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Evaluating ChatGPT as an Adjunct for the Multidisciplinary Tumor Board Decision–Making in Primary Breast Cancer Cases
Open accessPublished version of a preprint
Abstract
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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“In the realm of pharmaceutical research, ChatGPT can contribute by sifting through vast volumes of scientific literature, identifying potential drug candidates, and suggesting innovative research directions.”
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“It can assist in drug discovery, research proposal writing, and summarising complex medical research, expediting the research process [11,24,34,35,36,37,38].”
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Cited by
Sorted by citations
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“However, the current version cannot provide specific recommendations, emphasizing the need for dedicated AI software for this purpose [100–102].”
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Utilizing large language models in breast cancer management: systematic review
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BackgroundMethodResultInfluentialA descriptive study based on the comparison of ChatGPT and evidence-based neurosurgeons
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“ChatGPT can provide general basic answers regarding medical knowledge, lifestyle, treatment, and radiology.(15,28) Haemmerli et al.”
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“The literature search yielded six studies [28,44,47,78,84,102] which noted the highest accuracy ranging from 88 to 98% for information extraction and question-answering tasks in relation to breast cancer diagnosis and management, but accuracy variations and the presence of erroneous outputs mean…”
Griewing, S., Knitza, J., Boekhoff, J., Hillen, C., Lechner, F., Wagner, U., Wallwiener, M., & Kuhn, S. (2024) · Archives of Gynecology and Obstetrics · doi:10.1007/s00404-024-07565-4 · Cited by 38
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ChatGPT's Gastrointestinal Tumor Board Tango: A limping dance partner?
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“A similar observation of generic advice aligning with MTB recommendations was made in the study by Lukac et al., although they did not differentiate between generic and personalized advice due to their study ’ s limited size of ten patients [13].”
MethodRoldan‐Vasquez, E., Mitri, S., Bhasin, S., Bharani, T., Capasso, K., Haslinger, M. L., Sharma, R., & James, T. A. (2024) · Journal of Surgical Oncology · doi:10.1002/jso.27715 · Cited by 34
“11 Patient education is a key factor impacting patient experience and treatment outcomes in breast cancer.”
Ho, C., Tian, T., Ayers, A. T., Aaron, R. E., Phillips, V., Wolf, R. M., Mathioudakis, N. N., Dai, T., & Klonoff, D. C. (2024) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-024-02757-z · Cited by 33
Assessing the accuracy and reliability of ChatGPT’s medical responses about thyroid cancer
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Schmidl, B., Hütten, T., Pigorsch, S. U., Stögbauer, F., Hoch, C. C., Hussain, T., Wollenberg, B., & Wirth, M. (2025) · Scientific Reports · doi:10.1038/s41598-025-85920-4 · Cited by 29
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Quality of ChatGPT-Generated Therapy Recommendations for Breast Cancer Treatment in Gynecology
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“In contrast to the results of Lukac et al., 2023, who used primary breast cancer cases and compared it with their multidisciplinary tumor board recommendation, we found the HER-2 treatment recommendation to be the most reliable one [11].”
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“5 and tumor boards (Lukac et al. 2023; Sorin et al. 2023).”
Schmidl, B., Hütten, T., Pigorsch, S. U., Stögbauer, F., Hoch, C. C., Hussain, T., Wollenberg, B., & Wirth, M. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1455413 · Cited by 25
ChatGPT and generative AI in urology and surgery—A narrative review
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“35 In Korea, ChatGPT and GPT-4 were tested on the general surgery board exams.”
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“Similar studies to ours have been conducted with breast cancer patients: one study used ChatGPT to support individualized and personalized therapy, but found that “the current version is not able to provide specific recommendations for the therapy of patients with primary breast cancer” [31].”
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“…feedback, and enhancing its awareness of uncertainty and information-seeking behaviors may improve the medical advice provided by LLMs. Lukac et al [27] evaluated ChatGPT as an adjunct for decision-making in primary breast cancer cases and stated that the eloquence of ChatGPT based on several…”
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ChatGPT in surgery: a revolutionary innovation?
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“One study assessed Chat-GPT’s ability to outline the best treatment plan for patients with a primary diagnosis of early breast cancer by benchmarking its answers with their own treatment recommendations [23].”
