Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.

Purpose: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review article presents computerized approaches for the analysis of narrative language and identification of language disorders in children.

Method: We first describe the current barriers to clinicians' use of language sample analysis, narrative language sampling approaches, and the data processing stages that precede analysis.

Fibula fixation is not associated with a higher rate of wound complications during pilon fracture open reduction internal fixation.

Introduction: There is a lack of consensus regarding indications for fibula fixation in pilon fractures. Reduction of the fibula fracture can assist with restoring lateral column length and reduction of the tibial plafond during pilon ORIF. However, there are theoretical concerns with wound complications and soft tissue insult.

Behavioral Response Modeling to Resolve Listener- and Stimulus-Related Influences on Audiovisual Speech Integration in Cochlear Implant Users.

Objectives: Speech intelligibility is supported by the sound of a talker's voice and visual cues related to articulatory movements. The relative contribution of auditory and visual cues to an integrated audiovisual percept varies depending on a listener's environment and sensory acuity. Cochlear implant users rely more on visual cues than those with acoustic hearing to help compensate for the fact that the auditory signal produced by their implant is poorly resolved relative to that of the typically developed cochlea.