Background As the available information about breast cancer is growing every day, the decision-making process for the therapy is getting more complex. ChatGPT as a transformer-based language model possesses the ability to write scientific articles and pass medical exams. But is it able to support the multidisciplinary tumor board (MDT) in the planning of the therapy of patients with breast cancer? Material and Methods We performed a pilot study on 10 consecutive cases of breast cancer patients discussed in MDT at our department in January 2023. Included were patients with a primary diagnosis of early breast cancer. The recommendation of MDT was compared with the recommendation of the ChatGPT for particular patients and the clinical score of the agreement was calculated. Results Results showed that ChatGPT provided mostly general answers regarding chemotherapy, breast surgery, radiation therapy, chemotherapy, and antibody therapy. It was able to identify risk factors for hereditary breast cancer and point out the elderly patient indicated for chemotherapy to evaluate the cost/benefit effect. ChatGPT wrongly identified the patient with Her2 1 + and 2 + (FISH negative) as in need of therapy with an antibody and called endocrine therapy “hormonal treatment”. Conclusions Support of artificial intelligence by finding individualized and personalized therapy for our patients in the time of rapidly expanding amount of information is looking for the ways in the clinical routine. ChatGPT has the potential to find its spot in clinical medicine, but the current version is not able to provide specific recommendations for the therapy of patients with primary breast cancer.

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Aim According to the World Health Organization, approximately 810 pregnant women die every day as a consequence of peripartum complications. A large proportion of deaths happen in developing countries. Peripartum cardiac arrest is a rare event that must be treated immediately. It is important to consider the differential diagnoses in order to save lives. Methods In this review, we discuss a differential diagnosis of cardiac arrest according to the BEAU-CHOPS scheme of the American Heart Association in the relation to the case report of our 40-year-old G5/P3 patient who went into cardiac arrest during cesarean delivery. Results Typical differentials for cardiac arrest during labor are bleeding, embolism, anesthetic complications, cardiovascular diseases, eclampsia, and sepsis. All of them were considered and ruled out in this patient. In the end, we suspect that physiological cardio-inhibitory reflexes triggered by sudden profound hypovolemia after placental separation along with the patientʼs risk factors, especially obesity and maternal age, and the administration of spinal anesthesia all potentially contributed to the cardiac arrest. Conclusions This review highlights that the cardiac arrest during labor can be triggered by the multifactorial etiology, but firstly the typical differential diagnosis needs to be excluded.

As the available information about breast cancer is growing every day, the decision-making process for the therapy is getting more complex. ChatGPT as a transformer-based language model possesses the ability to write scientific articles and pass medical exams. But is it able to support the multidisciplinary tumor board (MDT) in the planning of the therapy of patients with breast cancer? We performed a pilot study on 10 consecutive cases of breast cancer patients discussed in MDT at our department in January 2023. Included were patients with a primary diagnosis of early breast cancer. The recommendation of MDT was compared with the recommendation of the ChatGPT for particular patients and the clinical score of the agreement was calculated. Results showed that ChatGPT provided mostly general answers regarding chemotherapy, breast surgery, radiation therapy, chemotherapy, and antibody therapy. It was able to identify risk factors for hereditary breast cancer and point out the elderly patient indicated for chemotherapy to evaluate the cost/benefit effect. ChatGPT wrongly identified the patient with Her2 1+ and 2+ (FISH negative) as in need of therapy with trastuzumab and called endocrine therapy “hormonal treatment”. Support of artificial intelligence by finding individualized and personalized therapy for our patients is unavoidable in this time of rapidly expanding amount of information. ChatGPT has the potential to find its spot in clinical medicine, but the current version is not able to provide specific recommendations for the therapy of patients with primary breast cancer.

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