Infrared Thermography Temperature


Linked on 11/20/2023

The Infrared Thermography Temperature Dataset contains temperatures read from various locations of inferred images about patients, with the addition of oral temperatures measured for each individual. The 33 features consist of gender, age, ethnicity, ambiant temperature, humidity, distance, and other temperature readings from the thermal images. The dataset is intended to be used in a regression task to predict the oral temperature using the environment information as well as the thermal image readings.

Dataset Characteristics


Subject Area

Health and Medicine

Associated Tasks


Feature Type

Real, Categorical

# Instances


# Features


Dataset Information

Has Missing Values?


Introductory Paper

Infrared Thermography for Measuring Elevated Body Temperature: Clinical Accuracy, Calibration, and Evaluation

By Quanzeng Wang, Yangling Zhou, Pejman Ghassemi, David McBride, J. Casamento, T. Pfefer. 2021

Published in Italian National Conference on Sensors

Variables Table

Variable NameRoleTypeDemographicDescriptionUnitsMissing Values
SubjectIDIDCategoricalSubject IDno
aveOralFTargetContinuousOral temperature measured in fast modeno
aveOralMTargetContinuousOral temperature measured in monitor modeno
GenderFeatureCategoricalGenderMale or Femaleno
AgeFeatureCategoricalAgeAge ranges in categories no
EthnicityFeatureCategoricalEthnicityAmerican Indian or Alaska Native, Asian, Black or African America, Hispanic/Latino, Multiracial, Native Hawaiian or other Pacific Islander,
T_atmFeatureContinuousAmbiant temperatureno
HumidityFeatureContinuousRelative humidityno
DistanceFeatureContinuousDistance between the subjects and the IRTs.  no
T_offset1FeatureContinuousTemperature difference between the set and measured blackbody temperature. See section 2.3.1 in .no

0 to 10 of 36

Additional Variable Information

- gender - age - ethnicity - ambiant temperature - humidity - distance - temperature readings from the thermal images

Class Labels

The class labels for the regression task are either the oral temperature measured in fast mode (aveOralF) or the temperature measured in monitor mode (aveOralM).


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Thermal Image


Quanzeng Wang

Yangling Zhou

Pejman Ghassemi

David McBride

J. Casamento

T. Pfefer

Quanzeng Wang

Yangling Zhou

Pejman Ghassemi

David McBride

J. Casamento

T. Pfefer


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