Radiogenomics　is　a　high-throughput　research　method　that　correlates　genomic　data　with　imaging　features,　and　is　now　applied　widely　to　the　identification　of　molecular　subtypes　of　breast　cancer　and　the　assessment　of　cancer　risk.　Radiogenomics,　based　on　machine　learning　and　big　data　technologies,　has　shown　tremendous　potential　in　personalized　diagnosis　and　treatment　of　breast　cancer.　To　summarize　the　current　research　status　and　future　prospects　of　machine　learning　technology　in　breast　cancer　radiogenomics,　the　genetic　characteristics　of　breast　cancer　and　the　methods　for　obtaining　breast　cancer　imaging　data　were　first　introduced,　and　the　application　of　machine　learning　technology　in　predicting　the　benign　/　malignant　nature　of　breast　cancer　was　analyzed.　Subsequently,　deep　learning　methods　applied　to　breast　cancer　image　segmentation　problems　were　compared　and　breast　cancer　radiogenomics　models　were　analyzed.　Finally,　the　current　limitations　of　research　and　further　research　directions　in　breast　cancer　radiogenomics　were　pointed　out.　©　2024　Beijing　University　of　Technology.　All　rights　reserved.