Detecting Methotrexate in Pediatric Patients Using Artificial Neural Networks

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Udgivet i:Applied Sciences vol. 15, no. 1 (2025), p. 306
Hovedforfatter: Alejandro Medina Santiago
Andre forfattere: Bermúdez Rodríguez, Jorge Iván, Orozco Torres, Jorge Antonio, Guzmán Rabasa, Julio Alberto, Villegas Izaguirre, José Manuel, Gladys Falconi Alejandro
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MDPI AG
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024 7 |a 10.3390/app15010306  |2 doi 
035 |a 3153575485 
045 2 |b d20250101  |b d20251231 
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100 1 |a Alejandro Medina Santiago  |u Instituto Nacional de Astrofísica, Óptica y Electrónica, Coordinación de Ciencias Computacionales—Conahcyt, Santa María Tonanzintla, San Andres Cholula, Puebla 72840, Mexico; Universidad de Ciencia y Tecnología Descartes, Avenida Ciprés 480, Tuxtla Gutiérrez 29065, Mexico; <email>jorge.ot@tuxtla.tecnm.mx</email> 
245 1 |a Detecting Methotrexate in Pediatric Patients Using Artificial Neural Networks 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Methotrexate is an antimetabolic agent with proliferative and immunosuppressive activity. It has been demonstrated to be an effective treatment for acute lymphoblastic leukemia (ALL) in children. However, there is evidence of an association between methotrexate and toxicity risks, which influences the personalization of treatment, particularly in the case of childhood ALL. This article presents the development and implementation of an algorithm based on artificial neural networks to detect methotrexate toxicity in pediatric patients with acute lymphoblastic leukemia. The algorithm utilizes historical clinical and laboratory data, with an effectiveness of 99% in the tests performed with the patient dataset. The use of neural networks in medicine is often linked to disease diagnosis systems. However, neural networks are not only capable of recognizing examples but also hold very important information. For this reason, one of the main areas of application of neural networks is the interpretation of medical data. In this article, we diagnose, with the application of neural networks in medicine, a concrete example: detecting methotrexate in its early stages in pediatric patients. 
653 |a Patients 
653 |a Anemia 
653 |a Mucositis 
653 |a Toxicity 
653 |a Leukemia 
653 |a Cancer therapies 
653 |a Mobile communications networks 
653 |a Vitamin B 
653 |a Neural networks 
653 |a Medical research 
653 |a Lymphocytes 
653 |a Pharmacokinetics 
653 |a Data analysis 
653 |a Bone marrow 
653 |a Genotype & phenotype 
653 |a Genes 
653 |a Enzymes 
653 |a Pediatrics 
653 |a Cell cycle 
653 |a Chemotherapy 
653 |a Drug dosages 
700 1 |a Bermúdez Rodríguez, Jorge Iván  |u Universidad de Ciencia y Tecnología Descartes, Avenida Ciprés 480, Tuxtla Gutiérrez 29065, Mexico; <email>jorge.ot@tuxtla.tecnm.mx</email>; Tecnológico Nacional de México, Instituto Tecnológico de Tuxtla Gutiérrez, Carretera Panamericana Km. 1080, Tuxtla Gutiérrez 29050, Mexico 
700 1 |a Orozco Torres, Jorge Antonio  |u Universidad de Ciencia y Tecnología Descartes, Avenida Ciprés 480, Tuxtla Gutiérrez 29065, Mexico; <email>jorge.ot@tuxtla.tecnm.mx</email>; Tecnológico Nacional de México, Instituto Tecnológico de Tuxtla Gutiérrez, Carretera Panamericana Km. 1080, Tuxtla Gutiérrez 29050, Mexico 
700 1 |a Guzmán Rabasa, Julio Alberto  |u Tecnológico Nacional de México, IT Hermosillo, Av. Tecnológico y Periférico Poniente S/N, Hermosillo 83170, Mexico; <email>jaguzmanrabasa@gmail.com</email> 
700 1 |a Villegas Izaguirre, José Manuel  |u Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Boulevard Universitario #1000, Unidad Valle de las Palmas, Tijuana 21500, Mexico; <email>villegas_josemanuel@uabc.edu.mx</email> 
700 1 |a Gladys Falconi Alejandro  |u Secretaria Académica, Universidad Politécnica del Golfo de México, Carretera Federal Malpaso—El Bellote Km. 171 / Monte Adentro, Paraíso, Tabasco 86600, Mexico; <email>gladys.falconi@updelgolfo.mx</email> 
773 0 |t Applied Sciences  |g vol. 15, no. 1 (2025), p. 306 
786 0 |d ProQuest  |t Publicly Available Content Database 
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