using COVID-19, normal, and pneumonia chest data. • The original dataset was restructured with the Fuzzy Color technique and two datasets were stacked. • Efficient features were selected by applying Social Mimic op...
Ardakani, Ali Abbasian Kanafi, Alireza Rajabzadeh Acharya, U. Rajendra Khadem, Nazanin Mohammadi, Afshin
Published in
Computers in Biology and Medicine
• Ten CNNs were used to distinguish infection of COVID-19 from non-COVID-19 groups. • ResNet-101 and Xception represented the best performance with an AUC of 0.994. • Deep learning technique can be used as an adjuvant tool in diagnosing COVID-19.
Ozturk, Tulin Talo, Muhammed Yildirim, Eylul Azra Baloglu, Ulas Baran Yildirim, Ozal Rajendra Acharya, U.
Published in
Computers in Biology and Medicine
• Proposed deep model for early detection of COVID-19 cases using X-ray images. • Obtained accuracy of 98.08% and 87.02% for binary and multi-classes. • Proposed heatmaps can help the radiologists to locate the affected regions on chest X-rays. • DarkCovidNet model can assist the clinicians to make faster and accurate diagnosis.
Robson, B.
Published in
Computers in Biology and Medicine
• This paper “drills down” into the studies of the author's previous COVID-19 paper. • Designing vaccine and drugs must seek to avoid escape mutations. • Subsequence KRSFIEDLLFNKV seems recognizable across many coronaviruses. • The ACE2 binding domain is a target, but shows variation. • A steroid dehydrogenase is argued to remain an interesting mod...
Robson, B.
Published in
Computers in Biology and Medicine
• Bioinformatics studies are carried out on the COVID-19 virus. • A sequence motif KRSFIEDLLFNKV is of particular interest. • Based on the above, synthetic peptides are designed. • Preliminary considerations are also given to non-peptide organic molecules.
Hao, Dongmei Peng, Jin Wang, Ying Liu, Juntao Zhou, Xiya Zheng, Dingchang
Published in
Computers in biology and medicine
Uterine contraction (UC) activity is commonly used to monitor the approach of labour and delivery. Electrohysterograms (EHGs) have recently been used to monitor UC and distinguish between efficient and inefficient contractions. In this study, we aimed to identify UC in EHG signals using a convolutional neural network (CNN). An open-access database ...
Plancke, Anne-Marie Connolly, Adam Gemmell, Philip M. Neic, Aurel McSpadden, Luke C. Whitaker, John O'Neill, Mark Rinaldi, Christopher A. Rajani, Ronak Niederer, Steven A.
...
Published in
Computers in Biology and Medicine
• Computational modelling plays an important role in optimising ICD configurations. • Our novel metric quantifies the relative energy used by the device to defibrillate. • It provides useful information, in conjunction with DFT and device impedance.
Campos, Fernando O. Orini, Michele Taggart, Peter Hanson, Ben Lambiase, Pier D. Porter, Bradley Rinaldi, Christopher Aldo Gill, Jaswinder Bishop, Martin J.
Published in
Computers in Biology and Medicine
• Safe and accurate detection of targets for catheter ablation remains a challenge. • We conducted a thorough assessment of the Re-entry Vulnerability Index (RVI). • Parameters of the algorithm can alter the specificity and sensitivity of RVI maps. • When constructed on sparse grids RVI maps could still detect arrhythmogenic sites. • In absence of ...
Beltrán Lissabet, Jorge Félix Belén, Lisandra Herrera Farias, Jorge G
Published in
Computers in biology and medicine
Viruses are worldwide pathogens with a high impact on the human population. Despite the constant efforts to fight viral infections, there is a need to discover and design new drug candidates. Antiviral peptides are molecules with confirmed activity and constitute excellent alternatives for the treatment of viral infections. In the present study, we...
Pszczolkowski, Stefan Law, Zhe K Gallagher, Rebecca G Meng, Dewen Swienton, David J Morgan, Paul S Bath, Philip M Sprigg, Nikola Dineen, Rob A
Published in
Computers in biology and medicine
Spontaneous intracerebral haemorrhage (SICH) is a common condition with high morbidity and mortality. Segmentation of haematoma and perihaematoma oedema on medical images provides quantitative outcome measures for clinical trials and may provide important markers of prognosis in people with SICH. We take advantage of improved contrast seen on magne...
