Age prediction is an important part of medical assessments and research. It can aid in detecting diseases as well as abnormal ageing by highlighting the discrepancy between chronological and biological age. To gain a comprehensive understanding of age-related changes observed in various body parts, we investigate them on a larger scale by using whole-body 3D images. We utilise the Grad-CAM interpretability method to determine the body areas most predictive of a person's age. We expand our analysis beyond individual subjects by employing registration techniques to generate population-wide interpretability maps. Our findings reveal three primary areas of interest: the spine, the autochthonous back muscles, and the cardiac region, which exhibits the highest importance.

翻译：年龄预测是医学评估与研究的重要组成部分。通过揭示实际年龄与生物学年龄之间的差异，年龄预测有助于检测疾病及异常衰老过程。为全面理解身体各部位随年龄变化的规律，我们利用全身三维图像在更大尺度上开展了研究。采用Grad-CAM可解释性方法，我们确定了最能预测年龄的身体区域。通过引入配准技术，我们将分析范围从个体扩展至群体层面，生成了全人群的可解释性图谱。研究结果显示三个主要关注区域：脊柱、自体背部肌肉以及重要性最高的心脏区域。