tetano
Editor, Senior Moderator
BMC Res Notes
. 2024 Jan 19;17(1):30.
doi: 10.1186/s13104-024-06688-w. Upper body thermal images and associated clinical data from a pilot cohort study of COVID-19
Sofia Rojas-Zumbado[SUP] 1 [/SUP], Jose-Gerardo Tamez-Peña[SUP] 2 [/SUP], Andrea-Alejandra Trevino-Ferrer[SUP] 2 [/SUP], Carlos-Andres Diaz-Garza[SUP] 2 [/SUP], Meritxell Ledesma-Hernández[SUP] 2 [/SUP], Alejandra-Celina Esparza-Sandoval[SUP] 2 [/SUP], Rocio Ortiz-Lopez[SUP] 2 3 [/SUP], Guillermo Torre-Amione[SUP] 3 [/SUP], Servando Cardona-Huerta[SUP] 3 [/SUP], Victor Trevino[SUP] 2 [/SUP]
Affiliations
Objectives: The data was collected for a cohort study to assess the capability of thermal videos in the detection of SARS-CoV-2. Using this data, a published study applied machine learning to analyze thermal image features for Covid-19 detection.
Data description: The study recorded a set of measurements from 252 participants over 18 years of age requesting a SARS-CoV-2 PCR (polymerase chain reaction) test at the Hospital Zambrano-Hellion in Nuevo León, México. Data for PCR results, demographics, vital signs, food intake, activities and lifestyle factors, recently taken medications, respiratory and general symptoms, and a thermal video session where the volunteers performed a simple breath-hold in four different positions were collected. Vital signs recorded include axillary temperature, blood pressure, heart rate, and oxygen saturation. Each thermal video is split into 4 scenes, corresponding to front, back, left and right sides, and is available in MPEG-4 format to facilitate inclusion into pipelines for image processing. Raw JPEG images of the background between subjects are included to register variations in room temperatures.
Keywords: Covid-19; Demographic data; Respiratory disease; Thermal imaging; Thermal videos.
. 2024 Jan 19;17(1):30.
doi: 10.1186/s13104-024-06688-w. Upper body thermal images and associated clinical data from a pilot cohort study of COVID-19
Sofia Rojas-Zumbado[SUP] 1 [/SUP], Jose-Gerardo Tamez-Peña[SUP] 2 [/SUP], Andrea-Alejandra Trevino-Ferrer[SUP] 2 [/SUP], Carlos-Andres Diaz-Garza[SUP] 2 [/SUP], Meritxell Ledesma-Hernández[SUP] 2 [/SUP], Alejandra-Celina Esparza-Sandoval[SUP] 2 [/SUP], Rocio Ortiz-Lopez[SUP] 2 3 [/SUP], Guillermo Torre-Amione[SUP] 3 [/SUP], Servando Cardona-Huerta[SUP] 3 [/SUP], Victor Trevino[SUP] 2 [/SUP]
Affiliations
- PMID: 38243331
- PMCID: PMC10799398
- DOI: 10.1186/s13104-024-06688-w
Objectives: The data was collected for a cohort study to assess the capability of thermal videos in the detection of SARS-CoV-2. Using this data, a published study applied machine learning to analyze thermal image features for Covid-19 detection.
Data description: The study recorded a set of measurements from 252 participants over 18 years of age requesting a SARS-CoV-2 PCR (polymerase chain reaction) test at the Hospital Zambrano-Hellion in Nuevo León, México. Data for PCR results, demographics, vital signs, food intake, activities and lifestyle factors, recently taken medications, respiratory and general symptoms, and a thermal video session where the volunteers performed a simple breath-hold in four different positions were collected. Vital signs recorded include axillary temperature, blood pressure, heart rate, and oxygen saturation. Each thermal video is split into 4 scenes, corresponding to front, back, left and right sides, and is available in MPEG-4 format to facilitate inclusion into pipelines for image processing. Raw JPEG images of the background between subjects are included to register variations in room temperatures.
Keywords: Covid-19; Demographic data; Respiratory disease; Thermal imaging; Thermal videos.