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Levin, G., Gotlieb, W. H., Ramirez, P. T., Meyer, R., & Brezinov, Y. (2024) · BJOG An International Journal of Obstetrics & Gynaecology · doi:10.1111/1471-0528.17929 · Cited by 11
Large language models in cancer: potentials, risks, and safeguards
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“Several studies have shown that LLMs can make treatment decisions for patients with oncological and cardiovascular diseases that are in substantial agreement with the respective treatment decisions made by clinical experts on tumor boards [4-7] and heart teams (HTs) [8].”
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Applications of Large Language Models (LLMs) in Breast Cancer CarePreprint
Sorin, V., Glicksberg, B. S., Barash, Y., Konen, E., Nadkarni, G. N., & Klang, E. (2023) · medRxiv · doi:10.1101/2023.11.04.23298081 · Cited by 11
“%) evaluated the performance of ChatGPT on actual patient data 13-15 , as opposed to two studies that used data from the internet 16,17 13,15 , and Choi et al. used LLM for information extraction from ultrasound and pathology reports 14 , ( Figure 2 ).”
BackgroundMethodMeyer, B., Kfuri‐Rubens, R., Schmidt, G., Tariq, M., Riedel, C., Recker, F., Riedel, F., Kiechle, M., & Riedel, M. (2025) · International Journal of Gynecology & Obstetrics · doi:10.1002/ijgo.70251 · Cited by 10
Rinderknecht, E., von Winning, D., Kravchuk, A. P., Schäfer, C., Schnabel, M. J., Siepmann, S., Mayr, R., Grassinger, J., Goßler, C., Pöhl, F., et al. (2024) · Current Oncology · doi:10.3390/curroncol31110520 · Cited by 10
“The initial prompts were developed by MM based on previous LLM queries and relevant studies [11–16,18 ,19 ].”
Generative artificial intelligence powered chatbots in urology
Khawaja, Z., Adhoni, M. Z. U., & Byrnes, K. G. (2025) · Current Opinion in Urology · doi:10.1097/mou.0000000000001280 · Cited by 9
ChatGPT-Assisted Decision-Making: An In-Depth Exploration of the Human–AI Interaction
Mustata, M. A., Iliescu, D., Mavriș, E., Jude, C.-R., Bojor, L., Tudorache, P., Cîrdei, I. A., Hrab, D.-E., Aluculesei, A.-C., Răpan, I., et al. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2499165 · Cited by 10
“However, for breast cancer treatments, it showed only 16.05% congruence with a multidisciplinary tumor board’s recommendations (Lukac et al., 2023).”
InfluentialArtificial intelligence as treatment support in breast cancer: current perspectives
Lukac, S., Putz, F., Micheli, G. D., Corti, C., Janni, W. J., Tolaney, S. M., Curigliano, G., Loibl, S., Tarantino, P., & Leone, J. P. (2025) · The Breast · doi:10.1016/j.breast.2025.104564 · Cited by 9
“Lukac et al. [1] re-ported a pilot study conducted on 10 consecutive cases of patients with early BC discussed in MTB.”
Li, Y., Gao, W., Luan, Z., Zhou, Z., & Li, J. (2023) · Cureus · doi:10.7759/cureus.48670 · Cited by 11
“By analyzing mammograms, ChatGPT can identify suspicious regions and offer insights to radiologists, potentially enhancing early diagnosis rates [12,20,21].”
BackgroundAccuracy and Reproducibility of ChatGPT Responses to Breast Cancer Tumor Board Patients
Liao, N., Li, C., Gradishar, W. J., Klimberg, V. S., Roshal, J. A., Yuan, T., Agarwala, S. S., Valero, V. K., Swain, S. M., Margenthaler, J. A., et al. (2025) · JCO Clinical Cancer Informatics · doi:10.1200/cci-25-00001 · Cited by 7
Large language models in thyroid diseases: Opportunities and challenges
Zhang, Y., Li, P., Xu, L., Zhang, X., Ji, H., & Wang, Y. (2025) · EngMedicine · doi:10.1016/j.engmed.2025.100076 · Cited by 7
Development and evaluation of large-language models (LLMs) for oncology: A scoping review
Mehan, N., Desinghe, T. D., & Saha, A. (2025) · PLOS Digital Health · doi:10.1371/journal.pdig.0000980 · Cited by 7
“Other languages include Chinese [53], Korean [72], Spanish [58], and German [42,46].”
