AI Medical Compendium Topic

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Neuroma, Acoustic

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The impact of artificial intelligence in the diagnosis and management of acoustic neuroma: A systematic review.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Schwann cell sheaths are the source of benign, slowly expanding tumours known as acoustic neuromas (AN). The diagnostic and treatment approaches for AN must be patient-centered, taking into account unique factors and preferences.

Accuracy of vestibular schwannoma segmentation using deep learning models - a systematic review & meta-analysis.

Neuroradiology
UNLABELLED: Vestibular Schwannoma (VS) is a rare tumor with varied incidence rates, predominantly affecting the 60-69 age group. In the era of artificial intelligence (AI), deep learning (DL) algorithms show promise in automating diagnosis. However, ...

Prediction of facial nerve outcomes after surgery for vestibular schwannoma using machine learning-based models: a systematic review and meta-analysis.

Neurosurgical review
Postoperative facial nerve (FN) dysfunction is associated with a significant impact on the quality of life of patients and can result in psychological stress and disorders such as depression and social isolation. Preoperative prediction of FN outcome...

Automatic Segmentation of Vestibular Schwannoma From MRI Using Two Cascaded Deep Learning Networks.

The Laryngoscope
OBJECTIVE: Automatic segmentation and detection of vestibular schwannoma (VS) in MRI by deep learning is an upcoming topic. However, deep learning faces generalization challenges due to tumor variability even though measurements and segmentation of V...

Development and application of explainable artificial intelligence using machine learning classification for long-term facial nerve function after vestibular schwannoma surgery.

Journal of neuro-oncology
PURPOSE: Vestibular schwannomas (VSs) represent the most common cerebellopontine angle tumors, posing a challenge in preserving facial nerve (FN) function during surgery. We employed the Extreme Gradient Boosting machine learning classifier to predic...

The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas.

Scientific reports
Linear and volumetric analysis are the typical methods to measure tumor size. 3D volumetric analysis has risen in popularity; however, this is very time and labor intensive limiting its implementation in clinical practice. This study aims to show tha...

Quality of Information Provided by Artificial Intelligence Chatbots Surrounding the Management of Vestibular Schwannomas: A Comparative Analysis Between ChatGPT-4 and Claude 2.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
OBJECTIVE: To examine the quality of information provided by artificial intelligence platforms ChatGPT-4 and Claude 2 surrounding the management of vestibular schwannomas.

Artificial Intelligence in Temporal Bone Imaging: A Systematic Review.

The Laryngoscope
OBJECTIVE: The human temporal bone comprises more than 30 identifiable anatomical components. With the demand for precise image interpretation in this complex region, the utilization of artificial intelligence (AI) applications is steadily increasing...

A fully automatic radiomics pipeline for postoperative facial nerve function prediction of vestibular schwannoma.

Neuroscience
Vestibular schwannoma (VS) is the most prevalent intracranial schwannoma. Surgery is one of the options for the treatment of VS, with the preservation of facial nerve (FN) function being the primary objective. Therefore, postoperative FN function pre...