This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals. In conventional methods, the detection and classification in automotive radar systems are conducted in two successive stages; however, in the proposed method, the two stages are combined into one. To verify the effectiveness of the proposed method, we applied it to the actual radar data measured using our automotive radar sensor. According to the results, our proposed method can simultaneously detect targets and classify them with over 90% accuracy. In addition, it shows better performance in terms of detection and classification, compared with conventional methods such as density-based spatial clustering of applications with noise or the support vector machine. Moreover, the proposed method especially exhibits better performance when detecting and classifying a vehicle with a long body.

Cho HW, et al. J Gynecol Oncol. 2021 Oct;33(1):e4. https://doi.org/10.3802/jgo.2022.33.e4

Due to improvements in chemotherapeutic agents, cancer treatment efficacy and cancer patient survival rates have greatly improved, but unfortunately gonadal damage remains a major complication. Gonadotoxic chemotherapy, including alkylating agents during reproductive age, can lead to iatrogenic premature ovarian insufficiency (POI), and loss of fertility. In recent years, the demand for fertility preservation has increased dramatically among female cancer patients. Currently, embryo and oocyte cryopreservation are the only established options for fertility preservation in women. However, there is growing evidence for other experimental techniques including ovarian tissue cryopreservation, oocyte in vitro maturation, artificial ovaries, stem cell technologies, and ovarian suppression. To prevent fertility loss in women with cancer, individualized fertility preservation options including established and experimental techniques that take into consideration the patient’s age, marital status, chemotherapy regimen, and the possibility of treatment delay should be provided. In addition, effective multidisciplinary oncofertility strategies that involve a highly skilled and experienced oncofertility team consisting of medical oncologists, gynecologists, reproductive biologists, surgical oncologists, patient care coordinators, and research scientists are necessary to provide cancer patients with high-quality care.

Ouh YT, et al. J Gynecol Oncol. 2017 Sep;29(1):e14. https://doi.org/10.3802/jgo.2018.29.e14

Cho HW, et al. Obstet Gynecol Sci. 2015 Jan;58(1):40-45. http://dx.doi.org/10.5468/ogs.2015.58.1.40