Nabieva, N., Brucker, S. Y., & Gmeiner, B. (2024) · Cancers · doi:10.3390/cancers16244163 · Cited by 8
“However, the performance was weak, achieving only 16.05% congruence with the tumor board, probably due to using the older version 3.5 [30].”
InfluentialBüyükceran, E. U., Seyfettin, A., Babatürk, A., Özkan, M. B., Çolak, D., Ünal, İ., Kaymaz, E., Ergün, E., Emer, M. Ö., & Mersin, H. H. (2025) · Journal of Medical Systems · doi:10.1007/s10916-025-02314-9 · Cited by 6
“Lukac et al., also focusing exclusively on breast cancer, found only 16.05% concordance in their evaluation [11, 14 ] Future research should focus on larger, multicenter prospective studies to assess the feasibility and reliability of LLMs in real-time clinical environments.”
InfluentialTriantafyllidis, A. K., Segkouli, S., Kokkas, S., Alexiadis, A., Lithoxoidou, E. E., Manias, G., Antoniades, A., Votis, K., & Tzovaras, D. (2025) · Healthcare · doi:10.3390/healthcare14010045 · Cited by 6
ChatGPT utilization within the building blocks of the healthcare services: A mixed-methods study
Shojaei, P., Khosravi, M., Jafari, Y., Mahmoudi, A. H., & Hassanipourmahani, H. (2024) · Digital Health · doi:10.1177/20552076241297059 · Cited by 7
Bader, S., Schneider, M. O., Psilopatis, I., Anetsberger, D., Emons, J., & Kehl, S. (2024) · Zeitschrift für Geburtshilfe und Neonatologie · doi:10.1055/a-2411-9516 · Cited by 5
“Die Autoren kamen zu dem Schluss, dass vor allem die bereitgestellten Informationen und deren Präsentation wichtig für die Vorhersage - kraft von KI-Anwendungen ist [11].”
InfluentialAbdullayev, N., Kottlors, J., Habibov, H., Yilmaz, F., Zimmer, C., Hokamp, N. G., Lennartz, S., Valiyev, V., Abbasli, C., Goertz, L., et al. (2025) · European Journal of Surgical Oncology · doi:10.1016/j.ejso.2025.110384 · Cited by 7
Yaşar, Y., Demır, M., Cantürk, A., ÖZYILMAZ, S., Turgan, A. H., & Ağaçkaya, Y. (2026) · Academic Radiology · doi:10.1016/j.acra.2026.01.017 · Cited by 5
De la Torre-Trillo, J., Yáñez Castillo, Y., Melgarejo Segura, M. T., Carmona Sánchez, E., Zambudio Munuera, A., Mora-Delgado, J., & López Luque, A. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15062130 · Cited by 5
“Lukac et al. found total agreement rates of 61.4% in primary breast cancer, decreasing to 48% in advanced cases [25], figures very similar to our localized and metastatic prostate subgroups.”
InfluentialLukac, S., Griewing, S., Leinert, E., Dayan, D., Heitmeir, B., Wallwiener, M., Janni, W., Fink, V., & Ebner, F. K. (2024) · Clinics and Practice · doi:10.3390/clinpract15010008 · Cited by 5
“However, these results confirm previous experience that, in everyday clinical practice, ChatGPT can be more supportive for the patient than for doctors [24,34].”
Masur, L., Driller, M. W., Suppiah, H. T., Matzka, M., Sperlich, B., & Düking, P. (2025) · JMIR Formative Research · doi:10.2196/71358 · Cited by 4
A systematic review on the generative AI applications in human medical genetics
Changalidis, A. I., Barbitoff, Y. A., Nasykhova, Y. A., & Glotov, A. S. (2026) · Frontiers in Genetics · doi:10.3389/fgene.2025.1694070 · Cited by 6
“…Lukac et al. (2023) assessed ChatGPT’s ability to contribute to multidisciplinary tumor board decisions for breast cancer patients: it lacked specificity and occasionally misclassified biomarker interpretations, highlighting current limitations in reliability for case-level recommendations [141].”
