Aprendizaje automático y modelos de clasificación
Eldocumento presenta las características más importantes de modelos de clasificación basados en análisisdiscriminante y máquinas de vectoressoporte, siendo el análisis discriminante un método que permite identificar lascaracterísticas que diferencian a
Luis Jaime Andrade González +1 more
doaj
El proyecto se centra en la predicción temprana del riesgo cardiovascular incidente en población joven mediante la evaluación y comparación de tres algoritmos de aprendizaje automático: Regresión Logística, Random Forest y Redes Neuronales.
Milton Daniel Chicaiza Criollo +1 more
doaj
Uso de inteligencia artificial en la predisposición genética a enfermedad crítica por COVID-19: evaluación comparativa de modelos de aprendizaje automático. [PDF]
Martin Perez S +9 more
europepmc +1 more source
Predicting outcome of daycare cognitive behavioural therapy in a naturalistic sample of patients with PTSD: a machine learning approach. [PDF]
Stuke H +6 more
europepmc +1 more source
Immune-related biomarkers for major depressive disorder identified via integrated bioinformatics and machine learning. [PDF]
Zhang Y, Wu P, Nie Z, Liu Z.
europepmc +1 more source
Can machine learning predict PTSD symptoms from trauma narratives of children and adolescents? [PDF]
Giuliani A +5 more
europepmc +1 more source
Trends in health literacy discussions within primary health care research: A topic analysis using machine learning techniques. [PDF]
Damar M +6 more
europepmc +1 more source
Predicting depressive symptoms through social support: a machine learning approach in military populations. [PDF]
Chen KH, Chiu PL, Chen MH.
europepmc +1 more source
Using explainable machine learning to investigate the relationship between childhood maltreatment, positive psychological traits, and CPTSD symptoms. [PDF]
Zhou X, Liang Z, Zhang G.
europepmc +1 more source
[Clinical reasoning and artificial intelligence. [PDF]
Cuestas E.
europepmc +1 more source

