Experimentation often produces unwieldy amounts of data, requiring manual extraction and interpretation. Open source and adaptable artificial intelligence algorithms may offer an expedient solution to sluggish data analysis. As the field of machine learning has grown, effective applications in tumour detection and genetic screening have emerged, frequently outperforming their human counterparts. As such, therein lies the potential for an analytical acuity and specificity hitherto nonexistent. A readily available image-based AI was tailored to detect regions of brown adipose tissue in thermal images of mice and to output a temperature measurement of said region. The resulting program is capable of processing images at a rate exponentially greater than manual analysis. This research demonstrates the analytical potential of AI, and, more importantly, its accessibility to those unfamiliar with programming and computer science.