El rol de la inteligencia artificial en el método de estimación de pose para el diagnóstico temprano de la parálisis cerebral infantil: avances en la medicina de diagnóstico por imagen.
The role of artificial intelligence in the pose estimation method for early diagnosis of cerebral palsy: advances in diagnostic medical imaging
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Uno de los métodos tradicionales para el diagnóstico de la parálisis cerebral infantil es la evaluación de la motricidad general, que analiza la calidad y complejidad de los movimientos del bebé mediante la inspección visual de los movimientos espontáneos. Sin embargo, esta evaluación es subjetiva y requiere personal clínico altamente capacitado, lo que puede ser costoso y consumir mucho tiempo. Para superar
esta limitación, actualmente se están desarrollando soluciones basadas en visión por computadora para analizar los movimientos de los bebés. Estos análisis se basan en la estimación de la pose, obtenida a partir de modelos de inteligencia artificial, y posteriormente se utilizan algoritmos de clasificación también basados en inteligencia artificial para determinar si los movimientos son normales o anormales.
En este artículo, se presenta el uso de la estimación de pose como método de visión por computadora para analizar los movimientos inquietos en niños con parálisis cerebral y se comparan estos movimientos estimados con cómo se clasifican mediante algoritmos de inteligencia artificial. Finalmente, se identifican algunos desafíos y perspectivas futuras sobre esta tecnología.
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