Julliana Gonçalves Marques
Datos Biográficos
| ID | 7946933 |
|---|---|
| NOMBRE | Julliana Gonçalves Marques |
| NOMBRES | Julliana Gonçalves |
| APELLIDO | Marques |
| FIRMA | MARQUES J G |
| AFILIACIONES | Universidade Federal do Rio Grande do Norte |
| ORCID | 0000-0002-0740-1136 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 2 |
| TOTAL DE CITAS | 0 |
| TOTAL COMO AUTOR | 2 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2022 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2024 |
| ÍNDICE H | 0 |
Using Association Rules to Obtain Sets of Prevalent Symptoms throughout the Covid-19 Pandemic
The efficient recognition of symptoms in viral infections holds promise for swift and precise diagnosis, thus mitigating health implications and the potential recurrence of infections. COVID-19 presents unique challenges due to various factors influencing diagnosis, especially regarding disease symptoms that closely resemble those of other viral diseases, including other strains of SARS, thus impacting the identification of useful and meaningful …
Evaluating Time Influence over Performance of Machine-Learning-Based Diagnosis
Efficiently recognising severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) symptoms enables a quick and accurate diagnosis to be made, and helps in mitigating the spread of the coronavirus disease 2019. However, the emergence of new variants has caused constant changes in the symptoms associate with COVID-19. These constant changes directly impact the performance of machine-learning-based diagnose. In this context, considering the impac…
Sin obras prominentes en esta página.
Evaluating Time Influence over Performance of Machine-Learning-Based Diagnosis
Efficiently recognising severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) symptoms enables a quick and accurate diagnosis to be made, and helps in mitigating the spread of the coronavirus disease 2019. However, the emergence of new variants has caused constant changes in the symptoms associate with COVID-19. These constant changes directly impact the performance of machine-learning-based diagnose. In this context, considering the impac…
Using Association Rules to Obtain Sets of Prevalent Symptoms throughout the Covid-19 Pandemic
The efficient recognition of symptoms in viral infections holds promise for swift and precise diagnosis, thus mitigating health implications and the potential recurrence of infections. COVID-19 presents unique challenges due to various factors influencing diagnosis, especially regarding disease symptoms that closely resemble those of other viral diseases, including other strains of SARS, thus impacting the identification of useful and meaningful …
2019-20 coronavirus outbreak (2 obras) · Anomaly Detection Techniques and Applications (2 obras) · Computer Science (2 obras) · Coronavirus disease 2019 (COVID-19 (2 obras) · Disease (2 obras) · Medicine (2 obras) · Pandemic (2 obras) · Pathology (2 obras) · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 (2 obras) · Virology (2 obras)