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1.
Cancers (Basel) ; 15(9)2023 Apr 25.
Article in English | MEDLINE | ID: covidwho-2319332

ABSTRACT

Worldwide, the coronavirus has intensified the management problems of health services, significantly harming patients. Some of the most affected processes have been cancer patients' prevention, diagnosis, and treatment. Breast cancer is the most affected, with more than 20 million cases and at least 10 million deaths by 2020. Various studies have been carried out to support the management of this disease globally. This paper presents a decision support strategy for health teams based on machine learning (ML) tools and explainability algorithms (XAI). The main methodological contributions are: first, the evaluation of different ML algorithms that allow classifying patients with and without cancer from the available dataset; and second, an ML methodology mixed with an XAI algorithm, which makes it possible to predict the disease and interpret the variables and how they affect the health of patients. The results show that first, the XGBoost Algorithm has a better predictive capacity, with an accuracy of 0.813 for the train data and 0.81 for the test data; and second, with the SHAP algorithm, it is possible to know the relevant variables and their level of significance in the prediction, and to quantify the impact on the clinical condition of the patients, which will allow health teams to offer early and personalized alerts for each patient.

2.
Chemistryselect ; 7(31), 2022.
Article in English | Web of Science | ID: covidwho-2003642

ABSTRACT

3,5-Di[(E)-arylidene]-1-[3-(4-methylpiperazin-1-yl)alkyl]piperidin-4-ones 7 a-k were synthesized through dehydrohalogenation of 1-(2-chloroacyl)piperidin-4-ones 5 a-k with N-methylpiperazine (6). High antiproliferation potencies were observed by most of the synthesized agents against both HCT116 (colon) and MCF7 (breast) cancer cell lines relative to the standard references (sunitinib and 5-fluorouracil). The synthesized agents are of dual activity against topoisomerases I and II alpha however, with higher efficacy against topoisomerase II alpha rather than topoisomerase I. Flow-cytometry cell cycle studies support the observed antiproliferation properties and exhibit the capability of 1-(2-chloroacetyl)-3,5-bis[(E)-4-chlorobenzylidene]piperidin-4-one (5 e) and 3,5-bis[(E)-4-bromobenzylidene]-1-[2-(4-methylpiperazin-1-yl)acetyl]piperidin-4-one (7 g) to arrest the HCT116 cell cycle progression at G1/S and G1 phases, respectively. Noticeable anti-SARS-CoV-2 properties were observed by many synthesized agents. 3,5-Bis[(E)-4-chlorobenzylidene]-1-[3-(4-methylpiperazin-1-yl)propanoyl]piperidin-4-one (7 f) is the most effective anti-SARS-CoV-2 synthesized with high SI. Applicability of the highly effective candidates synthesized as antitumor and anti-SARS-CoV-2 is due to the safety observations against normal (RPE1 and VERO-E6) cells. QSAR models validated internally and externally, support their possibility for optimizing more hits/leads.

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