İsmayılov, R., Altundağ, Ö., & Akçalı, Z. (2025) · Immunotherapy · doi:10.1080/1750743x.2025.2580272 · Cited by 4
Goh, S. S. N., Mariappan, R., Tan, G. S. W., Yao, J., Hew, F. M., Yeo, Y., Ow, S. G. W., Koh, W. Y., Kumarakulasinghe, N. B., Tan, T. H., et al. (2025) · JCO Clinical Cancer Informatics · doi:10.1200/cci-24-00243 · Cited by 4
Lamberti, G., Panzuto, F., Massironi, S., Cives, M., Salvia, A. L., Spada, F., Faggiano, A., Pusceddu, S., Albertelli, M., Tafuto, S., et al. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-02274-x · Cited by 4
“%) and the moderate ratings documented in glioma adjuvant therapy decision-making (median overall agreement 5/10) 20,21 .”
Prabhakaran, S., Bell, S. W., Lee, J. C., & Kong, J. C. H. (2026) · European Journal of Surgical Oncology · doi:10.1016/j.ejso.2026.111741 · Cited by 4
Applications of large language models in tumor boards: a systematic review
Konzmann, B., Henkel, M. J., Breit, C., & Wetterauer, C. (2026) · Oncology Reviews · doi:10.3389/or.2026.1757059 · Cited by 6
Taşkaldıran, I., Önder, Ç. E., Gökbulut, P., Koç, G., & Kuşkonmaz, Ş. M. (2024) · Digital Health · doi:10.1177/20552076241278692 · Cited by 4
Riedel, M., Meyer, B., Kfuri‐Rubens, R., Riedel, C., Amann, N., Kiechle, M. B., & Riedel, F. (2025) · Acta Obstetricia Et Gynecologica Scandinavica · doi:10.1111/aogs.15123 · Cited by 4
“21 Accordingly, we found that GPT-4 excelled at conveying general surgical outcomes, but—according to our clinical experts—lacked the necessary depth for detailed and accurate responses.”
Schmidl, B., Hoch, C. C., Walter, R., Wirth, M., Wollenberg, B., & Hussain, T. (2025) · Discover Oncology · doi:10.1007/s12672-025-02798-4 · Cited by 4
Akinniyi, O., Dixon, J., Aina, J., Weaks, F., Saleh, G. A., Rahman, M. M., Meeker, T. J., Trivedi, H., Gichoya, J. W., & Khalifa, F. (2025) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2025.109036 · Cited by 3
Artificial intelligence in breast surgery: Current applications, challenges, and future perspectives
Khajeh, M., Farshidmehr, P., Rahimpour, E., Amiri, P., & Shahram, M. A. (2026) · Journal of International Medical Research · doi:10.1177/03000605251412124 · Cited by 4
“51,52 For instance, AI-enabled smart bandages with integrated biosensors can monitor wound moisture, pH, and temperature in real time, triggering alerts when infection is suspected.”
Jiang, H., Yang, C., Zhou, W., Yin, C.-L., Zhou, S., He, R., Ran, G., Wang, W., Wu, M., & Yu, J. (2026) · JMIR Medical Informatics · doi:10.2196/68182 · Cited by 3
“Notably, the recommendations provided by ChatGPT for the clinical management of early-diagnosed breast cancer closely align with decisions made by multidisciplinary teams (MDTs) [13].”
Delourme, S., Redjdal, A., Jacques Bouaud, A., & Brigitte Séroussi, A. (2024) · Methods of Information in Medicine · doi:10.1055/a-2528-4299 · Cited by 3
Kaplan, S. T. (2025) · Oncology Research and Treatment · doi:10.1159/000545231 · Cited by 3
“Although Omni could recommend appropriate treatments based on molecular pro fi les for advanced solid tumors, it sometimes deviated from established clinical guidelines in complex scenarios [11, 12].”
Artificial intelligence as an adjunct tool for breast oncologists – are we there yet?
