World Neurosurg
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Machine learning (ML) is an application of artificial intelligence (AI) that gives computer systems the ability to learn data, without being explicitly programmed. Currently, ML has been successfully used for optical character recognition, spam filtering, and face recognition. The aim of the present study was to review the current applications of ML in the field of neuro-oncology. ⋯ MLBAs in neuro-oncology have been shown to predict patients' outcomes more accurately than conventional parameters in a retrospective analysis. If their high diagnostic accuracy in imaging analysis and detection of somatic mutations are corroborated in prospective studies, the use of tissue diagnosis or liquid biopsy might be curtailed. Finally, MLBAs are promising to help guide targeted therapy, can lead to personalized medicine, and open areas of study in the cancer cellular signaling system, not otherwise known.
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We described the imaging findings of small cell lung carcinoma metastasis to atypical meningioma and the importance of magnetic resonance imaging perfusion graphics at the differential diagnosis. To be able to determine subtypes of meningiomas and differentiate whether they are malignant or benign may provide a preoperative idea to determine prognosis and surgical procedure.
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To delineate the most recommendable treatment of spontaneous intracerebral hemorrhages and the indication for surgery, its timing, and the best surgical technique to be adopted case by case. ⋯ Careful selection of patients eligible for surgery is mandatory. The optimal timing falls into a time-window ranging between 7 and 24 hours after ictus. Minimal invasive techniques are valuable surgical options for patients in a poor GCS score or harboring large deep-seated hemorrhages.
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Primary orbital involvement is extremely rare in echinococcosis. We report a case of giant orbital hydatid cyst in a 15-year-old boy. ⋯ Hydatic cyst should be kept in differential diagnosis of orbital cystic lesions, especially in pediatric population and endemic areas.
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The modified 5-item frailty index (mFI-5) is a concise comorbidity-based risk stratification tool that has been shown to predict the occurrence of adverse outcomes following various orthopedic surgeries. ⋯ Higher mFI-5 scores were associated with increased postoperative morbidity following elective 1- to 2-level posterior lumbar fusions.