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This article reviews the historical evolution and technical progress of flexible touch panel technologies, from rudimentary single\u2010point touch to sophisticated grid\u2010free touch systems. Additionally, the working principles and mechanisms that underpin these advanced systems, including capacitive, resistive, piezoelectric, and triboelectric nanogenerator technologies, are explored. Following this, the integration of machine learning methods into these panels is discussed, offering new avenues for enhancing user experience and expanding functional capabilities. Various machine learning algorithms such as support vector machines, artificial neural networks, convolutional neural networks, and <jats:italic>k<\/jats:italic>\u2010nearest neighbors are examined for their potential applications in touch panel technologies. 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