Diagnosis Support by Machine Learning Using Posturography DataTeruKamogashira
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Machine learning algorithms can help analyze posturography data to diagnose vestibular dysfunction. An evaluation of various algorithms found that gradient boosting had the best performance with an AUC of 0.90. While deep learning did not perform best, optimizing algorithm parameters is important. Larger, multi-institutional clinical datasets may improve machine learning's ability to accurately diagnose vestibular disorders from posturography data.
Responses from the trapezoid body in the Mongolian gerbilTeruKamogashira
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The study recorded responses from 80 fibers in the trapezoid body of the Mongolian gerbil. 26 fibers responded best to sounds in the ipsilateral ear and 54 to the contralateral ear. Many onset responses were observed, which is unusual compared to other mammals like cats. Onset responses occurred over a similar depth as primary-like responses. This suggests more diversity in response types of neurons in the gerbil anteroventral cochlear nucleus than in cats.
Diagnosis Support by Machine Learning Using Posturography DataTeruKamogashira
?
Machine learning algorithms can help analyze posturography data to diagnose vestibular dysfunction. An evaluation of various algorithms found that gradient boosting had the best performance with an AUC of 0.90. While deep learning did not perform best, optimizing algorithm parameters is important. Larger, multi-institutional clinical datasets may improve machine learning's ability to accurately diagnose vestibular disorders from posturography data.
Responses from the trapezoid body in the Mongolian gerbilTeruKamogashira
?
The study recorded responses from 80 fibers in the trapezoid body of the Mongolian gerbil. 26 fibers responded best to sounds in the ipsilateral ear and 54 to the contralateral ear. Many onset responses were observed, which is unusual compared to other mammals like cats. Onset responses occurred over a similar depth as primary-like responses. This suggests more diversity in response types of neurons in the gerbil anteroventral cochlear nucleus than in cats.
#4: Thirty rats (350-450 g) of the Sprague-Dawley strain (Hilltop Labs, Scottsdale, PA) were anesthetized with urethan (1.5?g/kg; Sigma) and placed in a stereotaxic apparatus. The body temperature of the rat was kept constant by a small animal thermoregulation device. The scalp was removed, and a small (1.2?×?1.2?mm) bone window was drilled above the hippocampus (centered at AP?=?3.5 and L?=?2.5?mm from bregma) for extra- and intracellular recordings. A pair of stimulating electrodes (100??m each, with 0.5-mm tip separation) were inserted into the left fimbria-fornix (AP?=?1.3, L?=?1.0,?V?=?3.95) to stimulate the commissural inputs. Extracellular and intracellular electrodes were mounted on two separate manipulators on opposite sides of a Kopf stereotaxic apparatus. The horizontal axes of the two manipulators were parallel. The manipulator of the extracellular electrode was mounted at a 10° angle from vertical to permit the subsequent placement of the intracellular electrode. The optimal distance between the electrodes at the brain surface to cause the tips to arrive at the same point at the level of the hippocampus (2?mm deep) was calculated to be ~370 ?m. The extracellular electrode was lowered into the cell body layer of CA1 by monitoring for the presence of unit activity and evoked field potentials. Once the intracellular and extracellular electrode tips were placed in the brain, the bone window was covered by a mixture of paraffin (50%) and paraffin oil (50%) to prevent drying of the brain and decrease pulsation. The intracellular micropipette was then advanced into the region near the extracellular electrode, and an intracellular recording from a CA1 pyramidal cell was obtained. If no extracellular and intracellular pairs were encountered after advancing the micropipette through the CA1 pyramidal layer and stratum radiatum, the intracellular electrode was withdrawn, and a new intracellular electrode track was made from the cortical surface.