Artificial Intelligence Algorithms in Predictive Factors for Hematologic Toxicities During Concurrent Chemoradiation for Cervical Cancer.

The most recent research conducted for the International Federation of Gynecology and Obstetrics indicates that, depending on the stage of cervical cancer (CC), several therapies can provide similar overall survival and progression-free survival rates. To determine the hematologic toxicities during concurrent chemotherapy for cervical cancer, we evaluated these two therapies (cisplatin or carboplatin). Hematologic markers have been studied using statistical models and descriptive statistics. Artificial intelligence models were built using the treatment data and all the information gathered from each patient after one or more administrations to forecast the CC stage. The information was gathered from stage III cervical cancer patients and provided by Oncohelp Hospital from the West Region of Romania. Many traditional machine learning techniques, such as naïve Bayes (NB), random forest (RF), decision trees (DTs), and a trained transformer called TabPFN, were used in the current study to obtain the tabular data. The algorithms NB, RF, and DTs yielded the greatest classification score of 100% when it came to cervical cancer prediction. On the other hand, TabPFN demonstrated an accuracy of 88%. The effectiveness of the models was evaluated by computing the computational complexity of traditional machine learning methods. Early detection increases the likelihood of a good prognosis during the precancerous and malignant stages. Being aware of any indications and symptoms of cervical cancer can also help to prevent delays in diagnosis. These hematologic toxicities, which have been demonstrated to grow linearly with lowering hematologic markers below their normal expectations, would significantly impair patients' quality of life.
Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Ethics Committee of "Pius Brinzeu" Emergency County Clinical Hospital Timisoara issued approval No 285/18.03.2022. This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of "Pius Brinzeu" Emergency County Clinical Hospital Timisoara (No 285/18.03.2022). Informed Consent Statement: Not applicable. . Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.
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