Schlam, I. M., Menezes, M. C. S., Corti, C., Tan, A., Abuali, I. A., & Tolaney, S. M. (2023) · ESMO Open · doi:10.1016/j.esmoop.2023.101643 · Cited by 3
“However, another recent study by Lukac et al.(13) utilizing ChatGPT as a supportive tool for multidisciplinary tumor board in patients with early breast cancer noted that neoadjuvant treatments were not considered by ChatGPT, HER2 expression interpretation was incorrect, and, as expected, recent studies were not incor…”
ResultClinical Application of Large Language Models for Breast Conditions: A Systematic ReviewPreprint
Cheung, B. H. H., Poon, K. G., Lai, C. F., Lam, K. C., Co, M. T.-H., & Kwong, A. (2024) · medRxiv · doi:10.1101/2024.08.31.24312542 · Cited by 3
“[21, 22] Concordance rate was highest for recommendations on radiotherapy (95%), followed by chemotherapy (94.7%), endocrine therapy (75%), genetic testing (70%).”
BackgroundInfluentialLiao, W., Li, M., Ma, C., Han, Y., Wang, D., Liu, H., Wang, Y., Feng, Z., Wang, H., & Guan, Y. (2026) · Journal of Medical Internet Research · doi:10.2196/83188 · Cited by 2
“These findings are highly consistent with previous studies by Lukac et al [63] and Liu et al [64], both of whom emphasized the importance of AI’s ability to generate dependable treatment recommendations.”
Palzer, J., Genchev, A., Belger, E., Weigle, C. A., Wiemann, B. A., Tessmer, P., Murad, M., Berres, M., Meister, F., Amygdalos, I., et al. (2026) · Cancers · doi:10.3390/cancers18132175 · Cited by 2
“The utility of LLMs as part of an MTB has been addressed in recent studies for various cancer entities [5,6].”
The role of artificial intelligence in precision medicine for breast cancer
Hu, J.-J., Ding, Z.-L., & Yang, Z. (2026) · Discover Oncology · doi:10.1007/s12672-026-05550-8 · Cited by 3
“…in January 2023 involving 10 consecutive BC patients discussed in an MDT. ChatGPT incorrectly identified patients with HER2 1 + and 2+ (FISH-negative) as requiring antibody therapy, used the less precise term “hormone therapy” instead of “endocrine therapy” and provided only generic answers [89].”
Can ChatGPT be used as a scientific source of information on tooth extraction?
Yamamoto, S., Hamada, M., Nishiyama, K., Motoki, A., Fujita, Y., & Uzawa, N. (2025) · Journal of Oral and Maxillofacial Surgery Medicine and Pathology · doi:10.1016/j.ajoms.2025.02.009 · Cited by 2
Roeschl, T., Hoffmann, M., Hashemi, D., Rarreck, F., Hinrichs, N., Trippel, T. D., Gröschel, M. I., Unbehaun, A., Klein, C., Kempfert, J., et al. (2024) · medRxiv · doi:10.1101/2024.11.20.24313385 · Cited by 2
Schmidl, B., Hoch, C. C., Shoykhet, M., Weiser, T., Pigorsch, S. U., Stögbauer, F., Wollenberg, B., Hussain, T., & Wirth, M. (2025) · Research Square · doi:10.21203/rs.3.rs-5648998/v1 · Cited by 2
Metadata
- Authors
- Lukac, S., Dayan, D., Fink, V., Leinert, E., Hartkopf, A., Veselinovic, K., Janni, W., Rack, B., Pfister, K., Heitmeir, B., & Ebner, F.
- Affiliations
- University Hospital Ulm (DE)
- Corresponding author
- Lukac, Stefan
- ORCID
- Venue
- Archives of Gynecology and Obstetrics
- Published
- 2023-07-17
- Volume
- 308
- Issue
- 6
- Pages
- 1831-1844
- ISSN
- 0003-9128 (ISSN-L)
- 1432-0711
- PMC
- PMC10579162
- OpenAlex
- W4384558920
- Cited by
- 130
- References
- 23
- Citations by year
- 2026: 32 · 2025: 44 · 2024: 45 · 2023: 9
- FWCI
- 5.17
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Archives of Gynecology and Obstetrics (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Universitätsklinikum Ulm
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Breast Cancer Treatment Studies
- Keywords
- ChatGPT, large language models, multidisciplinary tumor board, primary breast cancer, early breast cancer, treatment decision-making, clinical implementation of AI, HER2-positive breast cancer, endocrine therapy, personalized treatment
- MeSH terms
- Aged, Antibodies, Artificial Intelligence, Breast Neoplasms, Female, Humans, Oncogenes, Pilot Projects
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